rafmacalaba/data-use-annotate

1[{"key": "paddy2-000", "text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:011890:38:1:0", "start": 565, "end": 598, "surface": "household expenditure survey data", "probe_tag": "keep", "probe_score": 0.9572, "luna_label": 1, "luna_reason": "Survey data supports quantified enrollment gaps across expenditure quintiles."}, {"key": "fcv_pads_east_africa:011890:38:1:1", "start": 870, "end": 881, "surface": "survey data", "probe_tag": "keep", "probe_score": 0.9348, "luna_label": 1, "luna_reason": "Survey data supports reported enrollment-rate comparisons and separation limitations."}]}, {"key": "paddy2-001", "text": "1.5. Distribution by Educational Status_**\n\nThe RAP Census also sought information on the educational status or the highest grade\ncompleted of all persons, ten years and over who were not attending school at the time of the\ncensus.\n\nOn aggregate, about 45 percent of the residents of the three localities were illiterate. When\neducational status was further cross classified by locality, the illiterates in _Chifrgoch_ and in\n_Gebriel Sefer_ constituted more than 48 and 39 percent respectively. In a similar survey for the\ntown, conducted during the preparation of the Structure Plan, in 2009, the illiteracy rate was\nfound to be only 28 percent. The wide gap is a further indication of a lower welfare level for\nresidents of the three localities when compared to the Town as a whole. More than 62 percent\nwere below the high school level and 3.4 percent had religious/traditional education (in a priest\nschool). Only 1.5 percent had college degrees, many of whom are probably teachers from\nelsewhere, but living in the Town.\n\n##### **_2.5.2.1.6. Students Currently Attending School_**\n\nIn the three localities of _Adishade_, _Chifrgoch_ and _Gebriel Sefer_, 728 students were identified as\nattending schools at the time of the census. There were 157 students at primary first cycle\nlevel, 256 at primary second cycle and 204 at secondary level. A total of 34 students did not\nstate their grade level. It is also interesting to note that females outnumber males at all levels of\nprimary and secondary education. It can be assumed that most or perhaps many of the students\nattending above the grade 12 level were likely to be outside of Lalibela Town. At any rate, it\ncan also be assumed that the resettlement is not likely to affect the attendance of students at\nhigher levels. Any likely impact on attendance of", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:013676:23:1:1", "start": 501, "end": 528, "surface": "similar survey for the\ntown", "probe_tag": "keep", "probe_score": 0.9002, "luna_label": 1, "luna_reason": "Past survey supports the reported 28 percent illiteracy finding."}]}, {"key": "paddy2-002", "text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:018315:38:1:0", "start": 565, "end": 598, "surface": "household expenditure survey data", "probe_tag": "keep", "probe_score": 0.9572, "luna_label": 1, "luna_reason": "Existing survey data supports concrete enrollment-rate comparisons."}]}, {"key": "paddy2-003", "text": "**9.** **CONCLUSION AND RECOMMENDATIONS**\n\n\nThe Environment Impact Assessment for Augmentation and Rehabilitation of Gatanga\nWater Supply identified that the population pressure of Gatanga district is growing at a\nsteady 2.426% per annun form the population statistics form the census report 2009 now\nstanding at 130,000 people. The current water infrastructure can only provide 6,310\nm3/day against an estimated demand of 9880m3/day leaving a deficit of 3,570m3/day.\nThe proposed project is step towards providing water close to the people of Gatanga\ndistrict.\n\nNegative environmental impacts identified in the report can be mitigated as illustrated in\nthe Environmental Management Plan and proper monitoring throughout construction and\noperation phases of the project is advised.\n\nThere is overwhelming acceptance by the project by the local community in the areas of\nGitemi, Ndakaini, Gitiri, Gatur, Gathaithi, Rwagetha, Chomo and Gatanga sub locations.\nThe areas are experiencing inadequate water supply leaving residents with the option of\ngoing for raw water plants which is not treated therefore leaving them exposed to water\nborne diseases such as typhoid and diarrhea.\n\nRecommendation is therefore for implementation of the above project with compliance to\nrecommendations outlined in the Environment Management Plan and resident and other\nstakeholder views as described in chapter six of the report.", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:020355:91:0:0", "start": 247, "end": 268, "surface": "population statistics", "probe_tag": "keep", "probe_score": 0.9472, "luna_label": 1, "luna_reason": "Census statistics support the reported population growth estimate."}, {"key": "fcv_pads_east_africa:020355:91:0:1", "start": 278, "end": 296, "surface": "census report 2009", "probe_tag": "keep", "probe_score": 0.9168, "luna_label": 1, "luna_reason": "2009 census report supports the stated population statistics and growth finding."}]}, {"key": "paddy2-004", "text": "**The World Bank**\nKENYA GPE COVID 19 LEARNING CONTINUITY IN BASIC EDUCATION PROJECT (P174059)\n\n\n10. Private returns to education are high in Sub-Saharan Africa, where one additional year of education\nrepresents on average a 12.4 percent increase in expected income, higher than the global average of 9.7\npercent. These returns also increase with education level. For higher education the regional average is 21\npercent, while the returns to primary and secondary education are 14.4 and 10.6 percent, respectively. As\nshown in the figure below, in Kenya, the average expected income also increases according to the highest\neducation level attended.\n\n\n**Figure 3.1. Median annual wage of paid employees (main job), 15-64 years old,**\n\n**by highest education level attended**\n\n\n\n\n\n\n\n\n\n\n\n_Source:_ Kenya Integrated Household Budget Survey 2015/16.\n\n11. Beneficiaries from this project include about 60 percent of primary and secondary school students\naccessing online and distance learning. An estimated 150,000 teachers will benefit from training in online\nand distance learning. In addition, students will benefit from online-based psychosocial support services\nand about 1.75 million learners will benefit from the school meals program. The expected positive\noutcomes are therefore higher retention rates, as the pandemic might increase dropouts, affecting\nparticularly harder children from poorer households and young girls. Costs are equivalent to the total cost\nof the project, which will disburse US$10.8 million over a period of 18 months.\n\n\n12. The analysis assumed that without the project, a share of students currently enrolled in either primary or\nsecondary education would drop out. Due to the current uncertainty regarding treatments/vaccines,\nduration of the lockdown, economic impacts on households’ income, and students’ dropouts and learning\noutcomes, a few different scenarios were considered. It was assumed that those households in the bottom\nquintiles (the poorest 40 percent)", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:008471:72:0:0", "start": 795, "end": 835, "surface": "Kenya Integrated Household Budget Survey", "probe_tag": "keep", "probe_score": 0.9306, "luna_label": 1, "luna_reason": "Named survey cited as the source for the wage figure."}]}, {"key": "paddy2-005", "text": "ratio and student textbook ratios show high degree of disparities, and are significantly higher in\nrural schools than in urban public schools. Beside public funds, SDI data also show that parental\ncontribution varies substantially among schools and is insufficient to offset the shortfall in\ncapitation grant. If anything, there is a slight positive (but insignificant) correlation between the\namount of parent contribution and the total amount of capitation funds that the school received.\n(iv) Lack of instructional related resources: One of the immediate consequences of the insufficient\nfunding is its impacts on textbook availability. Textbooks, once vetted by the Kenya Institute of\nCurriculum Development (KICD), are listed in the Orange Book and sold by the publishers directly\nto schools. In some cases, books are reaching the schools but then are damaged through usage or\ntaken to be sold at the market. With the increasing textbook price, currently the yearly capitation\ngrant can only cover 2 out of 6 required textbooks for primary students. In many schools, the\ntextbook stock is not well maintained (wear and tear and more worriedly the textbook theft\nprevalence), resulting in on average three students sharing one textbook, with few students being\nable to take textbooks home for further reference. Students do not have sufficient textbooks and\nother learning materials to adequately learn in classrooms. Based on SDI data, the current student/\ntextbook ratio for math is 2:6 and the ratio is higher for public and rural schools. Teacher reference\nmaterials are also in very short supply and often non-existent.\n(v) Lack of support and accountability at the system level and ineffective management at the\nschool level. Curriculum implementation is not carried out adequately across schools, with rural\nschools suffering most from teachers absent from class teaching. Formally all teachers are civil\nservants employed by the Teacher Service Commission and most of their monetary and nonmonetary incentives are decided centrally in spite of one’s performance in teaching and the\nconsequent learning achievement thereof. While well performing schools pay a", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:017318:5:0:0", "start": 164, "end": 172, "surface": "SDI data", "probe_tag": "keep", "probe_score": 0.9536, "luna_label": 1, "luna_reason": "SDI data supports findings on parental contributions and textbook ratios."}]}, {"key": "paddy2-006", "text": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:fcv_pads_east_africa:017781:62:2:0", "start": 688, "end": 697, "surface": "1999 data", "probe_tag": "confusion", "probe_score": 0.5672, "luna_label": 0, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:017781:62:2:1", "start": 758, "end": 796, "surface": "Development Economics central database", "probe_tag": "keep", "probe_score": 0.9023, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-007", "text": " activities, and from common\nproperty; (c) the extent to which groups will experience total or partial loss of assets; (d)\npublic infrastructure and social services that will be affected; (e) formal and informal\ninstitutions (such as community organizations, ritual groups, etc.) that can assist with\ndesigning and implementing the resettlement programs; and (f) attitudes on resettlement\noptions. Socioeconomic surveys, recording the names of affected families, should be\nconducted as early as possible to prevent inflows of population ineligible for\ncompensation.\n\n\n\n**Le2al** **Framework**\n\n12. A clear understanding of the legal issues involved in resettlement is needed to design\na feasible resettlement plan. An analysis should be made to determine the nature of the\n\nlegal framework for the resettlement envisaged, including (a) the scope of the power of\neminent domain, the nature of compensation associated with it, both in terms of the\nvaluation methodology and the timing of payment; (b) the legal and administrative\nprocedures applicable, including the appeals process and the normal time-frame for such\nprocedures; (c) land titling and registration procedures; and (d) laws and regulations\nrelating to the agencies responsible for implementing resettlement and those related to\nland compensation, consolidation, land use, environment, water use, and social welfare.\n\n\n\n**Alternative** **Sites** **and Selection**\n\n13. The identification of several possible relocation sites and the demarcation of selected\nsites is a critical step for both rural and urban resettlement. For land-based resettlement,\nthe new site's productive potential and locational advantages should be at least equivalent\n\n\n\n_These policies were prepared for use_ **_by_** _World_ _Bank staff_ **_and_** _(ire_ **_not necessarily_** _a_ _conmplete_ _treatnment of the_ _subject._", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:021018:70:1:0", "start": 398, "end": 419, "surface": "Socioeconomic surveys", "probe_tag": "confusion", "probe_score": 0.2821, "luna_label": 0, "luna_reason": "Surveys are planned to be conducted, so the data do not yet exist."}]}, {"key": "paddy2-008", "text": " Project**\n\n\nThe mission by an IDA environment specialist to the Republic of Djibouti in June 2000 confirmed the\ndegraded situation of the sanitary facilities in all of the schools visited. Discussions with school staff and\nparents of students revealed the concern felt by the latter regarding the adverse effects of the situation on\nthe students. The keeping of photographic archives was begun during this mission.\n\n\nThe impacts considered will not be due solely to the project but also to the prevailing situation, which is\ncharacterized by significant degradation of the existing facilities. Since a particular aim of the project is\nto increase the capacity of schools, the main environmental measure to be included in the project will be\nto construct or rehabilitate the sanitary facilities of these schools, and to design a system of upkeep and\nmaintenance that will ensure the appropriate functioning of the schools.", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:010834:65:1:0", "start": 363, "end": 384, "surface": "photographic archives", "probe_tag": "confusion", "probe_score": 0.2148, "luna_label": 0, "luna_reason": "Photographic archives were begun during the mission, indicating new data production."}]}, {"key": "paddy2-009", "text": "312 activities allocated and US $\n3,707,113 disbursed. The number of beneficiaries was 7,528 of which 2,966 (39%) were women. The grant distribution ratio in terms of activities supported outside Kampala stands\nat 36% which is 6% above the target.\n\nComponent 3 - Improving business environment - For Land;\n\n- Revival and rehabilitation of the School of Surveying (renamed Institute of Surveying and Land Management – ISLM) to train professionals for modern land administration\nand Development and approval of a new Curriculum for ISLM. A total of about 40 students have been graduating every year since 2005/6.\n\n- Construction/renovation of 13 land offices, Land Information Center, Records & Archival Center & a Resource Center at ISLM and Rehabilitation and basic computerization\nof land records in the mailo land registry in Kampala for records of Kampala, Wakiso and Mukono districts;\n\n- Scanned all leasehold and freeholds, majority of maps and part of mailo land records and Built a geodetic control & base mapping infrastructure to support LIS development\nin 6 Ministry of lands zonal offices (MZOs)\n\n- Developed a comprehensive national land information system (NLIS) and Undertook an inventory of government land in 5 districts.\n\n- Local Area Network (LAN) completed at Kampala City Council Authority, Jinja, Wakiso, Entebbe, Masaka & Mbarara; the Internet connectivity and data conversion and integration\nhas been for all these offices.\n\n- Approval of new staffing structures for Ministry Zonal Offices (MZO) has been done and Ministry of Lands, Housing and Urban Development staff have been posted in MZOs.\n\n- Disbursement to ING France who installed the land information system - A total of about US$8 m has been paid and there is a balance of US$3m which has been\ncommitted and will be paid by project closure, February 2 8, 2013.\n\nFor Business registry - Computers were purchased", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:016737:1:1:0", "start": 805, "end": 824, "surface": "mailo land registry", "probe_tag": "confusion", "probe_score": 0.3662, "luna_label": 0, "luna_reason": "Registry is named, but its records are not shown informing analysis or decisions."}, {"key": "fcv_pads_east_africa:016737:1:1:1", "start": 1122, "end": 1168, "surface": "comprehensive national land information system", "probe_tag": "confusion", "probe_score": 0.1236, "luna_label": 0, "luna_reason": "The project developed the land information system; this is production, not existing data use."}]}, {"key": "paddy2-010", "text": " Project**\n\n\nThe mission by an IDA environment specialist to the Republic of Djibouti in June 2000 confirmed the\ndegraded situation of the sanitary facilities in all of the schools visited. Discussions with school staff and\nparents of students revealed the concern felt by the latter regarding the adverse effects of the situation on\nthe students. The keeping of photographic archives was begun during this mission.\n\n\nThe impacts considered will not be due solely to the project but also to the prevailing situation, which is\ncharacterized by significant degradation of the existing facilities. Since a particular aim of the project is\nto increase the capacity of schools, the main environmental measure to be included in the project will be\nto construct or rehabilitate the sanitary facilities of these schools, and to design a system of upkeep and\nmaintenance that will ensure the appropriate functioning of the schools.", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:009424:65:1:0", "start": 363, "end": 384, "surface": "photographic archives", "probe_tag": "confusion", "probe_score": 0.2148, "luna_label": 0, "luna_reason": "Photographic archives were begun during the mission, indicating data production rather than existing use."}]}, {"key": "paddy2-011", "text": "required for local government involvement, and arrangements for maintenance, monitoring and\nevaluation (M&E). Social capital enhancing activities would be a mandatory part of all sub-projects, and\nwould be tailored to support activities chosen by the communities.\n\nSupport to Decentralized Government Structures. Most local administrations are beginning\nto operate again with a limited number of staff and other inputs. District and chiefdom authorities are\nvery weak, however, and lack the financial and human resources needed to address their concerns and\npnorities effectively. NGOs have demonstrated their ability to implement successful community-based\nsocial and economic projects and have played a key role in shelter reconstruction activities. With the\ngradual strengthening of local government capacity, partnerships between community groups and local\nauthorities are expected to increase. Upon completion of initial training, district and chiefdom authorities\nwould be required to demonstrate that they have used the training by showing that there have been some\nimprovements in their community. For instance, at the end of each training session, district authorities\nwould be required to develop a simple action plan that specifies some activities that NSAP or other\npartners could support. District and chiefdom authorities would also gain experience in implementing,\nsupporting or overseeing community development activities.\n\nHealth. The unfavorable health indicators in Sierra Leone can be attributed to several factors.\nHigh fertility, female genital mutilation and the presence of HIV/AIDS increase morbidity and mortality\nrisks for women and children. Many risk factors that have contributed to HIV/AIDS epidemics in other\nAfrican countries have long been present in Sierra Leone, and the protracted conflict has created the\nconditions for explosive growth in HIV/AIDS infection rates. The Centers for Disease Control carried\nout a survey in 2002 which found the HIV prevalence among adults (aged 1549) to be 6.1 %; in\nFreetown, 4% in rural areas and 4.9% nationwide. In response to the crisis, Government has developed\na multi-sector HIV/AIDS Program, which is being supported by various", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:015609:10:0:0", "start": 1950, "end": 1964, "surface": "survey in 2002", "probe_tag": "confusion", "probe_score": 0.7887, "luna_label": 1, "luna_reason": "Past survey attributed HIV prevalence findings to CDC data."}]}, {"key": "paddy2-012", "text": "s were built to\nmanage the disposal of dead animals and medical waste; (viii) out of 42 grievances recorded, 40 were resolved\nsatisfactorily. Implementing agencies followed biosafety rules, including constructing incinerators for used needles\nand other medical and laboratory wastes. Several areas need improvement, including limited capacity at the Woreda\nlevels, resistance to using PPE, delays in land acquisition and certification, waste management challenges, and\ninadequate monitoring due to security issues. Additionally, there is a lack of clear information on the E&S\nassessment and preparation of E&S risk instruments for Component B activities and activities during the CERC\nactivation period. The rating remains **Moderately Satisfactory** with substantial risks. See Annex 6 for more detail.\n\n\n**Procurement Performance**\n\n\nThe procurement performance has shown a slight upward trend, with the total estimated cost of planned\nand executed activities reaching USD 81.5 million. Completed procurement activities account for 32.5% of the total\nplanned, while pending activities make up 34%, and those signed and under implementation represent 33%. Key\nissues identified include: (i) Need for a comprehensive assessment and expedited implementation of pending and\nnew procurement activities; (ii) Significant variance between reported procurement performance and data in STEP\ndue to delays in updating STEP; (iii) Cancellation of an independent procurement audit, contrary to agreed\nprocedures and the Bank’s advice; (iv) Inconsistencies found in PPRs that need addressing to prevent future issues;\n(v) Challenges in collecting procurement data in the Tigray region due to limited facilities and connectivity. Overall,\nprocurement performance is rated as **Moderately Satisfactory** .\n\n**Financial Management**\n\n\nThe mission observed good progress in timely and quality IFR submission, clearance of long-outstanding\nUN advances, and consecutive internal audit reviews. The existing system provides reasonable assurance that\nproject funds are used for intended purposes, maintaining a rating of Moderately", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:004263:3:1:0", "start": 1372, "end": 1384, "surface": "data in STEP", "probe_tag": "confusion", "probe_score": 0.2895, "luna_label": 1, "luna_reason": "STEP data is compared with reported procurement performance to identify variance."}, {"key": "fcv_pads_east_africa:004263:3:1:2", "start": 1637, "end": 1653, "surface": "procurement data", "probe_tag": "confusion", "probe_score": 0.0659, "luna_label": 0, "luna_reason": "Data collection is described as an ongoing challenge, not use of existing data."}]}, {"key": "paddy2-013", "text": "sup>recently</sup> <sup>come</sup> <sup>under Government control.</sup>\n\n\n\n**2.** **Main sector** issues **and** <sup>**Government strategy:**</sup>\n\n\n\n_Sector Issues._\n_Poverty in Sierra Leone._ Sierra <sup>Leone has</sup> <sup>the lowest</sup> <sup>Human Development Index</sup> <sup>**in**</sup> <sup>the world</sup>\n\n\n\nand has a GNP per capita <sup>of only US$130</sup> <sup>compared</sup> <sup>to the average</sup> <sup>for Sub-Saharan</sup> <sup>Africa</sup> <sup>of $470.</sup>\n\n\n\nOver 82% of the population <sup>currently</sup> <sup>lives below</sup> <sup>the poverty line and life expectancy is only</sup> <sup>38 years.</sup>\n\n\n\nFertility, infant and child <sup>mortality are</sup> <sup>high</sup> <sup>and over</sup> <sup>a third</sup> <sup>of children and</sup> <sup>a fourth</sup> <sup>of adults</sup> <sup>are</sup>\n\n\n\nmalnourished. The pnmary <sup>school enrollment</s", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:009511:7:1:0", "start": 251, "end": 274, "surface": "Human Development Index", "probe_tag": "confusion", "probe_score": 0.8186, "luna_label": 1, "luna_reason": "Named index supports Sierra Leone's lowest-in-world ranking."}]}, {"key": "paddy2-014", "text": "contracts), setting the Bank’s prior review threshold at US$10 million for all contracts with a risk rating of\nsubstantial and below, declaration of mis-procurement for the misapplication of the rated criteria weightings, direct\npayment for all high value contracts, and the removal of reference to the publication in the United Nations\nDevelopment Business Online (UNDB Online). This will apply to the Upper check dam (UCD) works contract and\ntherefore its procurement is now urgent. **The Bank team will continue to monitor progress regularly and**\n**support MoWSI/PMU on these actions and any other emerging issues including organizing technical visits**\n**for specific discussions.**\n\n\n**20.** **This Aide Memoire has 8 annexes as follows:**\n\n\nAnnex 1: Overview of next steps and key agreed actions\nAnnex 2: Overview of the 10 issues from May 9, 2024, letter, status and agreed actions\nAnnex 3: Overview of main community complaints, status and agreed actions\nAnnex 4: Detailed progress by sub-component\nAnnex 5: People met during the mission\nAnnex 6: Results Framework", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:fcv_pads_east_africa:002105:5:0:0", "start": 322, "end": 364, "surface": "United Nations\nDevelopment Business Online", "probe_tag": "confusion", "probe_score": 0.2508, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-015", "text": " were now\nwalking along streets with lights, rather than taking motorized transport to their destinations. Some participants pointed\nout that accidents between vehicles and between vehicles and pedestrians had declined. Some mentioned that business\nhours had expanded and that the appearance and livability of the urban center had improved. The net present value of\nthis intervention was estimated at US$40.8 million and the internal rate of return is estimated at 56 percent.\n\n5. The sensitivity analysis performed indicates that the economic rate of return for interventions under Subcomponent 1.2 remain significant even when considering potential downside adjustments to the assumptions made as\n\n\n40 Based on data collection from informal settlements as part of KISIP1.\n\n\nPage 63 of 69", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:010786:63:2:0", "start": 713, "end": 754, "surface": "data collection from informal settlements", "probe_tag": "confusion", "probe_score": 0.8756, "luna_label": 1, "luna_reason": "Existing informal-settlement data collection is cited as the basis for analysis."}, {"key": "fcv_pads_east_africa:010786:63:2:1", "start": 766, "end": 772, "surface": "KISIP1", "probe_tag": "confusion", "probe_score": 0.3812, "luna_label": 0, "luna_reason": "Identifies the project conducting the data collection, not an existing data resource."}]}, {"key": "paddy2-016", "text": " which will define a specific quota for women<br>engineers, and gap analysis and activities to promote their participation in internship<br>programs, and a minimum 30 percent of project cost allocated for supporting this activity<br>will target women.|The project will support an internship program, which will define a specific quota for women<br>engineers, and gap analysis and activities to promote their participation in internship<br>programs, and a minimum 30 percent of project cost allocated for supporting this activity<br>will target women.|\n|Citizen Engagement, Share of<br>target beneficiaries with<br>rating ‘Satisfied’ or above on<br>project interventions<br>(Percentage)|0.00|Jun/2020|0.00|15-Jun-2024|0.00|15-Jun-2024|60.00|Jun/2028|\n|Citizen Engagement, Share of<br>target beneficiaries with<br>rating ‘Satisfied’ or above on<br>project interventions<br>(Percentage)|Comments on<br>achieving  targets|Comments on<br>achieving  targets|This indicator estimates demand-side social accountability through engagement with project<br>beneficiaries and the extent to which project activities and outcomes are meeting<br>beneficiaries’ demands. This is based on a perception survey administered on a<br>representative sample to representative local communities/beneficiaries including<br>Vulnerable and Marginalized Groups (VMGs) and focus on the management of social and<br>environmental risks and impacts, management of security forces, the selection process of<br>the selected local social infrastructure, and quality of construction of the social<br>infrastructure. Survey results will be disaggregated by gender.|This indicator estimates demand-side social accountability through engagement with project<br", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:001083:9:5:0", "start": 1174, "end": 1191, "surface": "perception survey", "probe_tag": "confusion", "probe_score": 0.2386, "luna_label": 1, "luna_reason": "Indicator is based on an administered perception survey of representative beneficiaries."}]}, {"key": "paddy2-017", "text": " 4.91 10.31 55.2 10.12 **~** **1** **1** 54.9 **1** **-** 9.96 54.4\n###### --- \nTotal 6.18 7.73 18.68 100.0 18.43 100.0 18.31 100.0\n\n_Source: National Health Accounts Study_\n\n\n\nTotal 6.18 7.73 18.68 100.0 18.43 100.0 18.31 100.0", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:011157:76:1:0", "start": 142, "end": 166, "surface": "National Health Accounts", "probe_tag": "confusion", "probe_score": 0.3994, "luna_label": 1, "luna_reason": "Named study cited as the source of table data."}]}, {"key": "paddy2-018", "text": "**Annex 1:** **Project** **Design** **Summary**\n\n**SIERRA LEONE:** **NATIONAL** **SOCIAL ACTION** **PROJECT**\n\n\n. **Hierarchy o.Qbijctives -'**  - . **diator** **r**, t **,P** **jCitidaI** **r!** **As's-umptIons,Y-**\n**Sector-related** **CAS** **Goal:** **Sector** **Indicators:** **Sector/ country reports:** **(from** **Goal** **to Bank** **Mission)**\nMitigate the risk of renewed 1. National conflict/security- - UNHCR/OCHA reports - Continued peace and\n**conflict** **and lay foundation** related indicators - Household Income and regional security\n**for** **poverty reduction and** 2. Inter-regional disparities in Expenditure Surveys - Economic and political\n**improvements** **in nutrition,** I-PRSP & PRSP core - PETS surveys stability\n**health, education** **and** indicators - Strategic Planning and\n**targeting** **the rural** 3. Inter-regional disparities in Action Process (SPP) reports\n**population,** women **and** Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** *", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:017262:29:0:0", "start": 590, "end": 639, "surface": "Inter-regional disparities in Expenditure Surveys", "probe_tag": "confusion", "probe_score": 0.6578, "luna_label": 0, "luna_reason": "Standalone table indicator text, not an analyzed or cited data resource."}, {"key": "fcv_pads_east_africa:017262:29:0:1", "start": 721, "end": 733, "surface": "PETS surveys", "probe_tag": "confusion", "probe_score": 0.8347, "luna_label": 1, "luna_reason": "Named survey type listed as a source for sector and country indicators."}]}, {"key": "paddy2-019", "text": "assistance to the Companies Register to enable the Registry clear the backlog in filing and allow\nfor speedy and accurate information sharing of corporate information and data; and b) combining\nof the Charges Register and the Chattel Mortgage Register into one; moving the combined\nseparate register (notification system) for charges/pledges over movable assets out of the\nCompanies Register and developing a new Personal Property Securities Act (i.e., secured\ntransactions framework) in line with international best practices; (ii) improvements in the land\nregistration system through digitizing land records; (iii) establishment of a legal and regulatory\nframework for the operation of a credit reference bureau that would facilitate the much needed\ninformation flow among the credit granting institutions; and (iv) the review of impediments to\nthe growth of the leasing industry, including tax laws on leasing.\n\n_CBK- Banking Supervision Department (BSD)_\n\n164. _Credit reference bureaus licensed and operational_ (Implementing Agency: CBK-BSD):\nFLSTAP funded a consultancy to support BSD staff in licencing CRBs, workshops on CRBs,\ncapacity building of BSD staff, and purchase of ICT office equipment. The introduction of two\nCredit Reference Bureaus (Jun 2010) and CRB regulations drafted with project support (Feb\n2009) contributed to the steady reduction of credit risks and NPLs.\n\n165. _Comprehensive legal and regulatory framework._ FLSTAP financed a consultant to assist\nEAD in preparing a draft policy paper and Consumer Protection Law 2012. The project also\nfinanced a market survey and preparation of proposals for increasing access to lease financing. to\nfurther enhance broader access to financial services\n\n_Transform manual system of land records to a digitized recording and storage system_\n_(Implementing Agency: Ministry of Lands)_\n\n166. The ICR ROSC Update for Kenya found the land registry of Kenya to be inefficient,\noutdated and burdened with inadequate practices. The improvement of the situation in terms of\norganization", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:020971:63:0:2", "start": 1898, "end": 1920, "surface": "land registry of Kenya", "probe_tag": "confusion", "probe_score": 0.3683, "luna_label": 1, "luna_reason": "ICR ROSC Update reports an assessment finding about Kenya’s land registry."}]}, {"key": "paddy2-020", "text": " foundation for democratic and sustainable local\n\n\n\ndevelopment. The Community Development Program will finance social and economic\ninfrastructure and support social capital building activities to facilitate the restoration of basic\nsocial services such as health and education and provide an incentive for teachers, health workers\nand displaced persons to return to their communities. The Rural Public Works and Shelter\nprograms will provide employment for demobilized soldiers and unemployed youth, housing for\ndisplaced persons and feeder roads to stimulate local economic activities. The innovative\nactivities including training and technical support will strengthen local government capacity to\nplan, contract, manage and sustain investments in local development and engage a wide array of\n\n\n\nstakeholders in participatory processes that contribute to sustainable local development.\n\n\n\nTargeting will be consistent with the Government's 2002-2003 National Recovery\nStrategy and the March 3, 2002 Transitional Support Strategy. Resources will be directed to (a)\nnewly accessible areas that have not received any support in more than a decade; and (b) remote\nareas that have received little, if any support from the ongoing IDA-financed CRRP or other\nsimilar projects. The results of the living standards measurement survey currently underway will\nbe available at the end of 2003 and will be used to review the validity of existing targeting\nmodalities.\n\n\nTarget Populations: Target groups include demobilized soldiers and unemployed youth,\nrefugees, IDPs, female-headed households, child laborers, orphans, primary school dropouts,\n\n\n_- 8 -_", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:011023:12:1:0", "start": 1291, "end": 1326, "surface": "living standards measurement survey", "probe_tag": "confusion", "probe_score": 0.253, "luna_label": 0, "luna_reason": "Survey is currently underway, so its data are being produced rather than already used."}]}, {"key": "paddy2-021", "text": "**The World Bank**\nTHE NORTHEASTERN ROAD-CORRIDOR ASSET MANAGEMENT\nPROJECT 2 - (NERAMP 2) (P514937)\n\n\n\nPROJECT APPRAISAL DOCUMENT\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Description|Direct people within the host communities that benefit from improved access to sustainable transport infrastructure and<br>services|\n|---|---|\n|Frequency|Annual|\n|Data source|Progress report by implementing entities, traffic surveys, market usage surveys, and labor records|\n|Methodology for Data <br>Collection|Road condition surveys using laser profilers, HDM‑4 analysis to classify segments, GIS mapping of condition classes|\n|Responsibility for Data <br>Collection|MoWT PIU, M&E Consultant|\n|**Improved Road Safety**|**Improved Road Safety**|\n|**Reduction in fatal and serious injury crashes along the rehabilitated corridor (percentage)**|**Reduction in fatal and serious injury crashes along the rehabilitated corridor (percentage)**|\n|Description|Percentage of fatal and serious injury crashes along the corridor. Reflects safety improvements from engineering and<br>enforcement.|\n|Frequency|Semiannual|\n|Data source|National crash database, Police crash database, hospital records, community reporting, and project management reports|\n|Methodology for Data <br>Collection|Extraction from the national crash database, triangulation with district health facilities|\n|Responsibility for Data <br>Collection|Uganda Police, MoWT PIU M&E Consultant|\n|**Increased resilience and adaptation to climate change **|**Increased resilience and adaptation to climate change **|\n|**People benefiting from climate-resilient infrastructure (Number of people) **|**People benefiting from climate-resilient infrastructure (Number of people) *", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:002275:43:0:2", "start": 437, "end": 450, "surface": "labor records", "probe_tag": "confusion", "probe_score": 0.2811, "luna_label": 1, "luna_reason": "Records are declared as a data source for measuring project beneficiaries."}, {"key": "fcv_pads_east_africa:002275:43:0:5", "start": 1126, "end": 1147, "surface": "Police crash database", "probe_tag": "confusion", "probe_score": 0.3241, "luna_label": 1, "luna_reason": "Named crash database extracted to measure fatal and serious injury crashes."}]}, {"key": "paddy2-022", "text": "-EMA **&** ECON               \nEnvironmental Impact Statement for Bondo-Nebbi transmiSSion line, Uganda   - DRAFT   \n\nHe has been an important source of information for local people and has\nfacilitated consultation and information sharing all through the project. Since the\nproject has a high profile and is generally considered important to the two\ndistricts, the local governments in the two districts have chosen their top\nrepresentatives/officals to be in charge of project liason (eg. The Assistant Chief\nAdministrative Officer (CAO) in Nebbi and the Deputy Chairman in Arua).\n\n\n**Assessment** **of the** **need** **for further consultations**\n\nIt is ECON and EMA's clear view that the consultation before ECON started its\ninvolvement had already been extensive and thorough. ECON continued the close\nand frequent liason from the start of our involvement in November 2001. There is\nan enormous interest in the project locally and the clear message conveyed\nthrough the consultation process is a strong eagerness to see the project go ahead.\nThe consultation saturation point for local people may, in our opinion, be\nexceeded.\n\nThe development of the resettlement plan, and the strengthening of the EMP,\n\nshould, in our view, conclude the pre-project-development consultation process.\n\n**Record of local** **meetings**\n\nThe first section of this annex provided a general description of the consultation\nprocess regarding the West Nile Electricity Project, as far back as is known by\nECON. To our knowledge there are no offical records of the meetings that have\ntaken place before ECON's involvement commenced in November 2001, except\nfor what is documented in the various EIA studies. Further, official minutes of\nmeetings and detailed lists of participants since Nov. 2001 have not been written\ndown by ECON. These records may, however, be kept locally.\n\n\nBelow is provided the record of local meetings since Nov", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:013039:76:0:1", "start": 1883, "end": 1907, "surface": "record of local meetings", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 0, "luna_reason": "Routine project consultation records are provided, without substantive analytical use."}]}, {"key": "paddy2-023", "text": "**Annex 1:** **Project** **Design** **Summary**\n\n**SIERRA LEONE:** **NATIONAL** **SOCIAL ACTION** **PROJECT**\n\n\n. **Hierarchy o.Qbijctives -'**  - . **diator** **r**, t **,P** **jCitidaI** **r!** **As's-umptIons,Y-**\n**Sector-related** **CAS** **Goal:** **Sector** **Indicators:** **Sector/ country reports:** **(from** **Goal** **to Bank** **Mission)**\nMitigate the risk of renewed 1. National conflict/security- - UNHCR/OCHA reports - Continued peace and\n**conflict** **and lay foundation** related indicators - Household Income and regional security\n**for** **poverty reduction and** 2. Inter-regional disparities in Expenditure Surveys - Economic and political\n**improvements** **in nutrition,** I-PRSP & PRSP core - PETS surveys stability\n**health, education** **and** indicators - Strategic Planning and\n**targeting** **the rural** 3. Inter-regional disparities in Action Process (SPP) reports\n**population,** women **and** Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** *", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:017862:29:0:1", "start": 721, "end": 733, "surface": "PETS surveys", "probe_tag": "confusion", "probe_score": 0.8347, "luna_label": 1, "luna_reason": "Named PETS surveys are cited as an existing source for sector indicators."}]}, {"key": "paddy2-024", "text": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:fcv_pads_east_africa:019780:16:0:0", "start": 379, "end": 395, "surface": "statistical data", "probe_tag": "confusion", "probe_score": 0.582, "luna_label": 0, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:019780:16:0:1", "start": 1487, "end": 1500, "surface": "random survey", "probe_tag": "drop", "probe_score": 0.012, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-025", "text": "DJIBOUTI\nSchool Access and Improvement Program\n\n\n**Project Appraisal Document**\n\n\nMiddle East and North Africa Region\n\nMNSHD\n\n\n\nDate: November 17, 2000 Team Leader: Qaiser M. Khan\n\n\n\nCountry Director: Inder K. Sud Sector Director: Baudouy\nProject **ID:** P044585 Sector(s): EP - Primary Education, ES - Secondary\n\n\n\n. Education\nLending Instrument: Adaptable Program Loan <sup>(APL)</sup> Theme(s): Education; Gender and development\n\n\n\nPoverty Targeted Intervention: N\n\n\n\nProgram Fin ncing Data\n\n\n\nEstimated\nAPL Indicative Financing Plan Implementation Period (Bank FY) Borrower\n\n\n\n**IBRD** Others **Total** **COMMITMENT** **Closing**\n**US$** m % US$ m US$ m Date Date\nAPL 1 10.00 75.8 3.20 13.20 03/31/2001 06/30/2005 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\n________________ Education\n\n\n\nAPL 2 10.0 65.8 5.20 15.20 07/01/2005 06/30/2008 Republic of\n\n\n\nLoan/ Credit Djibouti\n\n\n\nCredit Ministry of\n\n\n\ni_________ ________________ Education\n\n\n\nAPL 3 10.00 41.0 14.40 24.40 07/01/2008 06/30/2011 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\nEducation\n\n\n\nTotal 30.00 22.80 52.80\nProject Financing Data Credit\nFor Loans/Credits/Others: Amount (US$m): 10.0\n\n\n\nProposed Terms: Standard Credit\n\n\n\nGrace period (years): 10 Years to maturity: 40\nCommitment fee: 0.50% (0% for FY01) Service charge: 0.75", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:013796:4:0:0", "start": 1106, "end": 1128, "surface": "Project Financing Data", "probe_tag": "drop", "probe_score": 0.0462, "luna_label": 0, "luna_reason": "Standalone table header for financing amounts, not a data-use mention."}]}, {"key": "paddy2-026", "text": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:012717:29:2:0", "start": 530, "end": 538, "surface": "M&E data", "probe_tag": "drop", "probe_score": 0.023, "luna_label": 0, "luna_reason": "Span appears inside a project output-indicator table artifact."}]}, {"key": "paddy2-027", "text": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:fcv_pads_east_africa:011960:16:0:0", "start": 379, "end": 395, "surface": "statistical data", "probe_tag": "confusion", "probe_score": 0.582, "luna_label": 0, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:011960:16:0:1", "start": 1487, "end": 1500, "surface": "random survey", "probe_tag": "drop", "probe_score": 0.012, "luna_label": 0, "luna_reason": "Staff will carry out the survey as project baseline data collection."}]}, {"key": "paddy2-028", "text": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:019177:29:2:0", "start": 530, "end": 538, "surface": "M&E data", "probe_tag": "drop", "probe_score": 0.023, "luna_label": 0, "luna_reason": "Project monitoring data listed for indicator reporting, not an independently used existing source."}]}, {"key": "paddy2-029", "text": "|Col1|Col2|Col3|Col4|Col5|system to<br>enable<br>recording<br>of G&CM<br>at the<br>county and<br>sub-<br>county<br>levels<br>through<br>the<br>programs<br>MISs, and<br>(vii) report<br>detailing<br>its<br>implement<br>ation in at<br>least 20<br>sub-<br>counties.|Col7|copy of the PIBS<br>attached.|Col9|\n|---|---|---|---|---|---|---|---|---|\n|||Beneficiary<br>outreach strategy<br>for SAU programs<br>implemented in at<br>least 20 sub-<br>counties and<br>beneficiary<br>awareness improved<br>across NSNP|This set of DLRs assesses<br>efforts to improve<br>beneficiary awareness of<br>key program parameters<br>including awareness of the<br>transfer amount and how to<br>communicate with the<br>program regarding<br>grievances and updates.<br>DLR 6b (i) assesses the<br>development and adoption<br>of a beneficiary outreach<br>strategy for the SAU<br>programs. This DLR will<br>be deemed to have been|No|Copy of<br>the<br>beneficiar<br>y outreach<br>strategy in<br>form and<br>substance<br>acceptable<br>to", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:010461:49:0:0", "start": 279, "end": 283, "surface": "PIBS", "probe_tag": "drop", "probe_score": 0.0135, "luna_label": 0, "luna_reason": "Acronym alone names no eligible data source or demonstrated data use."}]}, {"key": "paddy2-030", "text": " National Accounts. Consumption data is used to derive potential VAT, and<br>Government revenue collection data is used to ascertain actual VAT collections. The difference is the total VAT Gap,<br>from which the policy gap will be subtracted to arrive at the VAT compliance gap.|\n|Responsibility for Data<br>Collection|PMCSO (MoR)|\n\n\n|Improved Public Financial Management Capabilities|Col2|\n|---|---|\n|**Public availability of annual recurrent and capital budget execution reports and contract award information (Text)**|**Public availability of annual recurrent and capital budget execution reports and contract award information (Text)**|\n|Description|Measures the extent to which budgetary, fiscal, and procurement information is publicly disclosed in a timely manner.|\n|Frequency|Annually|\n|Data source|Ministry of Finance Website and Federal Procurement and Property Administration Agency Website|\n|Methodology for Data<br>Collection|The Federal Government consistently makes available to the public: a) the annual recurrent and capital budget<br>execution reports, and b) contract awards information, through the MoF website and e-GP website respectively,<br>starting from EFY 2018 (FY2025/26). The quality and timeliness of budgetary and fiscal information will be assessed<br>using PEFA PI-5 (Budget Documentation) and PEFA PI-9 (Public Access to Fiscal Information). The quality of<br>procurement information will be assessed using the Open Contracting Data Standard (OCDS).|\n|Responsibility for Data<br>Collection|PMCSO (MoF)|\n\n\n\n\n\n|Beneficiary Citizen Feedback|Col2|\n|---|---|\n|**Increase in civil servant beneficiaries’ experience with the quality of HRM practices (Percentage) **|**", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:fcv_pads_east_africa:004104:40:1:0", "start": 20, "end": 36, "surface": "Consumption data", "probe_tag": "drop", "probe_score": 0.0166, "luna_label": 1, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:004104:40:1:1", "start": 77, "end": 111, "surface": "Government revenue collection data", "probe_tag": "confusion", "probe_score": 0.0742, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-031", "text": "With<br>permanent heads appointed and core staff and<br>approved basisn plans in place)||Text|Comments||||\n|Water resources monitoring network<br>operational and information collected and used<br>routinely||Text|Value|limited monitorning network in<br>place|Technical design of the<br>enhanced Hydrologic<br>Information System/ Basin<br>Information System (HIS/BIS)<br>completed|Enhanced HIS/BIS water<br>resources monitoring network<br>(including radar, gauging, and<br>earth observation products)<br>for Tana and Beles sub-<br>basins operational;<br>Comprehensive Basin<br>knowledge|\n|Water resources monitoring network<br>operational and information collected and used<br>routinely||Text|Date|30-Oct-2008|15-Dec-2012|30-Sep-2013|\n|Water resources monitoring network<br>operational and information collected and used<br>routinely||Text|Comments||||\n|Endowment and Growth Framework in place<br>for theIncentives in place to enhance targeted<br>private sectorTana-Beles area||Yes/No<br>Sub Type<br> Supplemental|Value|No|No|Yes|\n\n\n\n**<u>Data on Financial Performance (as of 17-Jan-2013)</u>**\n\n\n**<u>Financial Agreement(s) Key Dates</u>**\n\n|Project|Ln/Cr/Tf|Status|Approval Date|Signing Date|Effectiveness Date|Original Closing Date|Revised Closing Date|\n|---|---|---|---|---|---|-", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:019355:3:1:0", "start": 1037, "end": 1066, "surface": "Data on Financial Performance", "probe_tag": "drop", "probe_score": 0.013, "luna_label": 0, "luna_reason": "Standalone financial-performance table heading, not a cited or analyzed data resource."}]}, {"key": "paddy2-032", "text": "8 **-**\n\n\nENVIRONMENTAL MANAGEMENT AND MONITORING PLAN FOR TIHE EMBAKASI TO MACHAKOS TURN-OFF (A104/A109)\n\n\nTable 8.1 Monitoring and Management of Impacts and Mitigation Measures on the A104/A109\n\n\n**Environmental/** **Proposed** **Mitigation** **and** **Aspects** **for** **Responsibility for** **Responsibility for** **Monitoring** **means** **Recommended frequency**\n**Social** **Impact** **Monitoring** **intervention** **and** **monitoring** **mitigation,** **monitoring** **(c)** **=** **construction** **of monitoring**\n**during design,** **construction** **and/or** **maintenance** **after** **(o)** **=** **operation**\n**and** **defects liability period** **defects** **liability period**\nChanges in hydrology - _Install drainage structures properly_ Design Engineer (c) inspection (c) during construction and\n/impeded drainage Supervising Engineer and on completion of each\nContractor structure\n\n\n\n\n              - Efficiency of drainage structures Supervising Engineer MoRPW&H Maintenance Unit (o) routine maintenance and (o) once a year\nroad condition survey\nSoil erosion - _Control earthworks_ Supervising Engineer and (c) inspection (c) daily;\n\n_-_ _Install drainage structures_ _properly_ Contractor (o) routine maintenance and erosion control measures:\n\n_-_ _Install erosion control measures_ road condition survey during construction and on\n\n              - _", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:014237:43:0:0", "start": 1049, "end": 1070, "surface": "road condition survey", "probe_tag": "drop", "probe_score": 0.0366, "luna_label": 0, "luna_reason": "Standalone monitoring-table entry, not an analyzed existing data source."}]}, {"key": "paddy2-033", "text": "**Annex 1:** **Project** **Design** **Summary**\n\n**SIERRA LEONE:** **NATIONAL** **SOCIAL ACTION** **PROJECT**\n\n\n. **Hierarchy o.Qbijctives -'**  - . **diator** **r**, t **,P** **jCitidaI** **r!** **As's-umptIons,Y-**\n**Sector-related** **CAS** **Goal:** **Sector** **Indicators:** **Sector/ country reports:** **(from** **Goal** **to Bank** **Mission)**\nMitigate the risk of renewed 1. National conflict/security- - UNHCR/OCHA reports - Continued peace and\n**conflict** **and lay foundation** related indicators - Household Income and regional security\n**for** **poverty reduction and** 2. Inter-regional disparities in Expenditure Surveys - Economic and political\n**improvements** **in nutrition,** I-PRSP & PRSP core - PETS surveys stability\n**health, education** **and** indicators - Strategic Planning and\n**targeting** **the rural** 3. Inter-regional disparities in Action Process (SPP) reports\n**population,** women **and** Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** *", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:fcv_pads_east_africa:008446:29:0:0", "start": 590, "end": 639, "surface": "Inter-regional disparities in Expenditure Surveys", "probe_tag": "drop", "probe_score": 0.0005, "luna_label": 1, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:008446:29:0:1", "start": 721, "end": 733, "surface": "PETS surveys", "probe_tag": "drop", "probe_score": 0.0465, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-034", "text": "|\n|Number of female teachers trained in<br>using remote learning methodologies<br>(online and distance learning<br>methods)|This indicator measures the<br>number of female teachers<br>trained in using remote<br>learning methodologies<br>(online and distance<br>learning methods). For data<br>collection and reporting,<br>this indicator will also<br>measure % of female<br>teachers trained in using|Semi-annual<br>|TSC<br>|TSC will collect data<br>for female teachers<br>trained using<br>the  revised training<br>package for digital<br>learning<br>|TSC (PRIEDE PCU<br>Component 1 lead will<br>obtain data from TSC )<br>|\n\n\nPage 39 of 70", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:008471:43:1:0", "start": 599, "end": 612, "surface": "data from TSC", "probe_tag": "drop", "probe_score": 0.0285, "luna_label": 0, "luna_reason": "TSC will collect these indicator data prospectively."}]}, {"key": "paddy2-035", "text": " 6.2: % of Phase 1 schools are visited by cluster<br>supervisors and key teachers at least (Text)||Not available|95.00|\n|**_Action: This indicator has been Revised_**||||\n|**Improved quality**|**Improved quality**|**Improved quality**|**Improved quality**|\n|IR Indicator 6.3: Average score of composite index of school<br>inspection standards on teaching practi (Text)||54.00|70.00|\n|**Improved quality**|**Improved quality**|**Improved quality**|**Improved quality**|\n|IR Indicator 6.4: % of actual teaching time relative to scheduled<br>instructional time in P1 schools (Text)||Time-on-task survey to be conducted in Year 1 and Year 2|To be determined|\n|**Improved quality**|**Improved quality**|**Improved quality**|**Improved quality**|\n|IR Indicator 6.5: % of students having textbooks (Text)||58.00|70.00|\n|**Improved quality**|**Improved quality**|**Improved quality**|**Improved quality**|\n\n\n\nPage 13 of 28", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:019345:12:1:0", "start": 580, "end": 599, "surface": "Time-on-task survey", "probe_tag": "drop", "probe_score": 0.0449, "luna_label": 0, "luna_reason": "Survey is explicitly planned for future conduct in Years 1 and 2."}]}, {"key": "paddy2-036", "text": "**The EU-LFS data could not be used for this study as it only has information on the wage distribution**\n\n**in deciles rather than specific point estimates.** This poses a challenge when analyzing the data, as point\n\nestimates are often needed to estimate labor income accurately. To overcome this issue, one option is\n\nto use imputation techniques to fill in the missing values. Specifically, we could use the EUSILC data,\n\nwhich provides detailed demographic characteristics and income information, to impute the missing\n\npoint estimates on the LFS data. This can help provide a more accurate representation of the wage\n\ndistribution and enable a more nuanced analysis. However, it is important to carefully consider the\n\nimputation process's potential biases and limitations and evaluate the quality of the resulting\n\nestimates, especially when several data sources (including administrative tax data) need to be imputed.\n\n\n**In this study, we match income data from the 2020 tax administrative dataset with the 2021 EU-SILC**\n\n**(reference income year 2020) using data matching techniques; then, we assess the degree of tax**\n\n**compliance and possible overestimation of the share of minimum wage earners in the tax data.**\n\nFollowing the literature, we assume that the \"true\" income is reported in the survey, while \"reported\"\n\nincome is reported to the tax authority. After imputing tax income into the EU-SILC, we assess the\n\ndegree of tax evasion and the impact of tax evasion on the share of minimum wage earners.\n\n\n**Before matching the administrative tax data and the EU-SILC datasets, it is essential to carefully**\n\n**evaluate the comparability of the datasets before conducting any analysis.** We must evaluate the\n\ncomparability of the two datasets regarding the target population and income. This involves\n\ndetermining whether the datasets are compatible and suitable for comparison. The extent of\n\ncomparability determines the accuracy of the results and the", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:001472:12:0:2", "start": 547, "end": 555, "surface": "LFS data", "probe_tag": "keep", "probe_score": 0.9405, "luna_label": 1, "luna_reason": "Existing labor-force survey data used to impute missing wage point estimates."}, {"key": "prwp:001472:12:0:7", "start": 1579, "end": 1595, "surface": "EU-SILC datasets", "probe_tag": "keep", "probe_score": 0.977, "luna_label": 1, "luna_reason": "Named EU-SILC datasets are matched and used to assess tax compliance."}]}, {"key": "paddy2-037", "text": " a & s &i a C a & r iP ba bc eif N S ub-Sorth A aharan A S outh A<br>Unified website Ministry website<br>Journal Other|Col2|1.5<br>economies<br>1<br>of<br>proportion<br>.5<br>0 incom e incom e incom e incom e<br>igh iddle iddle Low<br>H<br>m m<br>pper er<br>Low<br>U<br>Unified website Ministry website<br>Journal Other|\n|---|---|---|\n|0<br>.5<br>1<br>1.5<br>2<br>proportion of economies<br>High income: OECD<br>Europe & Central Asia<br>East Asia & Pacific<br>Latin America & Caribbean<br>Middle East & North Africa<br>Sub-Saharan Africa<br>South Asia<br>Unified website<br>Ministry website<br>Journal<br>Other<br>|||\n\n\n\n_Source:_ Citizen Engagement in Rulemaking database, World Bank Group, http://rulemaking.worldbank.org.\n_Note:_ The categories shown are not mutually exclusive. In some countries, for example, the government might use\nboth unified and ministerial websites to give notice of proposed regulations. The figure shows data only for the 136\n(of 185) economies in which the government gives notice of proposed regulations.\n\nGiven global trends in internet access, it is no surprise that the use of the internet for citizen\nengagement in rulemaking is more prevalent among high- and upper-middle-income countries.\nIndeed, unified websites are used in as many as 75 percent of high-income", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:006850:11:2:0", "start": 631, "end": 672, "surface": "Citizen Engagement in Rulemaking database", "probe_tag": "keep", "probe_score": 0.9392, "luna_label": 1, "luna_reason": "Named database supplies data underlying the figure and reported internet-use findings."}]}, {"key": "paddy2-038", "text": "help alleviate SME financing constraints? An extensive literature has shown that\n\n\naccess to external financing and firm growth are shaped by a country’s legal\n\n\ninstitutions (La Porta, Lopez-de-Silanes, Shleifer, and Vishny, 1997, 1998; Demirguc\n\nKunt and Maksimovic, 1998; Beck, Demirguc-Kunt, and Maksimovic, 2005, and\n\n\nBeck, Demirguc-Kunt, Laeven, and Maksimovic, 2006). In other words, in countries\n\n\nwith better institutional environments, financing obstacles are smaller and firms\n\n\nobtain more external financing and are able to grow faster. More importantly, recent\n\n\nresearch using firm-level data has shown that SMEs seem to benefit the most from\n\n\nimprovements in the institutional environment. Using data from 4,000 firms in 54\n\n\ncountries, Beck, Demirguc-Kunt, and Maksimovic (2005) show that marginal changes\n\n\nin the institutional environment result in financing and legal obstacles having a\n\n\nsmaller negative impact on firm growth, and this effect is larger for SMEs. Using a\n\n\nsimilar database, Beck, Demirguc-Kunt, and Maksimovic (2008) show that SMEs\n\n\ngain greater access to bank finance as a result of improvements in property rights.\n\n\nIn this paper, rather than focusing on firms’ perception regarding SME\n\n\nfinancing (as has been the case with most of the recent studies), we analyze the factors\n\n\nbanks perceive as drivers and obstacles to lending to SMEs. Of particular interest is\n\n\nthe role of the competitive and institutional environments in shaping SME lending,\n\n\nand more generally banks’ interest in dealing with SMEs. By institutional factors we\n\n\nmean the rules and regulations that affect the functioning of the financial system and\n\n\ninfluence the operation of the private sector, as well as the more general\n\n\nmacroeconomic environment that shapes financial contracts. We compare banks’\n\n\nperceptions about SMEs in Argentina and Chile. <sup>5</sup> We use a survey that", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:003988:4:0:1", "start": 714, "end": 735, "surface": "data from 4,000 firms", "probe_tag": "keep", "probe_score": 0.9544, "luna_label": 1, "luna_reason": "Existing firm data supports a cited finding on institutional effects and SME growth."}]}, {"key": "paddy2-039", "text": "**Table** **1:** Transitions among young (18-21 years old) between work statuses\n\n\n<u>No</u> <u>work</u> <u>Informal</u> <u>work</u> <u>Formal</u> <u>work</u> <u>Total</u>\n\n\nNo work 78 _._ 93 15 _._ 43 5 _._ 64 100\nInformal work 26 _._ 37 63 _._ 07 10 _._ 56 100\n<u>Formal</u> <u>work</u> <u>15</u> <u>14</u> _<u>.</u>_ <u>92</u> <u>70</u> _<u>.</u>_ <u>07</u> <u>100</u>\n\n\n<u>Total</u> <u>53</u> _<u>.</u>_ <u>06</u> <u>29</u> _<u>.</u>_ <u>09</u> <u>17</u> _<u>.</u>_ <u>85</u> <u>100</u>\n\n\n_Notes:_ Author’s calculations using panel data from 2018 and 2019 ENOE surveys.\nTable presents the average probability of maintaining or changing work status from\none period to the next. The rows reflect the initial status, and the columns reflect\nthe final status. Youth are followed for four quarters (3 month periods) between\n2018 and 2019 in staggered cohorts.\n\n\nthe probability of transitioning to formal work from non-employment (5.6%", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:prwp:001134:10:0:0", "start": 530, "end": 540, "surface": "panel data", "probe_tag": "keep", "probe_score": 0.9963, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:001134:10:0:1", "start": 560, "end": 572, "surface": "ENOE surveys", "probe_tag": "keep", "probe_score": 0.9844, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-040", "text": " OPHI MDP. Six of the variables from the MDP can be\ngenerated from the SHSD. However, the SHSD still captures only a limited number of\ndimensions of poverty, for example it does not provide information on health indicators. As\nsuch, two additional variables are derived from the accessibility analysis (Section 3.4), access\nto hospital and health facilities, and another measure, child stunting, is derived from the\n‘Multiple Indicators Cluster Surveys’ (MICS) survey dataset using a small area estimation\n(SAE). SAE uses a regression formulation to distribute aggregated household information to a\nhigher spatial resolution (e.g. from a national to a regional level), either within a survey data\n(using both aggregated and microdata) or across different surveys (Elbers et al., 2003). Here,\nwe use a regression formulation using overlapping household information in the MICS data and\nthe synthetic household data to construct one variable that is captured in the MICS data (child\nstunting) but not in the synthetic data (see Appendix B for details). We acknowledge that these\nvariables covering household health status are an incomplete measure of health. We end up\nwith nine variables to construct the MDP index as shown in Table 1.\n\nIn line with the OPHI MDP formulation, we also apply a weighting factor to the different\nvariables, such that the three groups contribute equally to the MDP. In the end, the household’s\nMDP score is the weighted sum of the individual deprivations, which scales between 0 and 1.\n\nBased on the index created, we define two levels of MDP:\n\n   - **_Moderate MDP:_** _a household has an MDP of 1/3 or higher_\n\n   - **_Extreme MDP:_** _a household has an MDP of 1/2 or higher_\n\n\n12", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:000581:13:1:2", "start": 871, "end": 880, "surface": "MICS data", "probe_tag": "keep", "probe_score": 0.9325, "luna_label": 1, "luna_reason": "MICS survey data used in regression to construct the child-stunting variable."}]}, {"key": "paddy2-041", "text": "**Figure 2. Correlation between local residuals and distance between localities**\n\n\n1.0\n\n\n0.5\n\n\n0.0\n\n\n-0.5\n\n\n\n-1.0\n\n\n\n0-25 Km 20-25 Km 25-40 Km 40-65 Km 65 + Km\n\nLinear model Quadratic model\n\n\n\n_Note:_ The legend indicates the specification chosen for the neighborhood effect. Mean values\n\nare computed at the VDC level.\n\n\n\n**8.** **Microsimulation results**\n\n\nThe microsimulations performed are based on an iterative process, using the preferred estimation\nof the hedonic price function at the household level and measures of actual destruction at the local\nlevel. The process involves first evaluating the physical loss of assets each household might have\nexperienced due to the disaster. Then, the monetary damage from this loss is evaluated as if asset\nprices had not changed, which results in new market values for all dwellings in each locality. A\nmean of these new market values allows assessing the change in neighborhood effects due to the\ndisaster. Plugging this change in the hedonic price function leads to a second-round impact of the\ndisaster, hence to new market values for dwellings and new neighborhood effects. The\ncomputation is repeated until changes become marginal.\n\nMore specifically, the first step in this process is to adjust the market value of each dwelling in a\nway that reflects the physical destruction it might have experienced due to the disaster. In terms of 𝑖𝑖 is assessed by allocating the estimated local\n\nacross the households covered by the 2011 NLSS III. Four\n\nequation (6), the damage term �𝐾𝐾0ℎ −𝐾𝐾1ℎ�𝑝𝑝0\n\n𝑖𝑖\n\ndestruction rates �𝐾𝐾0𝑖𝑖 −𝐾𝐾1𝑖𝑖�𝐾𝐾⁄ 0\n\n\n\n𝑖𝑖 is assessed by allocating the estimated local\n\nacross the households covered by the 2011 NLSS III. Four\n\nequation (6), the damage term �𝐾𝐾0ℎ −𝐾𝐾1ℎ�𝑝𝑝0\n\n𝑖𝑖\nalternative allocation rules are used to this effect:\n\ndestruction rates", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:001322:14:0:0", "start": 1480, "end": 1493, "surface": "2011 NLSS III", "probe_tag": "keep", "probe_score": 0.978, "luna_label": 1, "luna_reason": "Named survey used to allocate destruction rates across households."}]}, {"key": "paddy2-042", "text": "RUS Russian Federation 2002 Russia Longitudinal Monitoring Survey (RLMS)\nRWA Rwanda 1997 Enquete Integrale sur les Conditions de Vie des Menages\nSEN Senegal 1995 Enquete sur les Depenses des Menages\nSLB Solomon Islands 1999 Population Census\nSLE Sierra Leone 2003 Sierra Leone Integrated Household Survey\nSLV El Salvador 1995 Encuesta de Hogares de Propositos Multiples\nSLV El Salvador 2002 Encuesta de Hogares de Propositos Multiples\nSTP São Tomé and Principe 2000 Enquete sur les Conditions de Vie des Menages\nSVK Slovak Republic 1992 Slovak Microcensus\nSVN Slovenia 1999 Household Budget Survey\nSWE Sweden 1995 Income Distribution Survey (HINK)\nSWE Sweden 2000 Income Distribution Survey (HINK)\nSWZ Swaziland 1995 Household Income and Expenditure Survey\nSWZ Swaziland 2000 Household Income and Expenditure Survey\nTHA Thailand 1990 Socio Economic Survey\nTHA Thailand 1994 Socio Economic Survey\nTHA Thailand 2002 Socio Economic Survey\nTJK Tajikistan 1999 Tajikistan Living Standards Survey\nTON Tonga 1996 National Population Census\nTTO Trinidad and Tobago 1992 Survey of Living Conditions\nTUR Turkey 2002 Household Income and Expenditure Survey\nTWN Taiwan, China 1995 Survey of Family Income and Expenditure\nTWN Taiwan, China 2000 Survey of Family Income and Expenditure\nTZA Tanzania 1991 Household Budget Survey\nTZA Tanzania 2000 Household Budget Survey\nUGA Uganda 2002 National Household Survey\nUKR Ukraine 1999 Household Budget Survey\nUKR Ukraine 2003 Household Budget Survey\nURY Uruguay 1995 Encuesta Continua de Hogares\nURY Uruguay 2003 Encuesta Continua de Hogares\nUSA United States 1994 Current Population Survey (CPS)\nUSA United States 2000 Current Population Survey (CPS)\nVEN Venezuela, RB 1995 Encuesta de Hogares por Muestreo\nVEN Venezuela, RB 2004 Encuesta de Hogares por Muestreo\nVNM Vietnam 1992 Living Standards Survey\nVNM Vietnam 2001 Household Living Standards Survey\nYEM Yemen, Rep. 1998 Demographic and Health Survey\nYUG Serbia and Montenegro 2005", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:003284:29:0:0", "start": 28, "end": 65, "surface": "Russia Longitudinal Monitoring Survey", "probe_tag": "confusion", "probe_score": 0.8746, "luna_label": 1, "luna_reason": "Named existing survey listed as a data resource."}, {"key": "prwp:003284:29:0:4", "start": 951, "end": 990, "surface": "1999 Tajikistan Living Standards Survey", "probe_tag": "confusion", "probe_score": 0.8823, "luna_label": 1, "luna_reason": "Named existing survey identified in the data resource listing."}]}, {"key": "paddy2-043", "text": " trade balance by assumption – balancing regional budget constrains.\nAlternatively, we could pin down wages for some given deficit or surplus.\n\n\n###### **Appendix B. Data sources and construction of controls**\n\nThis appendix provides details on the data used and the data sources. A summary of the key\nvariables and the associated descriptive statistics are given in Table 3 in the main text and in\nTable 8 below.\n\n\n**B.1.** **Data sources.**\n\n\n**Plant-level** **data** **and** **industries.** Our analysis is based on the Annual Survey of Manufacturers (asm) Longitudinal Microdata file. This data cover the years from 1990 to 2010. Our\nfocus is on manufacturing plants only. For every plant we have information on: its primary\n6-digit naics code (the codes are consistent over the 20 year period); its year of establishment;\nits total employment; whether or not it is an exporter in selected years; its sales; the number of\nnon-production and production workers; and its 6-digit postal code. The latter, in combination\nwith the Postal Code Conversion files (pccf), allow us to effectively geo-locate the plants by\nassociating them with the geographical coordinate of their postal code centroids.\n\nThe survey frame of the asm has evolved over time. Early in the period, it was relatively\nstable with, on average, about 32,000 plants per sample year. The sample of plants was restricted to those with total employment (production plus non-production workers) above zero,\nand plants must have sales in excess of $30,000. Also, aggregate records were excluded. These\nrecords represent multiple (typically small) plants without latitudes and longitudes. In 2000,\nhowever, the number of plants in the survey increased substantially as the asm moved from\nits own frame to Statistics", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:006871:37:4:1", "start": 1030, "end": 1058, "surface": "Postal Code Conversion files", "probe_tag": "confusion", "probe_score": 0.7641, "luna_label": 1, "luna_reason": "Conversion files are used to geo-locate plants by postal-code coordinates."}]}, {"key": "paddy2-044", "text": " 0.7 133\nGuinea (2010) 67.3 0.21 0.3 80.7 20\nGuinea-Bissau (2013) 0.1 0 0 0.1 0\nMadagascar (2010) 253 210 83 87 -66\nMali (2013) 3.7 0.2 5 3.7 0\nMauritania (2019) 13 0.02 0.2 6 -54\nNiger (2010) 106.3 0.11 0.1 26.5 -75\nSouth Sudan (2014) 0.1 0 0 0.2 100\n<u>Eswatini (2015)</u> <u>82</u> <u>59</u> <u>72</u> <u>17</u> <u>-79</u>\n_Source: Authors’ calculations, based on USITC data._\n\n\n**3.2 Empirical Specification**\n\n\nThe empirical approach to identify the impact of the AGOA suspension exploits the\n\n\nvariation in country and product eligibility and in the timing of suspension across\n\n\ncountries. More specifically, following Frazer and Van Biesebroeck (2010) and Hakobyan\n\n\n(2020), we adopt a triple difference-in-differences regression model to identify the impact\n\n\nof suspension on exports from the suspended countries.\n\n\n12", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:001107:13:1:0", "start": 367, "end": 377, "surface": "USITC data", "probe_tag": "confusion", "probe_score": 0.3422, "luna_label": 1, "luna_reason": "USITC data underlie authors’ calculations presented in the table."}]}, {"key": "paddy2-045", "text": " billions of constant 2011 US dollars, extended with<br>depreciation and investment series from the WEO<br>|Penn World Table, WEO<br>|\n|Employment|Employees and self-employed in thousands, extended with employment<br>growth rate from the WEO|Penn World Table, WEO|\n\n\n\nThe methodology is subject to several caveats, the most important being the endogeneity of the\nregressors. First, the Hausman test is performed to verify whether the random-effect specification may\nbe appropriate for cross-country regressions. The Pesaran (2004) test is used to control for the presence\nof cross-sectional dependence in panels with many cross-sectional units and few time-series\nobservations. The robustness of the estimates is also verified by employing the Arellano-Bond General\nMethod of Moments (GMM) estimator, although that is also subject to caveats. For example, it may\nunderestimate the impact of several common determinants of the steady-state level of income, such as\nhuman capital, as discussed in Hauk and Wacziarg (2004). The adoption of the GMM estimator\nrequires losing at least two periods of data, which may alter the results when the starting sample is\nsmall. Finally, it may also be subject to the problem of weak instruments: the first-stage relationship\nbetween differenced independent variables and lagged dependent ones may be weak. The problems are\naddressed by using the Blundell and Bond System GMM (see Section 4).\n\n\nTo better control for potential endogeneity, the ideal would be to cross-check the estimates based on\nmacroeconomic time series with those obtained from using sector- and firm-level data (see also the\ndiscussion in Egert and Gal 2016).\n\n\n6 The baseline model does not control for the lagged dependent variable, but the robustness of the results is tested\nunder this specification (see Section 4).\n7 As discussed", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:002123:10:1:2", "start": 1532, "end": 1557, "surface": "macroeconomic time series", "probe_tag": "confusion", "probe_score": 0.3034, "luna_label": 1, "luna_reason": "Existing time series underpin macroeconomic estimates and are compared with sector-level data."}, {"key": "prwp:002123:10:1:3", "start": 1589, "end": 1616, "surface": "sector- and firm-level data", "probe_tag": "confusion", "probe_score": 0.521, "luna_label": 1, "luna_reason": "Existing sector- and firm-level data are used to cross-check macroeconomic estimates."}]}, {"key": "paddy2-046", "text": " periods (October 2019, October 2020, and October 2021) from a major mobile phone service\noperator in Argentina, representing 37 percent of the national market, with over 8 million unique\nsubscribers. The methodology fused CDR data with data from public transport validations (the SUBTE\nsmart card in Buenos Aires) and publicly available household mobility survey data from 2010/2018 _Encuestas de Movilidad Domiciliaria_ (ENMODO). In addition, the analysis incorporates data from a largescale interception survey and a stated-preference survey with private motorized transport users across\nAMBA implemented by the study team, respectively, in November-December 2021 and February- March\n2022.\n\n\n**The mobility indicators are calculated for personal mobility travel, filtering out from the origin-**\n**destination (OD) matrices the trips associated with professional mobility (e.g., taxi drivers)** . The\nmethodology for identifying professional mobility and overall methodology for calculating OD matrices\ngenerally follows other studies that have leveraged CDR data for mobility analysis (see, e.g. Bachir _et al_ .,\n2019; Bayir _et al_ ., 2010). The analysis is based on a total of 2,010 travel zones across the metropolitan\narea, of which 534 are in central Buenos Aires (Autonomous City of Buenos Aires, or CABA) and 1,476 in\nthe Province of Buenos Aires (PBA). The CDR data sourced from the mobile phone operator was processed\ninto OD matrices by following a verification process and developing algorithms that disaggregate the\nmatrices into different modes (i.e., non-motorized, public transport, and private motorized), segment\nthem into trip purposes (i.e., home-based trips to work, home-based trips to other activities, and nonhome based trips), and by gender and age (using anonymized client data available from the mobile\noperator,", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:001219:4:1:3", "start": 520, "end": 595, "surface": "stated-preference survey with private motorized transport users across\nAMBA", "probe_tag": "confusion", "probe_score": 0.7452, "luna_label": 1, "luna_reason": "Completed survey data are incorporated into the mobility analysis."}]}, {"key": "paddy2-047", "text": "dismissed, in favor of the next potential break year. Being agnostic about the break structure\nimplies that any type of break is recorded first and needs to be classified afterwards. This\ncan have the undesirable effect that a strong recovery could mask an initial slump, or a\ndownbreak could occur when a country is already in a crisis.\n\nWe have experimented with other definitions requiring only downbreaks and mildly\nnegative growth, but then we quickly catch more slowdowns in growth which are not\nreally recessions. If we remove the questionable episodes then the sample sizes quickly\nbecome too small, suggesting we are missing important slumps. We are convinced that an\nintelligent filtering of Bai-Perron style breaks could allow a sensible classification of slumps,\nbut it requires adding several criteria and appears to yield fewer slumps than our approach.\nAn interesting extension of this line of work would be to combine both approaches and\nsequentially test whether (a part of) a GDP series exhibits a single downbreak or a sequence\nof breaks fitting our restrictions.\n\n\n**Figure** **S3.1**          - Examples of similar episodes\n\n\n\n**(a)** Inverted\n\n\n**(e)** Inverted\n\n\n\n**(f)** Our breaks\n\n\n\n**(b)** Our breaks\n\n\n\n**(c)** Inverted\n\n\n\n**(d)** Our breaks\n\n\n\n\n\n\n\n\n\n**(g)** Inverted\n\n\n\n**(h)** Our breaks\n\n\n\n\n\n\n\n\n\n\n\n_Notes_ : Illustration of slumps obtained using (i) the inverted definition of Berg et al. (2012) and (ii) our two-break model.\nThe depicted GDP per capita series are from the Penn World Tables version 6.3. Solid vertical lines indicate break points\nand dashed lines indicate the empirical trough.\n\n\nxiv", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:000296:52:0:0", "start": 1505, "end": 1522, "surface": "Penn World Tables", "probe_tag": "confusion", "probe_score": 0.1801, "luna_label": 1, "luna_reason": "Named GDP per capita data source used for the figure’s depicted series."}]}, {"key": "paddy2-048", "text": "sup>\n\n\n**Educational** **efficiency**\n\n\nThus far, this study has demonstrated that while providing solar products increased children’s educational inputs\n\n\n(i.e., hours studied, school-attendance record found on a surprise visit), it did not result in an improvement in their\n\n\neducational achievement (subject test scores and overall GPA). Thus, we are left with the third possibility that learning\n\n\nunder solar lighting is not as substantially productive and solar lighting alone is not sufficient to improve children’s\n\n\nlearning and schooling performance.\n\n\nTo verify this possibility, in column (a) of Table 7, we exploited the study hours and school attendance (estimated\n\n\nin the analysis of Table 5 and Table 6) as regressors to explain the likelihood of children progressing to the next grade\n\n\nafter taking the 2014 examination (see Table S.17 to Table S.19 in the supplemental appendix for the corresponding\n\n\nestimation results on GPA scores). The dependent variable is the same as in Table 2, columns (d)―(f). Surprisingly,\n\n\nthe educational inputs - home-study hours and attendance record - have no significant association with children’s\n\n\nprogression to the next grade. Furthermore, including the treatment dummies in Table 7, column (b) shows virtually\n\n\nno influence on the estimated relationship between the educational inputs and achievement. Given the significant\n\n\n18To check the treatment heterogeneity on educational inputs, in Table S.16 in the supplemental appendix, we also performed similar\nexercises to those in Table S.5 for the total study hours from September 2013 to April 2014 and indicators of children’s attendance at our\nschool visits in February, April, and August in 2014. Overall, no noticeable heterogeneity was found.\n\n\n16", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:006952:17:1:0", "start": 178, "end": 202, "surface": "school-attendance record", "probe_tag": "confusion", "probe_score": 0.1008, "luna_label": 1, "luna_reason": "Attendance record provided evidence of schooling inputs measured during a surprise visit."}, {"key": "prwp:006952:17:1:1", "start": 1086, "end": 1103, "surface": "attendance record", "probe_tag": "confusion", "probe_score": 0.5603, "luna_label": 0, "luna_reason": "Bare topic phrase lacks an eligible source noun despite analytical context."}]}, {"key": "paddy2-049", "text": "2. Policy Makers Need to Focus on the Quality and Not Just the Quantity of Services Delivered\n\n\n_<mark>Deon Filmer and Adam Wagstaff</mark>_\n\n\nEducation and health policymakers often focus on indicators of the _quantity_ of services provided: Are\nchildren enrolled in school? Are women delivering their babies in a health facility? Are newborn babies\nreceiving postnatal care? This assumes that children in school will automatically learn, and that health\noutcomes such as maternal and child mortality will automatically improve as service coverage increases.\n\nThis assumption often is wrong. Even in countries on track to hit enrollment targets, children often have\nlow levels of mastery of reading, writing and mathematics. Indonesia and Mexico, for example, had both\nalmost reached the universal primary completion MDG target by the mid‐2000s, but at the time 68\npercent of Indonesian youth and 50 percent of Mexican youth lacked even minimally adequate\ncompetence in mathematics. <sup>15</sup> [^15: Filmer D, Hasan A, Pritchett L. A Millennium Learning Goal: Measuring Real Progress in Education: Center for\nGlobal Development, 2006.] In health, evidence shows a similar tenuous link between service coverage\nand outcomes. For example, having women deliver their babies in a health facility (an MDG and SDG\ntarget) has been found _not_ to lead to lower maternal or neonatal mortality rates. <sup>16</sup> [^16: Gabrysch S, Nesbitt RC, Schoeps A, Hurt L, Soremekun S, Edmond K, Manu A, Lohela TJ, Danso S, Tomlin K,\nKirkwood B, and Campbell OMR. Does Facility Birth Reduce Maternal and Perinatal Mortality in Brong Ahafo,\nGhana? A Secondary Analysis Using Data on 119,244 Pregnancies from Two Cluster‐Randomised Controlled Trials.\nThe Lancet Global Health 2019; 7(8): e1074‐e87.]\n\nIn both education and health, poor _quality_ of service delivery is the key reason why service coverage does\nnot necessarily translate into better outcomes", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:002317:10:0:0", "start": 1660, "end": 1687, "surface": "Data on 119,244 Pregnancies", "probe_tag": "confusion", "probe_score": 0.5967, "luna_label": 1, "luna_reason": "Pregnancy data from two trials supports analysis of facility birth and mortality outcomes."}]}, {"key": "paddy2-050", "text": " specific variables. The functional form is left unspecified in equation\n(1). The empirical work makes extensive use of dummy variables in order to catch\nnonlinearities in returns to years of schooling, tenure, and other quantitative variables.\nThe last component, ui, is a random disturbance term that captures unobserved\ncharacteristics.\n\n\n_Quantile regressions_\n\n\nLabor market studies usually make use of conditional mean regression estimators,\nsuch as OLS. This technique is subject to criticism because of several, usually, heroic\nassumptions underlying the approach. One is the assumption of homoskedasticity in the\ndistribution of error terms. If the sample is not completely homogenous, this approach,\nby forcing the parameters to be the same across the entire distribution of individuals may\nbe too restrictive and may hide important information.\n\n\n10 The conversion is based on the 2000 PPP. The questionnaire asks for information about income in the\nlast 12 months and self-consumption in the last week (which is multiplied by 52 to obtain the annual selfconsumption).\n\n\n15", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:003778:16:1:0", "start": 892, "end": 900, "surface": "2000 PPP", "probe_tag": "confusion", "probe_score": 0.5839, "luna_label": 1, "luna_reason": "PPP data are used to calculate the income conversion."}]}, {"key": "paddy2-051", "text": "Table 1: Major sources of cross-country corruption data\n\n\n\n\n\n\n\n\n\n\n|Data sources|Examples|\n|---|---|\n|Representative surveys of service users|Representative surveys of service users|\n|Firms|World Bank investment climate assessments<br>(including BEEPS)<br> <br>WEF’s Executive Opinion Survey<br> <br>IMD’s executive opinion survey|\n|Households|International Crime Victim Surveys<br> <br>New Democracy Barometer, Afrobarometer,<br>Asia Barometer, Latinobarometer<br> <br>World Values Surveys<br> <br>Global Corruption Barometer (TI)<br> <br>Gallup International “Voice of the People”|\n|Expert assessments|Expert assessments|\n|experts rating<br>multiple countries|Nations in Transit (Freedom House)<br> <br>International Country Risk Guide (ICRG)<br> <br>Economic Intelligence Unit (EIU)<br> <br>World Markets Research Centre (WMRC)<br> <br>World Bank CPIA|\n|surveys of “well-<br>informed persons”<br>within country|UNECA African Governance Indicators<br> <br>World Governance Assessments|\n|Composite indexes|Composite indexes|\n|aggregation from<br>various sources|TI corruption perceptions index<br> <br>WBI control of corruption index|\n\n\n\n49", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:003181:48:0:1", "start": 101, "end": 140, "surface": "Representative surveys of service users", "probe_tag": "confusion", "probe_score": 0.2682, "luna_label": 0, "luna_reason": "Standalone table row naming a survey category, not an independently used data source."}, {"key": "prwp:003181:48:0:4", "start": 343, "end": 377, "surface": "International Crime Victim Surveys", "probe_tag": "confusion", "probe_score": 0.706, "luna_label": 0, "luna_reason": "Survey name appears as a source example inside a table."}, {"key": "prwp:003181:48:0:10", "start": 498, "end": 525, "surface": "Global Corruption Barometer", "probe_tag": "confusion", "probe_score": 0.7199, "luna_label": 0, "luna_reason": "Listed as a table example without evidence of data use."}, {"key": "prwp:003181:48:0:11", "start": 661, "end": 679, "surface": "Nations in Transit", "probe_tag": "confusion", "probe_score": 0.7849, "luna_label": 0, "luna_reason": "Named source appears as a standalone entry within a data-sources table."}, {"key": "prwp:003181:48:0:17", "start": 1102, "end": 1133, "surface": "WBI control of corruption index", "probe_tag": "confusion", "probe_score": 0.5741, "luna_label": 0, "luna_reason": "Named index appears as a table cell, not an independently used data mention."}]}, {"key": "paddy2-052", "text": "(by about 5-10%), very few studies found that these improvements in skills translated into positive effects\n\non sales and profitability. This combination of small changes in business practices and low statistical power\n\nmeans that few studies find effects of training on sales or profitability, although a few studies find some\n\npositive short-term effects. By comparison, one-on-one consulting provided to larger firms can improve the\n\nperformance of firms. Some of the reasons for limited impact of training programs include, short-time\n\nhorizon of evaluations, and that the monitoring and evaluation surveys have high attrition rate such that the\n\nimpact, especially on control group is not well measured. There may also be spillover effects on untreated\n\ncontrol group of firms. There is also difficulty of measuring firm outcomes, such as revenues and profits,\n\nsince firms in developing countries often do not keep records and are reluctant to share this information,\n\nwhich in turn might subject to changes in reporting following the business training.\n\n\n**_3.4.1 Content of training: What to train on?_**\n\n\nThere is a wide variety of technical skills training programs. Marketing and financial practices training\n\nprograms are most common of these. In South Africa, experimental evidence on 852 (primarily micro)\n\nfirms suggest that both training programs can increase firm profits. Twelve months after the program,\n\ntreated firms with marketing training tended to have larger size (sales and employment) because they\n\nimplemented better market research tactics, advertising, and were inclined to adjust to customer needs. By\n\ncomparison, treated firms with finance training experienced larger changes in firm efficiency. These firms\n\nwere more likely to adopt financial practices aimed at separating business and personal finances, keeping\n\nand analyzing business records, managing budgets more efficiently, and assessing working capital needs,\n\nimplying a larger increase in output-input ratio relative to the other groups (Anderson et al., 2018). These\n\nresults suggest that marketing training effects were larger for firms with less initial exposure to different", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:002377:16:0:0", "start": 577, "end": 610, "surface": "monitoring and evaluation surveys", "probe_tag": "confusion", "probe_score": 0.6985, "luna_label": 1, "luna_reason": "Surveys’ high attrition is cited as limiting measurement of program impacts."}]}, {"key": "paddy2-053", "text": "Table 5 presents this same kind of analysis by Khoemacau, a private company operating a copper mine in\nBotswana. In a corporate presentation in 2023, Khoemacau presented this table showing the relative\nmerits of operating in Botswana and other mining destinations. <sup>50</sup> [^50: Khoemacau Copper Mining, “Khoemacau Copper Mining: Developing a Safe, Modern, Significantly Scalable,\nCopper Silver Mining Business in the Kalahari,” April 2023.] Botswana ranks below Chile but above\nPeru, DRC, Argentina, and Zambia. The table particularly awards Botswana ribbons for rule of law, political\nstability, regulatory quality, corruption prevention, and safe environment.\n\n\nA detailed examination of the 48 projects across these four countries for which we have relatively\ncomplete technical and economic project data provides a more robust analysis of the effects of poor\nquality of infrastructure and services versus poor quality of governance. Poor quality of infrastructure and\nservices, via the items listed in the first part of Table 4, will result in higher operating costs. We have\ncollected operating cost data for mining and processing a ton of ore at a selection of these projects.\n\n\nThe geological orientation of the orebody at each project will have some influence on such costs, as will\nwhether the mine is open pit or underground; however, a main factor influencing these costs is\ninfrastructure and the cost of local inputs. The average mining and processing cost per ton of mill feed at\nfive representative open pit copper projects in Chile is US$11.7. The average cost per ton is US$12.1 at\nthree representative mines in Zambia, US$32.9 at four representative mines in Botswana, and US$84.1 in\nDRC. Figure 18 shows the individual project costs by date of technical study, restricting the sample to only\nopen pit mines, which tend to have lower costs than underground mines.\n\n\n\n_Figure 18: Mining and Processing Cost (US$/t) vs. Date_\n_of Technical Study, Open Pit_\n\n\n\n_Figure 19", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:001393:40:0:0", "start": 779, "end": 814, "surface": "technical and economic project data", "probe_tag": "confusion", "probe_score": 0.157, "luna_label": 1, "luna_reason": "Existing project data supports detailed comparative analysis of infrastructure and governance effects."}]}, {"key": "paddy2-054", "text": ". (1993) improved these unit\n\n\ncost estimates by the development of continuous cost functions for stone protected and clay\n\n\ncovered sea dikes, and sand dunes. They also included an allowance for extreme sea levels\n\n\nwhich influences initial dike heights, and roughly doubled global costs compared to Dronkers\n\n\net al. (1990) (see Table 1).\n\n\nTo set the stage, we analyzed possible determinants of unit costs of sea dikes with a\n\n\ncountry-level cross-sectional data set from the DIVA database. The total sample contains\n\n\n248 observations. We removed 47 observations without low-lying land below 10 meters\n\n\nA.D., as these do not have sea dikes. Furthermore, eight outliers with very high asset\n\n\ndensities (e.g. Monaco, Gibraltar, Bahrain) were excluded from the econometric analysis.\n\n\nA least squares regression analysis was performed to investigate how experts appear to\n\n\nhave evaluated the importance of local differences in determinants of unit costs, as revealed", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:prwp:007643:48:1:0", "start": 431, "end": 469, "surface": "country-level cross-sectional data set", "probe_tag": "confusion", "probe_score": 0.7343, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:007643:48:1:1", "start": 479, "end": 492, "surface": "DIVA database", "probe_tag": "keep", "probe_score": 0.9639, "luna_label": 1, "luna_reason": "Database data analyzed in sample construction and least-squares regression."}]}, {"key": "paddy2-055", "text": "**Annex 1. Respondents to the WB-ASBA Survey**\n\n\n\n\n\n\n\n\n\n\n|Country|Head of<br>Supervision|Head of Research<br>Central Bank|\n|---|---|---|\n|Argentina<br>Bolivia<br>Brazil<br>Colombia<br>Costa Rica<br>Chile<br>Ecuador<br>El Salvador<br>Guatemala<br>Honduras<br>Mexico<br>Nicaragua<br>Panama<br>Paraguay<br>Peru<br>Dominican Republic<br>Uruguay<br>Venezuela<br>Aruba<br>Bahamas<br>Barbados<br>Belize<br>Cayman Islands<br>Haiti<br>Netherland Antilles<br>Suriname<br>Trinidad and Tobago<br>British Virgin Islands<br>Guyana<br>Jamaica<br>Eastern Caribbean Islands|X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X|X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X|\n\n\n\n32", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:005116:33:0:0", "start": 30, "end": 44, "surface": "WB-ASBA Survey", "probe_tag": "confusion", "probe_score": 0.0891, "luna_label": 0, "luna_reason": "Survey name appears in an annex table heading listing respondents."}]}, {"key": "paddy2-056", "text": "\nIn the absence of physical quantities or firm-level prices, we deflate all variables with industry\n\nspecific price indices; value added or sales revenue by subindustry-level deflators from the\n\n\nProducer Price Index, material costs by deflators based on input-output tables and capital by\n\n\ndeflators constructed from the Gross Fixed Capital Formation. As noted by DLW (2012), the use\n\n\nof deflation only affects the level of the markup estimates, and not the correlation between markups\n\n\nand firm-level characteristics.\n\n\n35 The alternative would have been to use a Cobb-Douglass specification. However, doing so would result in all firms\nin a sector having the same output elasticities. This will make the elasticity independent of input use intensity, which\ncould lead to variations in technology being attributed to variation in markups. This will potentially bias the results\nwhen analyzing markup differences across firms.\n\n\n33", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:001991:34:1:0", "start": 196, "end": 216, "surface": "Producer Price Index", "probe_tag": "confusion", "probe_score": 0.7542, "luna_label": 1, "luna_reason": "Producer Price Index is used as a deflator in markup estimation."}]}, {"key": "paddy2-057", "text": "20 STEVEN PENNINGS\n\n\nAppendix A. Summary of Data Sources\n\n\n   - US import prices and US producer prices (dependent variables in regressions): confidential BLS microdata\n(see www.bls.gov/bls/blsresda.htm).\n\n   - Import and export values (for import shares): Feenstra Trade Database\n(http://cid.econ.ucdavis.edu/).\n\n   - Nominal bilateral exchange rates, country CPI, US CPI: Gopinath and Rigobon (2008)\n(http://www.aeaweb.org/articles.php?doi=10.1257/aer.100.1.304). Chinese CPI: IMF IFS.\n\n   - US Real Trade Weighted Exchange Rate (TWI), US GDP: Federal Reserve of St Louis Economic Database\n(FRED).\n\n   - Manf. output data and materials prices (series: PIMAT) from NBER-CES Manf. Ind. Database\n(http://www.nber.org/nberces/).\n\n   - NAICS6 measure of producer prices: bls.gov.\n\n   - Construction of Figure 1 (Aggregate Data). Manufacturing import prices index from Canada and Europe\nand all imports from Japan downloaded from bls.gov/mxp/. Annual average indices deflated by annual US\nCPI from FRED. Bilateral ER data and foreign CPI from FRED, annual averages. Competitors’ RERs data:\nBroad Real US TWI from FRED. Country trade weights for removing the bilateral rate and rescaling the\nTWI: Federal Reserve H.10 release.\n\n\nAppendix B. Data Construction\n\n\nB.1. **Import** **price** **data.** The import price variable is constructed as the change in the log of the price of\neach individual good over its life in the sample (mean of around 2 years) in USD, from", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:006928:21:0:6", "start": 733, "end": 766, "surface": "NAICS6 measure of producer prices", "probe_tag": "confusion", "probe_score": 0.6562, "luna_label": 1, "luna_reason": "Named producer-price measure sourced from BLS as an appendix data source."}, {"key": "prwp:006928:21:0:7", "start": 1086, "end": 1113, "surface": "Broad Real US TWI from FRED", "probe_tag": "confusion", "probe_score": 0.3337, "luna_label": 1, "luna_reason": "FRED series used as competitors’ real exchange-rate data in Figure 1 construction."}]}, {"key": "paddy2-058", "text": "- 3 \n\nproductivity in connection to climate and soil conditions (e.g., Global Agro-ecological Zones\n\n(GAEZ) system developed by the FAO and the International Institute for Applied Systems\n\nAnalysis (IIASA)). These data provide information on crop suitability at the detailed spatial\n\nlevel. On the infrastructure side, the new economic geography literature is building a solid\n\nbody of knowledge on regional distribution and disparity of infrastructure endowments,\n\nidentifying missing links and bottlenecks (see, for instance, World Bank (2009) and (2010)).\n\n\nThere are however only a few empirical studies that statistically link these two different\n\nsources of spatial data on the agriculture and infrastructure sides, excepting a number of\n\nmore recent works, such as Dorosh, Wang, You and Schmidt (2012). This paper examines\n\nthe agricultural potential of East Africa, namely, Burundi, Kenya, Rwanda, Tanzania and\n\nUganda, through an examination of the two different sources of spatial data. Despite the\n\ncurrently high international commodity prices, in particular in the traditional export crops,\n\nsuch as coffee and cotton, these East African countries are still struggling to improve\n\nagricultural productivity. This paper specifically aims at: (i) generating spatial agricultural\n\nproduction and potential data for the region; (ii) developing spatial data to show transport\n\naccessibility in each locality; and (iii) developing an empirical model to link these data and\n\nanalyze the relationship between agriculture production and transport infrastructure\n\ninvestment.\n\n\nThe remaining sections are organized as follows: Section II describes our spatial agriculture\n\ndata. Section III develops an empirical model and describes our infrastructure data. Section\n\nIV discusses our main estimation results and some policy implications. Section V concludes.\n\n\n**II.** **SPATIAL PRODUCTION ALLOCATION MODEL (SPAM)** **UPDATE**\n\n\nThe current paper relies on a spatial production allocation model (SPAM) developed by the\n\nInternational Food Policy Research Institute (IFPRI) for generating highly disaggregated\n\ncrop-specific production data", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:006341:4:0:2", "start": 1740, "end": 1759, "surface": "infrastructure data", "probe_tag": "confusion", "probe_score": 0.2615, "luna_label": 1, "luna_reason": "Existing infrastructure data are declared as the basis for the empirical model."}]}, {"key": "paddy2-059", "text": "where all variables are expressed in current **US** dollars. **NFQA** denotes the net holdings of\n\nequity-related assets and **NFLA** the net holdings of other assets, each given **by** the corresponding\n\nterm in square brackets in the second line of **(3.1).** Using the letters **A** and L to denote\n\nrespectively assets and liabilities, **NFQA** can be seen to equal the sum **of** the net holdings **of**\n\ndirect foreign investment assets **FDIA** **-** FDIL plus the net holdings of portfolio equity assets,\n\n**EQYA** **-** **EQYL.** In turn, the second term in square brackets captures the net position in non\nequity-related assets, that for brevity we shall call \"loan assets\". The position consists **of**\n\ninternational reserves RA, plus the net loan position **LA** **-** LL.\n\nAbsent valuation changes, unrequited capital transfers debt forgiveness and other debt\n\nreduction operations, and ignoring misinvoicing of current account transactions, the rate of\n\nchange of **NFA** would just equal the current account surplus **CA,** expressed in **US** dollars:\n\n**_ANFA(j,_** _t)_ **_=_** **_CA(j,_** _t)_ **(3.2)**\n\nGiven some initial condition for **NFA,** recursive use of **(3.2)** would then permit\n\nconstruction of the country's net foreign asset position. Likewise, accumulation of disaggregated\n\nfinancial-account flows from the BoP would permit construction of each of the stocks in **", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:000405:14:0:0", "start": 1297, "end": 1348, "surface": "disaggregated\n\nfinancial-account flows from the BoP", "probe_tag": "confusion", "probe_score": 0.113, "luna_label": 1, "luna_reason": "BoP financial-account flows are used to construct corresponding asset stocks."}]}, {"key": "paddy2-060", "text": " 12,692 fulfilled the eligibility criteria.\n\n\nAs explained above, and key to the integrity of the experimental design, baseline data\n\n\nwas collected prior to assigning localities to the three treatment and control groups. The\n\n\nbaseline questionnaire included simple variables on employment, assets, education, and\n\n\nhousehold characteristics.\n\n\nThe second public lottery took place in March 2016. The list of the 5,116 selected\n\n\nbeneficiaries was publicly released in each locality between July and September 2016. <sup>25</sup>\n\n\n24The baseline instrument was designed by the research team. NGO staff were trained as enumerators.\nAn independent team of experienced enumerators was hired to perform field supervision and data quality\nchecks. A double-blind data-entry process was set-up.\n\n25The lag between the second lottery and the release of the beneficiary lists was due to delays in the\n\n\n13", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:prwp:000613:16:1:0", "start": 119, "end": 132, "surface": "baseline data", "probe_tag": "drop", "probe_score": 0.0022, "luna_label": 0, "luna_reason": null}, {"key": "sample:prwp:000613:16:1:1", "start": 851, "end": 868, "surface": "beneficiary lists", "probe_tag": "drop", "probe_score": 0.0042, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-061", "text": "20**<br>|<br>**Full IE-LFS 2019/20**<br>|<br>**Full IE-LFS 2019/20**<br>|<br>**Quarter 3 IE-LFS 2019/20**<br>|<br>**Quarter 3 IE-LFS 2019/20**<br>|<br>**Quarter 3 IE-LFS 2019/20**<br>|<br>**Quarter 3 IE-LFS 2019/20**<br>|<br>**Quarter 3 IE-LFS 2019/20**<br>|**AWMS R3**<br>|**AWMS R3**<br>|**AWMS R3**<br>|**AWMS R3**<br>|**AWMS R3**<br>|\n|<br>Fieldwork<br>|<br>Fieldwork<br>|<br>Fieldwork<br>|<br>October19-September 2020<br> <br>|<br>October19-September 2020<br> <br>|<br>October19-September 2020<br> <br>|<br>June-August 2022<br> <br>|<br>June-August 2022<br> <br>|<br>June-August 2022<br> <br>|<br>June-August 2022<br> <br>|<br>June-August 2022<br> <br>|<br>April-June 2023<br> <br>|<br>April-June 2023<br> <br>|<br>April-June 2023<", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:001116:12:1:1", "start": 260, "end": 267, "surface": "AWMS R3", "probe_tag": "drop", "probe_score": 0.0064, "luna_label": 0, "luna_reason": "Standalone table cell containing a survey or round code, not a data-use claim."}]}, {"key": "paddy2-062", "text": "**Tanzania**\n\n\n<u>Notes: Documented ownership was excluded from the analysis for Tanzania. Categories are attached to the variables: joint owner</u>\n(J), exclusive owner (E), and not hold (N). The figures only describe the first two dimensions from the MCA.\n\n\n37", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:001905:38:0:0", "start": 253, "end": 256, "surface": "MCA", "probe_tag": "drop", "probe_score": 0.0173, "luna_label": 0, "luna_reason": "Analysis acronym names a method, not an eligible data resource."}]}, {"key": "paddy2-063", "text": "Table 6 shows the results from two estimations: one using annual data and the other using twoyear averages. <sup>7</sup> [^7: The simple two year average is performed for each of the variables; the first two-year average covers the period 1999-2000\nand the last two-year average the period 2007-08. CA is performed on these average values.] As noted earlier, the objective of using the two-year averages is to smooth out business\ncycle effects. Clearly, an even longer period would have been desirable from the perspective of purging\nbusiness cycle effects, but limitations in terms of the number of available data points prevented us from\ndoing so. The estimated coefficient in the multinomial regressions reflects the likelihood of being in one\ncluster relative to a reference cluster. As noted earlier, the reference group used is the lower growth\nand higher vulnerability (V) cluster, which is the worst of all possible outcomes.\n\n\n**Table 6. Multinomial Logit Estimations based on Growth and Vulnerability Clusters** 1/\n\n|Col1|Col2|Col3|VULNERABILITY|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n||||**Annual Data**|**Annual Data**|**Two-Year Averages**|**Two-Year Averages**|\n||||**Lower**|**Higher**|**Lower**|**Higher**|\n|Trade openness; exports plus imports (% of GDP)<br>Export and import growth rates, difference in %<br>Financial openness; FX assets & liabilities (% of GDP)<br>FDI, net, % of GDP<br>Counter-cyclical fiscal policies 2/<br>Monetary tightening; Δ in velocity<br>Exchange rate flexibility<br>Capital controls<br>Initial level of income, share", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:004776:11:0:0", "start": 58, "end": 69, "surface": "annual data", "probe_tag": "confusion", "probe_score": 0.7644, "luna_label": 1, "luna_reason": "Annual data are used directly in estimations reported in Table 6."}, {"key": "prwp:004776:11:0:2", "start": 1108, "end": 1119, "surface": "Annual Data", "probe_tag": "drop", "probe_score": 0.0349, "luna_label": 0, "luna_reason": "Standalone table header identifying an estimation-data column"}]}, {"key": "paddy2-064", "text": "Nielsen, R. A. (2017). _Deadly clerics:_ _Blocked ambition and the paths to jihad_ . Cambridge University\n\nPress.\n\n\nNielsen, S. Y. (2016). Perceptions between syrian refugees and their host community. _Turkish_\n\n_Policy_ _Quarterly_ _15_ (3), 99–106.\n\n\nNRC (2021, Mar). Syria: Another decade of crisis on the horizon expected to displace millions\n\nmore.\n\n\nOCHA (2021). Syrian arab republic: Idp movements and idp spontaneous return movements data.\n\n\nParry, J. and O. Aymerich (2021). “idps with perceived isil affiliation: Can local peace agreements\n\nfacilitate their return?”, _Unpublished_ _Working_ _paper_ . Commissioned as part of the “Preventing Social Conflict and Promoting Social Cohesion in Forced Displacement Contexts” Series.\nWashington, DC: World Bank Group.\n\n\nPhillips, C. (2016). _The_ _battle_ _for_ _Syria:_ _International_ _rivalry_ _in_ _the_ _new_ _Middle_ _East_ . Yale\nUniversity Press.\n\n\nPrucha, N. (2016). Is and the jihadist information highway–projecting influence and religious\nidentity via telegram. _Perspectives_ _on_ _Terrorism_ _10_ (6), 48–58.\n\n\nRaleigh, C., A. Linke, H. Hegre, and J. Karlsen (2010). Introducing acled: An armed conflict\n\nlocation and event dataset: Special data feature. _Journal_ _of_ _Peace_ _Research_ _47_ (5), 651–660.\n\n\nRamadan, R. (2017). Questioning the role of facebook in maintaining syrian social capital during\n\nthe syrian crisis. _Heliyon_ _3_", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:000955:29:0:0", "start": 409, "end": 446, "surface": "idp spontaneous return movements data", "probe_tag": "drop", "probe_score": 0.0429, "luna_label": 0, "luna_reason": "Bibliography title fragment, not evidence of data being used."}]}, {"key": "paddy2-065", "text": "**REFERENCES**\n\n\nAcosta, P. (2011). ―Female Migration and Child Occupation in Rural El Salvador.‖\n\nForthcoming in _Population Research and Policy Review._\n\nAcosta, P. (2006). ―Labor Supply, School Attendance, and Remittances from\n\nInternational Migration: The Case of El Salvador.‖ World Bank Policy Research\nWorking Paper 3903.\n\nAcosta, P., P. Fajnzylber and J. Humberto Lopez (2008). ―Remittances and Household\n\nBehavior: Evidence for Latin America,‖ in P. Fajnzylber and J. Humberto Lopez\n(eds) _Remittances and Development: Lessons from Latin America._ Washington, DC:\nWorld Bank.\n\nAdams, R. (2010) ―Evaluating the Economic Impact of International Remittances on\n\nDeveloping Countries Using Household Surveys: A Literature Review.‖\nForthcoming in _Journal of Development Studies_ .\n\nAdams, Jr., R. (1998). ―Remittances, Investment and Rural Asset Accumulation in\n\nPakistan,‖ _Economic Development and Cultural Change_ 47:1 (October): 155-173.\n\nAdams, R. and A. Cuecuecha (2010). ―The Economic Impact of International Migration\n\nand Remittances on Poverty and Household Consumption and Investment in\nIndonesia.‖ World Bank, Washington DC.\n\nBeaudouin, P. (2005). ―Economic Impact of Migration on a Rural Area in Bangladesh.‖\n\nMimeo, Centre d’Economie de la Sorbonne, Universite Paris 1.\n\nBuchori, C. and M. Amalia (2006). ―Fact Sheet: Migration, Remittance and Female\n\nMigrant Workers.‖ World Bank, Washington DC.\n\nCabegin, E. (2006). ―The Effect of Filipino Overseas Migration on the Non-Migrant\n\nSpouse’s Market Participation and Labor Supply Behavior.‖ Institute for Study of\nLabor (IZA) Discussion Paper 22", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:004775:25:0:0", "start": 695, "end": 712, "surface": "Household Surveys", "probe_tag": "drop", "probe_score": 0.0327, "luna_label": 0, "luna_reason": "Fragment from a bibliography title, not an independent data-use mention."}]}, {"key": "paddy2-066", "text": " <sup>22</sup> The average income abroad of applicants is around\n\n\n$120,000; the median is considerably lower at about $84,000. Average incomes in Malaysia, for\n\n\nthose who returned, are actually higher with the average and median around $137,000 and\n\n\n20 The electronic administrative records are missing information for 18 percent of our sample. Note that the electronic\nrecords are not used to determine whether an application is accepted, rather TalentCorp prepares a paper file on each\napplicant. The characteristics of those missing, including their return status, are near identical to the overall sample,\nsuggesting they are missing at random.\n21 For 21 percent of the sample income abroad is missing. In addition, to deal with measurement error we exclude\noutlying income observations. Most importantly, the income abroad question on the REP application is ambiguous in\nwhether annual or monthly income should be reported. The large majority of respondents seem to have reported annual\nincome, but we exclude reported incomes of less than $24,000 (14 percent of observations) since these could plausibly\nbe monthly wages. Our results are robust to varying this cutoff income. We also exclude the top 1 percent of income\nobservations. The characteristics of individuals with income information missing or below the cutoffs are near\nidentical to those of the remainder of the sample, including their return probability.\n22 PPP conversion rates are from the World Bank Development Indicators. 2011 numbers are inflated by the change\nin the US Consumer Price Index.\n\n\n10", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:prwp:006882:11:1:0", "start": 260, "end": 293, "surface": "electronic administrative records", "probe_tag": "drop", "probe_score": 0.0451, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:006882:11:1:1", "start": 1464, "end": 1497, "surface": "World Bank Development Indicators", "probe_tag": "confusion", "probe_score": 0.7644, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:006882:11:1:2", "start": 1546, "end": 1569, "surface": "US Consumer Price Index", "probe_tag": "confusion", "probe_score": 0.2936, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-067", "text": "members’ behavior. It may also offer opportunities to improve enforcement of pastoralists’ use rights and\n\n\nright holders’ ability to enter contingent contracts building on such rights, something that can increase\n\n\nflexibility of and most likely also effectiveness of PES, e.g., by including upfront payments (Jack _et al._\n\n\n2022) or tailoring interactions to the specific circumstances of target groups.\n\n\nThe combination of increased benefits and reduced cost of documented land rights creates opportunities for\n\n\nAfrican countries to reap benefits that can translate into greater transparency, effectiveness, coverage, and\n\n\nfiscal impact of their land institutions through appropriate regulatory change. Such change would include\n\n\n(i) adjusting their regulatory and institutional frameworks to deliver services at scale by allowing use of\n\n\ndigital technology (e-signatures, mass valuation, digital lodging of surveys, etc.), interoperability, and\n\n\npublic monitoring; (ii) replacing high and distortionary transaction taxes by a recurrent land tax based on\n\n\nmass valuation techniques and public access to assessed property values; (iii) using access to registry\n\n\ninformation to catalyze operation of financial and other factor markets; (iv) clarifying modalities for\n\n\nregistering group and secondary rights, including ways to decide on management and conflict resolution\n\n\nconsensually and transparently; (v) establishing standards for transfer of use rights to public land to which\n\n\nno formal rights exist or for public land acquisition, in a transparent and competitive way; and (vi) allowing\n\n\nland users to capitalize on new opportunities to provide local and global public goods through climate\n\n\nchange mitigation and adaptation by providing national land use monitoring to allow documentation and\n\n\nquantification of such contributions.\n\n\n**3. Land rights to help address challenges of structural transformation**\n\n\nInstitutions that clearly define rights to agricultural land and allow such land to be transferred easily can\n\n\nhelp reduce transaction cost in land markets and support functioning of other factor markets linked to land\n\n\nmarkets (e.g., those for insurance and credit). Africa is also richly endowed with land that, while\n\n\ntraditionally often", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:001009:20:0:0", "start": 1162, "end": 1184, "surface": "registry\n\n\ninformation", "probe_tag": "drop", "probe_score": 0.0356, "luna_label": 0, "luna_reason": "Proposed future use of registry information, not an existing data use."}]}, {"key": "paddy2-068", "text": "##### **References**\n\nAdda, J. (2016): “Economic activity and the spread of viral diseases: Evidence from high\n\n\nfrequency data,” _The_ _Quarterly_ _Journal_ _of_ _Economics_, 131, 891–941.\n\n\nAhrens, A., C. B. Hansen, and M. Schaffer (2019): “LASSOPACK: Stata module for\n\n\nlasso, square-root lasso, elastic net, ridge, adaptive lasso estimation and cross-validation,” .\n\n\nAllinder, R. M., L. S. Fuchs, D. Fuchs, and C. L. Hamlett (1992): “Effects of summer\n\n\nbreak on math and spelling performance as a function of grade level,” _The_ _Elementary_ _School_\n\n\n_Journal_, 92, 451–460.\n\n\nAlves, M. T. G., J. F. Soares, and F. P. Xavier (2016): “Desigualdades educacionais\n\n\nno ensino fundamental de 2005 a 2013: hiato entre grupos sociais,” _Revista_ _Brasileira_ _de_\n\n\n_Sociologia_, 4, 49–82.\n\n\nAndrabi, T., B. Daniels, and J. Das (2020): “Human Capital Accumulation and Disasters:\n\n\nEvidence from the Pakistan Earthquake of 2005,” _OSF._ _http://doi._ _org/10.17605/OSF._\n\n\n_IO/3QG98_ .\n\n\nAthey, S. and G. Imbens (2006): “Identification and Inference in Nonlinear Difference-in\n\nDifferences Models,” _Econometrica_, 74, 431–497.\n\n\nAzevedo, J. P., A. Hasan, D. Gold", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:001359:31:0:0", "start": 106, "end": 127, "surface": "high\n\n\nfrequency data", "probe_tag": "drop", "probe_score": 0.0261, "luna_label": 0, "luna_reason": "Span is part of a bibliography entry, not an independently used data source."}]}, {"key": "paddy2-069", "text": " (cap on reimbursement and/or services provided at the hospital level)<br>|<br>Global budget (cap on reimbursement and/or services provided at the hospital level)<br>|<br>Global budget (cap on reimbursement and/or services provided at the hospital level)<br>|\n|Uzbekistan||<br>Missing data|<br>Missing data|||||||||||||\n|Uzbekistan||||||||||||||||\n\n\n\nreports.", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:004181:48:5:0", "start": 277, "end": 289, "surface": "Missing data", "probe_tag": "drop", "probe_score": 0.0115, "luna_label": 0, "luna_reason": "Standalone table cell indicating missing data, not a substantive data-use mention."}]}, {"key": "paddy2-070", "text": "#### **The Internet and Chinese Exports in the Pre-Alibaba Era***\n\n**Ana M. Fernandes** <sup>**a**</sup> **Aaditya Mattoo** <sup>**b**</sup> **Huy Nguyen** <sup>**c**</sup> **Marc Schiffbauer** <sup>**d**</sup>\n\n\n**JEL Classification codes** : F14, O33.\n**Keywords:** internet, information and communication technology, export growth, firm-level data,\nChina.\n\n\na Ana Margarida Fernandes. The World Bank. Email: afernandes@worldbank.org.\nb Aaditya Mattoo. The World Bank. Email: amattoo@worldbank.org.\nc Huy Nguyen. International Monetary Fund Email: hnguyen4@imf.org.\nd Marc Schiffbauer. The World Bank. Email: mschiffbauer@worldbank.org.\n\n\n- This paper was prepared as a background paper for the World Development Report 2016 _Digital Dividends_ . The authors would\nlike to thank Michael Minges, Rajendra Singh, Tim Kelly, Indhira Santos, Uwe Deichmann, Shawn Tan, Deepak Mishra, and\nMaggie Chen for helpful discussions, to Michael Ward for sharing data, and to Changjiang Li at CNNIC for help with access to\ndata on ICT in China. Research for this paper has in part been supported by the World Bank’s Multidonor Trust Fund for Trade\nand Development and the Strategic Research Program on Economic Development. The findings expressed in this paper are those\nof the authors and do not necessarily represent the views of the World Bank or its member countries.", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:007220:2:0:0", "start": 335, "end": 350, "surface": "firm-level data", "probe_tag": "drop", "probe_score": 0.0206, "luna_label": 0, "luna_reason": "Keyword-only generic data label; no attributed finding or actual use."}]}, {"key": "paddy2-071", "text": "###### **Rainfall data**\n\nThe rainfall data used in this paper were compiled by the Directorate of Economics\n\n\nand Statistics, Government of Andhra Pradesh. Rainfall data are available at the sub\n\ndistrict (i.e. block) level for the years 2002/03 to 2011/12. Rainfall deviation and rainfall\n\n\ndeviation (lag) describe the relative deviation of cumulative rainfall over the agricultural\n\n\nyear (June - May) from the long-term average, e.g. _devrain_ <sup>05</sup> <sup>_/_</sup> <sup>06</sup> = ( _rf_ <sup>05</sup> <sup>_/_</sup> <sup>06</sup> _−_ _rf_ ) _/rf_ .\n\n\nFor the 2007 round of interviews, current rainfall uses the 2005/06 rainfall, and lagged\n\n\nrainfall uses rainfall in the agricultural year 2004/05. For the 2009/10 round of interviews,\n\n\ncurrent rainfall uses the rainfall in the agricultural year 2008/09, and lagged rainfall uses\n\n\ndata from the agricultural year 2007/08.\n\n###### **NREGS data**\n\n\nThe implementation of the NREGS was intended prioritize India’s 200 poorest districts,\n\n\nsubsequently extending to the remaining districts. India has a total of 655 districts, of\n\n\nwhich 625 had introduced the NREGS as of 2008. The 30 remaining district were urban\n\n\ndistricts. In 2003 the Planning Commission of India elaborated clear rules stating which\n\n\ndistricts should be included in which round of implementation of the NREGS. However,\n\n\nthe process of district selection was influenced by political considerations due to the huge\n\n\nsize and financial relevance of this program and the rules elaborated by the Planning\n\n\nCommission were not strictly followed.\n\n\n_•_ NREGS introduced in District: This variable", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:007007:53:0:0", "start": 9, "end": 22, "surface": "Rainfall data", "probe_tag": "drop", "probe_score": 0.0421, "luna_label": 1, "luna_reason": "Existing Andhra Pradesh rainfall data are used to calculate rainfall deviations."}]}, {"key": "paddy2-072", "text": ", and Zenou, 2010;\nÅslund and Rooth, 2007), and Switzerland\n(Müller, Pannatier, and Viarengo, 2022),\nas well as the previously described crosscountry study. This could in principle stem\nfrom scarring on an individual level from\nweak initial opportunities, or persistently\nweak local labour market combined with\nimperfect geographic mobility. The effects\nare hard to disentangle, while Åslund and\nRooth (2007) find some indication that both\nphenomena are at play, Godøy (2017) finds\nevidence only for persistently weak local\nlabour markets.\n\n\n##### Migrants and refugees dispersed away from ethnic enclaves experience weaker labour market inclusion outcomes, and vice versa.\n\nCo-nationals can provide important\ninformation to refugees about employment\nopportunities. In Germany, Battisti, Peri,\nand Romiti (2022) found that immigrants\ninitially located in places with more conationals, as well as well as refugees and\nrepatriated ethnic Germans dispersed to\nsuch places, are more likely to be employed\nin the first 3 years. It was found, however,\nthat these groups had lower probability of\ninvesting in human capital. In Swiss data,\nMartén, Hainmueller, and Hangartner\n(2019) found that refugees dispersed to\nlocations with more co-nationals are more\nlikely to find work, especially in the first 3\nyears. In Danish data, Damm (2014) found that\nhigher skill levels of non-Western immigrant\nmen in an area raises employment probability\nof refugee men, while higher employment\nrates of their co-national men raises their\nearnings. Also in Danish data, Damm (2009)\nfound that larger size of ethnic network in an\narea increases earnings of refugees.\nIn Swedish data, Edin, Fredriksson,\nand Aslund (2003) found that refugees\ndispersed to areas with more co-nationals\nexperience higher earnings.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\nKingdom,", "source": "jad_paddy_docs", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jad_paddy_docs:000007:12:2:0", "start": 1120, "end": 1130, "surface": "Swiss data", "probe_tag": "keep", "probe_score": 0.9927, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:12:2:1", "start": 1307, "end": 1318, "surface": "Danish data", "probe_tag": "keep", "probe_score": 0.9708, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-073", "text": " themselves.\nUkrainian refugees make up the largest\nshares of the population in the city of\nWroclaw (7.4%), Przemysl, a city on the\nUkrainian border (6.5%), and in Pruszkowski\npoviat, a suburban area of Warsaw (6.3%).\nThe city of Warsaw comes seventh with\nUkrainian refugees comprising 5.6% of the\nlocal population.\n\n\n\n**Ukrainian refugees in Poland continue**\n**to get their incomes primarily from**\n**work.** In the SEIS survey conducted in\nMay and June 2024, 80% of the refugee\nhouseholds’ incomes came from work,\nwhich included full-time and part-time\nwork, self-employment, remote work, and\nother forms of employment in Poland, as\nwell as remote employment in Ukraine.\nThis is the same as in the previous\nMSNA survey, conducted in July and\nAugust 2023 (see Deloitte, 2024), despite\n\n\n\nthe fact that the child benefit received\nby 42% of Ukrainian refugee households\nincreased in that time from PLN 500 to\nPLN 800 a month. For a vast majority of\nUkrainian household the „Family 800+”\nchild benefit was the only social benefit that\nthey received from the Polish government.\nOnly 5% of Ukrainian refugee households\nclaimed an accommodation allowance,\n4% – a disability grant and an even smaller\npercentage – other benefits.", "source": "jad_paddy_docs", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jad_paddy_docs:000001:5:2:0", "start": 418, "end": 429, "surface": "SEIS survey", "probe_tag": "keep", "probe_score": 0.9975, "luna_label": 1, "luna_reason": "Completed SEIS survey supports the reported 80 percent income finding."}, {"key": "sample:jad_paddy_docs:000001:5:2:1", "start": 710, "end": 721, "surface": "MSNA survey", "probe_tag": "keep", "probe_score": 0.9784, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-074", "text": " overall.\nThese connections are important to bear in mind when designing government, development, and humanitarian\nsupport programs.\n\n\nEmployment continues to be closely associated with lower poverty rates, though ultimately, it’s the size of\nincome that is generated by working household members that makes the biggest difference. Considering that\nthe share of working-age refugees that are employed is nearing host population levels after rising further in\n2024, attention should now turn to wages. Data on the latter, which was derived from household level\nindicators, demonstrates that refugees on average make two-thirds of what the local population does per hour\nof work. Low wage premiums for higher education levels and the fact that some 60% of current refugee\nemployees have a background in an entirely different sector of the economy, suggest the presence of\nunderemployment and skills mismatching. This assertion is corroborated by nearly 35% of employed refugees\nin the region reporting few available jobs with adequate pay, lack of positions that match their skills, or issues\nwith getting their qualifications recognized. Moreover, almost the same percentage indicate lack of local\nlanguage knowledge to be a problem, a well-acknowledged barrier to skilled employment.\n\n\n**Based on the above findings it is recommended that:**\n\n\n- Governments, development and humanitarian actors take into account poverty levels when designing their\nsupport programs for Ukrainian refugees. The quality of day to day life, safety, and level of access to key\nservices are directly tied to household income.\n\n- Poverty measures account for differences in housing costs between refugees and host populations.\n\n- A special focus is placed on supporting refugee employment at their skill level, including transition from\ncurrent low-level jobs. The difference between refugee and local population wages could be an important\nmetric to monitor on an ongoing basis\n\n\n1. Compared to the <u>[2023 MSNA data](https://data.unhcr.org/en/documents/details/108068)</u>\n2.", "source": "jad_paddy_docs", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jad_paddy_docs:000010:2:1:0", "start": 544, "end": 570, "surface": "household level\nindicators", "probe_tag": "confusion", "probe_score": 0.1331, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000010:2:1:1", "start": 1982, "end": 1996, "surface": "2023 MSNA data", "probe_tag": "confusion", "probe_score": 0.6904, "luna_label": 1, "luna_reason": "Named 2023 MSNA dataset used as a comparison source."}]}, {"key": "paddy2-075", "text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n## **2.** Ukrainian refugees in the Polish labour market\n\n##### In the past year, as far as labour market integration is concerned, refugees from Ukraine improved in terms of employment and wages, yet they continue to be disproportionately skewed towards elementary occupations. They are also the group to see the fastest improvements, with the gap towards Polish citizens visibly closing across the entire wage distribution (2.1). The current refugee employment rates are only slightly lower than those for Polish citizens, and median net wages are at about four-fifths of the economy as a whole, which may nevertheless be overly optimistic when compared to gross or average wages (2.2).\n\n#### **2.1 Improving economic situation**\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 9. Ukrainian refugee labour status** <sup>**9**</sup> [^9: These employment rates are very close to the ones from the Polish central bank surveys of Ukrainian refugees, which showed 62% in July 2023 and 68% in July] **Chart 10. Ukrainian refugee median net wage** <sup>**10**</sup> [^10: See the note on median wage estimation method in the Online Technical Appendix.]\n\nWorking age (women 15-59, men 15-64) PLN, 18-64 age group\n\n\n4,000\n\n\n69%\n\n\n\n**Ukrainian refugees are more likely**\n**to be employed in elementary**\n**occupations than pre-war Ukrainian**\n**migrants, non-Ukrainian foreigners,**\n**and Polish citizens, but they are**\n**also the group to have improved**\n**the most in the last two years.** The\ndata as of June 30, 2024 shows that\n38% of Ukrainian refugees worked in\nelementary occupations,", "source": "jad_paddy_docs", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jad_paddy_docs:000001:7:0:0", "start": 1010, "end": 1059, "surface": "Polish central bank surveys of Ukrainian refugees", "probe_tag": "keep", "probe_score": 0.9709, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000001:7:0:1", "start": 1602, "end": 1626, "surface": "data as of June 30, 2024", "probe_tag": "confusion", "probe_score": 0.7759, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-076", "text": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n\nFor the regional analysis, population weights were\napplied based on the most up-to-date refugee\npopulation figures for each country, ensuring the\nfindings accurately represented the broader\nregional refugee population. To maintain\ncomparability, the figures for 2023 presented in this\nreport were also re-estimated using survey weights.\n\n\nThis report utilises the criteria of the Washington\nGroup on Disability Statistics Short Set on\nFunctioning (WG-SS) <sup>7</sup> . The assessment included a\ncomprehensive set of questions covering mobility,\nvision, hearing, cognition, self-care, and\ncommunication. For the purpose of this report,\ndisability is defined as level 3 and above, indicating\nsignificant limitations in functioning (‘a lot of\ndifficulty’ or ‘cannot do at all’). For indicators related\nto chronic illness and vaccination, respondents\nself-reported whether they or any household\nmembers had a chronic illness and whether children\nin the household had received measles vaccine.\n\n\nTo facilitate trend monitoring, the questionnaires\nwere standardized across all countries, ensuring\nconsistency in the majority of indicators between\n2023 and 2024. Since the 2023 regional survey did\nnot include data from Latvia, Lithuania, and Estonia,\nvalues for these countries were excluded from the\n2023–2024 comparison. To maintain accuracy, only\nvalid responses were included in the calculations,\nwith responses such as ‘prefer not to answer’ or ‘do\nnot know’ excluded. To facilitate interpretation,\ncertain response options were consolidated into\nbroader categorical variables.\n\n\nTo protect data privacy and maintain confidentiality,\ninformed consent was obtained and documented\nfrom all participants, with clear explanations\nprovided regarding the purpose and use of the\ndata. The complete questionnaires, along with the\nconsolidated anonymized dataset, are available in\nthe <u>[UNHCR Microdata Library.](https://microdata.unhcr.org/index.php/catalog/?page", "source": "jad_paddy_docs", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jad_paddy_docs:000004:6:0:0", "start": 161, "end": 187, "surface": "refugee\npopulation figures", "probe_tag": "confusion", "probe_score": 0.7247, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000004:6:0:1", "start": 1240, "end": 1260, "surface": "2023 regional survey", "probe_tag": "confusion", "probe_score": 0.8437, "luna_label": 1, "luna_reason": "Existing survey coverage informs exclusion from the 2023–2024 comparison."}]}, {"key": "paddy2-077", "text": " the economy. It provides information\non the total impact of shocks on various\naspects of the economy, including the\nlabour market, government revenue, as\nwell as key economic aggregates. It is the\nmost appropriate tool for accounting for\nthe multi-layered impact of Ukrainian\nrefugees. A counterfactual analysis was\nperformed using the latest data on the\nPolish economy to account for the effects\nof other shocks in the economy. The model\nenabled a counterfactual analysis to be\nconducted by isolating the refugee influx\nfrom all other economic shocks, e.g. the\nother macroeconomic consequences of the\nwar in Ukraine. The results were calculated\nfor 2022, 2023 and 2024 with an additional\nlong-term analysis up to 2030 to assess the\neconomy’s long-term adaptation (assuming\nno new shocks, including no countershocks <sup>34</sup> [^34: E.g. refugees keep having lower productivity rather than adapt to level of natives.] ).\n\n\n32 <u>Economics of climate change | Deloitte Australia</u>\n\n\n\n**Chart 32. Average weekly hours in main job**\n\nWomen in 15-64 age group\n\n\n\n68.4%\n\n\n2023-Q2\n\n\n\n68.8%\n\n\n2024-Q2\n\n\n\n2021-Q2\n\n\n\n67.5%\n\n\n2022-Q2\n\n\n\n40.3\n\n\n\n40.3\n\n\n\n40.4\n\n\n\n40.4\n\n\n\n\n\n\n\n\n\n\n\nSource: Deloitte own elaboration based of Eurostat\ndata (Labour Force Survey).\n\n\n\nSource: Deloitte own elaboration based of Eurostat\ndata (Labour Force Survey).\n\n\n\nPart-time\n\nFull-time\n\n\n\n31 Deloitte has not received data that would be detailed as to citizenship, poviat, sex, age group, occupational group, and ZUS insurance code that would be suitable\nfor econometric approach.\n\n\n42\n\n\n\n33 <u>https://www2.deloitte.com/pl/pl/pages/risk/solutions/analiza-ryzyk-klimatycznych-badanie-scenariuszy-z-modelem-DClimate.html34</u>\n\n34 E.g. refugees keep having", "source": "jad_paddy_docs", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jad_paddy_docs:000001:21:2:0", "start": 344, "end": 370, "surface": "data on the\nPolish economy", "probe_tag": "confusion", "probe_score": 0.4794, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000001:21:2:1", "start": 1215, "end": 1228, "surface": "Eurostat\ndata", "probe_tag": "drop", "probe_score": 0.006, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000001:21:2:2", "start": 1230, "end": 1249, "surface": "Labour Force Survey", "probe_tag": "keep", "probe_score": 0.9867, "luna_label": 1, "luna_reason": "Eurostat survey data underlie the chart’s reported employment figures."}]}, {"key": "paddy2-078", "text": "unhcr.org/en/situations/ukraine)</u>\n4 According to the active PESEL UKR database.\n5 According to the active PESEL UKR database in October 2023.\n6 Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.\n\n\n06\n\n\n\n7  According to the Labour Force Survey data from Eurostat.\n8  According to the harmonized unemployment rates from Eurostat.\n9  According to the quarterly NBP survey.\n10 According to the UNHCR (2023) survey.\n11 According to the social security data until 30th September 2023.\n12 Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.", "source": "jad_paddy_docs", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jad_paddy_docs:000007:3:4:0", "start": 279, "end": 317, "surface": "Labour Force Survey data from Eurostat", "probe_tag": "keep", "probe_score": 0.9701, "luna_label": 1, "luna_reason": "Existing Eurostat Labour Force Survey data is cited as the basis for a statement."}, {"key": "sample:jad_paddy_docs:000007:3:4:1", "start": 404, "end": 424, "surface": "quarterly NBP survey", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:3:4:2", "start": 487, "end": 533, "surface": "social security data until 30th September 2023", "probe_tag": "keep", "probe_score": 0.9598, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:3:4:3", "start": 569, "end": 622, "surface": "Multi-Sector Needs Assessment Poland 2023 survey data", "probe_tag": "keep", "probe_score": 0.9996, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-079", "text": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\non the other sectors by enhancing connectivity of the host population and refugees to markets. The existing\nroad infrastructure in West Nile Sub-Region is of poor quality and not motorable especially during rains.\nAccess to health facilities and referral medical units is also encumbered by the dilapidated road network.\n\n\n11. **Uganda was ranked 127** <sup>**th**</sup> **out of 162 countries in the 2018 Gender Inequality Index** <sup>11</sup> . Prevalence rates of\ngender-based violence (GBV) in Uganda are high. According to the Uganda Demographic and Health Survey\n(UDHS) <sup>12</sup>, 56 percent of women have experienced spousal violence and 22 percent sexual violence. The\nfigures for Violence Against Children (VAC) are also high, with 59 percent of females and 68 percent of males\nreporting experiencing physical violence during childhood. <sup>13</sup> Adolescent girls in Uganda are more likely to\nbe poor, miss out on school and are at a greater risk of contracting HIV. <sup>14</sup> Of Ugandans ages 13-17 years,\none in four girls and one in ten boys reported sexual violence in 2015. <sup>15</sup> Nearly a quarter of teenage girls in\nUganda become pregnant. <sup>16</sup> The intersection with poverty and lack of access to education is the greatest\nrisk to violence against adolescent girls, particularly in rural areas. Refugee women/girls are at high risk of\nseveral forms of GBV including sexual exploitation and abuse (SEA), rape, forced and child marriage and\nintimate partner violence (IPV) <sup>17</sup>", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000050:14:0:0", "start": 499, "end": 527, "surface": "2018 Gender Inequality Index", "probe_tag": "keep", "probe_score": 0.9487, "luna_label": 1, "luna_reason": "Named index provides Uganda’s 2018 international ranking."}, {"key": "jdc_operational:000050:14:0:1", "start": 631, "end": 667, "surface": "Uganda Demographic and Health Survey", "probe_tag": "keep", "probe_score": 0.9706, "luna_label": 1, "luna_reason": "Survey is cited for violence prevalence findings among Ugandan women."}]}, {"key": "paddy2-080", "text": "*<u>Year 3</u>** **<u>Total</u>**\n\n**(In millions of USD)**\n\n**Health** **16.5** **19.8** **26.0** **62.3**\nHospitalization 11.0 13.1 15.8 39.9\nPrimary Healthcare Services-MOPH 2.3 2.8 5.6 10.7\nMedication (Chronic) 3.2 3.8 4.6 11.6\n**Education** 3.4 5.3 7.0 15.7\n**E-card Food Voucher** 18.0 36.0 70.2 124.2\n\n\n**Total** **37.9** **61.1** **103.2** **202.2**\n\n\nOf which from Government (Health & Education) 19.9 25.1 33.0 78.0\n\nOf which TFL and UNHCR 6.8\n\nOf which from Other (E-card food) 11.2 36.0 70.2 117.4\n\n\n_Source: MOSA NPTP Team & World Bank Staff Calculations_\n\n\n1/ Year 1 refers to 2014/2015, Year 2 to 2015/2016, and Year 3 to 2016/2017 respectively.\n\n\n13. **The expected coverage rate of extremely poor individuals by the end of the project.**\nWe are making the assumption that, by 2016/2017, 100 percent of extremely poor households\nwill be covered with NPTP benefits. Since we are using 2004 HBS data to simulate NPTP\nimpact, we are assuming that the extreme poverty line is US$3.84 per capita per day, and that 7.2\npercent of the population (or 306,251 individuals) were extremely poor in that year, in addition\nto the", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000047:68:1:0", "start": 900, "end": 913, "surface": "2004 HBS data", "probe_tag": "keep", "probe_score": 0.937, "luna_label": 1, "luna_reason": "Existing 2004 household survey data used to simulate NPTP impact and poverty."}]}, {"key": "paddy2-081", "text": "**The World Bank**\nDecent Employment Creation for Vulnerable Lebanese Citizens and Syrian Refugees in Livestock Value Chains\n\n\nmerchandise exports from 1998–2017 (World Bank, 2021). The production of animal products, such\nas cow’s milk, poultry, sheep and goats and eggs, is one of the main activities in rural Lebanon,\nparticularly in the northern areas. In these areas, the poorest in the country, the majority of farmers\ndepend on dairy products as their primary means of subsistence (Abdallah _et al_ ., 2018). The 2016\nproduction survey indicated that the number of cattle heads reached 86 265, of which 62 percent\nwere dairy cows, accounting for 82 percent of the total value of milk production (FAO, 2021).\n5. **In smallholder and family farming households, women play a prominent role in animal production,**\n**but major constraints impede female work in the livestock value chain.** According to an FAO review\n(2021), in homesteads, women take care of poultry (with an average of 10–50 backyard chicken),\nsheep, goats and cattle. They are responsible for all aspects of animal husbandry, especially on farms\nwith less than 3 cows. The tasks include milking, feeding, providing water, fodder collection,\npreparing feed rations, and feed and care for the animals, particularly small ruminants, rabbits and\npoultry. Women also clean stables and poultry houses, as well as ensure egg collection and processing\nof milk into butter, cheese, yogurt, labneh, and other dairy products (in many cases, the processing\nand marketing activities are done through cooperatives). Marketing tasks performed by women\ninclude selling fresh milk, eggs and processed dairy products to people coming to their doorsteps\nfrom within their same villages or nearby villages or to middlemen coming to their doors. Female\ntraining needs in animal production include capacity building in the areas of animal nutrition and feed\nration mix, disease diagnosis and treatment", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000036:3:0:0", "start": 519, "end": 541, "surface": "2016\nproduction survey", "probe_tag": "keep", "probe_score": 0.9275, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-082", "text": "up> Although labor inspectors have an important role to play in enforcing\nworker rights.\n\n\n28 The unemployment rate was 13 percent in 2015, 13 percent in 2010, 15 percent in 2005 and 14 percent in\n2000. There are approximately 210,000 unemployed Jordanians in 2015. See Employment Unemployment\nSurvey for 2015. Available online at: http://www.dos.gov.jo/dos_home_e/main/linked-html/Emp&Un.htm\n29 In 2015, unemployment rates were 23 percent among women versus 11 percent among men; 19 percent\namong those with a bachelor degree or higher versus 11 percent among those with less than secondary\neducation; and 15 percent among 20–24 year olds, 26 percent among 25–29 years, and 14 percent among 40–54\nyear olds. Employment Unemployment Survey for 2015. Available online at:\n<u>http://www.dos.gov.jo/dos_home_e/main/linked-html/Emp&Un.htm. The largest share of unemployed</u>\nJordanians live in Amman (32 percent of the total), followed by Irbid (22 percent), Zarqa (14 percent), Mafraq\n(6 percent), and Balqa (6 percent). The remaining seven governorates are home to the remaining 21 percent of\nunemployed Jordanians.\n30 In 2015, the MOL issued 324,000 annual work permits, the majority of which were issued to Egyptians (65.3\npercent), with 3 percent to other Arabs and 26 percent to others. According to the new census, there are about\n636,000 Egyptians and 200,000 non-Arabs in Jordan. It is not clear how many of these are working informally.\n31 Economic migrants are subject to a minimum wage, which is lower than the minimum wage for Jordanian\nworkers. The separate minimum wage makes non-Jordanian", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000045:68:1:0", "start": 270, "end": 300, "surface": "Employment Unemployment\nSurvey", "probe_tag": "keep", "probe_score": 0.9882, "luna_label": 1, "luna_reason": null}, {"key": "sample:jdc_operational:000045:68:1:1", "start": 1307, "end": 1317, "surface": "new census", "probe_tag": "keep", "probe_score": 0.9572, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-083", "text": " activities.\n\n\n3. **Lebanon is one of the countries hardest hit by COVID-19 in the Middle East and North Africa (MENA) region** .\nLebanon is in the midst of three mega-crises: the economic crisis; the COVID-19 pandemic; and the aftermath of\nthe Port of Beirut explosion. The crippling economic crisis starting in October 2019 has greatly constrained the\nhealth system's ability to provide accessible and affordable health services. As of May 4, 2022, Lebanon has\nrecorded a total of 1,097,204 confirmed cases and 10,393 deaths since the start of the pandemic. <sup>1</sup> A total of\n5,602,398 COVID-19 vaccine doses have been administered. <sup>2</sup> Of the total number of vaccinated people, 2,677,312\nreceived at least one dose (approximately 49 percent of the eligible population of ages 12 and older), and\n2,351,269 have been fully immunized with two doses (approximately 43 percent of the eligible population of ages\n12 and older). Among those who received two doses, approximately 24 percent received a third dose. <sup>2</sup>\n\n4. **The World Bank has been supporting Lebanon in strengthening its response to COVID-19 through its existing**\n\n\n1 MoPH COVID-19 Surveillance in Lebanon Daily Report – May 4, 2022\n2 MoPH COVID-19 Surveillance in Lebanon Daily Report – April 25, 2022\n\n\nPage 7 of 54", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000000:11:2:0", "start": 1155, "end": 1205, "surface": "MoPH COVID-19 Surveillance in Lebanon Daily Report", "probe_tag": "keep", "probe_score": 0.9469, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-084", "text": "**The World Bank**\nSupport for Social Recovery Needs of Vulnerable Groups in Beirut (P176622)\n\n\nwere left with a physical disability. <sup>49</sup> However, with the total number of injuries reported in the thousands,\nthis figure could in fact be considerably larger.\n\n21. **The heightened needs of persons with disabilities and OPs during and after crises has been well-**\n**documented with strong evidence showing that these needs are often overlooked.** <sup>50</sup> In the immediate\naftermath of the blast, cash assistance and shelter support were identified as key areas for emergency\nsupport, while access to medical supplies and services were identified as top priorities for Persons with\nDisabilities and older persons in the medium to longer term. In a survey of a sample of residents of the\nPOB area from all age groups, 34% reported that their family had difficulties accessing health services and\n45% reported difficulties accessing medicines. <sup>51</sup> This was a particular concern for 65% of older personheaded households who have a chronic disease that require medicine and are at a heightened risk of\ncontracting COVID-19. Elderly women who live alone are particularly vulnerable, given their greater\nlikelihood of not having access to savings, pensions, and other social protection instruments. <sup>52</sup>\n\n22. **To support the elderly and disabled Syrian refugees and vulnerable Lebanese, the GoL and the UN LCRP**\n**strategy guided programming for 2020**, specifically by the Persons with Specific Needs sub-committee\nunder the Protection Sector. The sub-committee identified that in 2020, gaps in support to persons with\ndisabilities were particularly at risk of emerging. Activities conducted by sector partners include: (i)\nsupport Primary Health Care Centres (PHC); (ii) support to Mobile Medical Units (MMUs)", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000002:9:0:0", "start": 763, "end": 794, "surface": "survey of a sample of residents", "probe_tag": "keep", "probe_score": 0.9198, "luna_label": 1, "luna_reason": "Survey findings report concrete health-access difficulties among residents."}]}, {"key": "paddy2-085", "text": "|Intermediate Results Indicators|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n|||||Cumulative Target Values|Cumulative Target Values|Cumulative Target Values|Frequency|Data<br>Source/Methodology|Responsibility for Data<br>Collection|\n|Indicator Name|Core|Unit of<br>Measure|Baseline<br>2013|2014-15<br>(Year 1)|2015-16<br>(Year 2)|2016-17<br>(Year 3)||||\n|Number of NPTP Applicants||Number|480,000|550,000|700,000|800,000|Quarterly|- NPTP database|NPTP Program|\n|Time lapse between application<br>and eligibility notification||Months|3|1|1|1|Quarterly|- NPTP database|NPTP Program|\n|Household awareness of NPTP||Percentage|40|60|80|90|Two time during the life<br>of the program|- Opinion Poll surveys<br>(Y2, Y3)|NPTP Program|\n|Proportion of assisted people<br>informed about the e-card food<br>program||Percentage|0||100||Once after the first year<br>of the program|- NPTP database|NPTP Program<br>|\n\n\n23", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000047:33:0:0", "start": 478, "end": 491, "surface": "NPTP database", "probe_tag": "confusion", "probe_score": 0.8819, "luna_label": 0, "luna_reason": "Standalone database entry inside an indicator table."}, {"key": "sample:jdc_operational:000047:33:0:1", "start": 724, "end": 744, "surface": "Opinion Poll surveys", "probe_tag": "keep", "probe_score": 0.9834, "luna_label": 0, "luna_reason": "Future opinion-poll surveys are planned for program-year indicator measurement."}]}, {"key": "paddy2-086", "text": " which none had accessed support\nservices. <sup>23</sup> [^23: UNHCR, (Oct 2017), Sexual Violence Against Men and Boys.] Data in Beirut/Mount Lebanon indicates that in 2020, 21%of child sexual abuse survivors are\n\n\n17 <u>[https://www.icj.org/wp-content/uploads/2019/07/Lebanon-Gender-Violence-Publications.pdf](https://www.icj.org/wp-content/uploads/2019/07/Lebanon-Gender-Violence-Publications.pdf)</u>\n18 <u>[https://today.lorientlejour.com/article/1249052/despite-major-steps-forward-in-domestic-violence-law-coronavirus-lockdowns-expose-the-](https://today.lorientlejour.com/article/1249052/despite-major-steps-forward-in-domestic-violence-law-coronavirus-lockdowns-expose-the-many-shortcomings-that-remain.html)</u>\n<u>[many-shortcomings-that-remain.html](https://today.lorientlejour.com/article/1249052/despite-major-steps-forward-in-domestic-violence-law-coronavirus-lockdowns-expose-the-many-shortcomings-that-remain.html)</u>\n\n\n19 <mark>United Nations Population Fund, Gender Based Violence Annual Report 2020, UNFPA, Lebanon.</mark>\n20 <u>[https://aiw.lau.edu.lb/news-events/aiw-updates/the-aiw-statement-of-lebanon-tra.php](https://aiw.lau.edu.", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000002:5:2:0", "start": 121, "end": 149, "surface": "Data in Beirut/Mount Lebanon", "probe_tag": "confusion", "probe_score": 0.609, "luna_label": 1, "luna_reason": "Geographic data are tied to a concrete 2020 survivor statistic."}]}, {"key": "paddy2-087", "text": " (305 in Koboko District, 423 in Moyo District and\n1,780 in Yumbe District). There are 741 structures located in the proposed RoW; they include permanent/semipermanent buildings and others such as gates, soak pits, pit latrines, fences and perimeter walls etc. It is also\nestimated that about 266 households will be physically displaced as a result of the Project while another 2002\nPAPs across the three districts will be economically displaced. Taking into account that project preparation\ntimelines are relatively short, there will be particular attention to ensure adequate quality of the RAP especially\nin terms of (i) designing Livelihood Restoration Plans, (ii) appropriate measures to support PAPs from vulnerable\ngroups and those with disabilities, and (iii) carrying out a comprehensive census. PAPs will continue to be engaged\nthroughout the RAP processes and particularly during its implementation to address any issues that might have\nbeen missed out in earlier studies. Additional measures may include thorough screening at project preparation,\nthe project proponent’s commitment to monitoring, implementing agreed measures and institutional\nstrengthening measures. All affected properties will be subjected to a transparent valuation process and will be\npromptly and adequately compensated. A Livelihood Restoration Plan has been developed as part of the RAP\n\n\nPage 43 of 80", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000050:47:2:0", "start": 783, "end": 803, "surface": "comprehensive census", "probe_tag": "confusion", "probe_score": 0.0948, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-088", "text": "**Annex II: Detailed Project Description**\n\n\n**LEBANON**\n**Emergency National Poverty Targeting Program Project (P149242)**\n\n\n**Project Components**\n\n\n1. The Emergency NPTP project consists of two technical components and a fiduciary\noperations component. Specifically, the components are: (i) administration of the NPTP, (ii)\nprovision of Social Assistance, and (iii) fiduciary Operations.\n\n\n**_Component 1: Administration of the National Poverty Targeting Program (US$11.19 million_**\n**_total cost, of which US$3.89 million financed from TFL, and US$6.9 million from the GOL)_** <sup>**_29_**</sup> [^29: There is a financing gap of US$390,107 million for this component.]\n\n\n2. This component’s objective is to ensure an effective and efficient administration and\nimplementation of the NPTP through its structures in the MOSA and the PCM, so that it can\nexpand the coverage and enhance the social assistance to extremely poor Lebanese households\nand those affected by the Syrian crisis. This component will also improve the efficiency of the\nNPTP. To achieve its objective, this component will finance technical assistance for the\nfollowing activities:\n\n\n(a) Supporting the program management team in the MOSA and the PCM;\n(b) Recertification of applicants in 2015 including refining the program application\nforms and PMT questionnaire;\n(c) Upgrading the NPTP Management Information System (MIS);\n(d) Refining the grievance and redress mechanism for improved efficiency and\ntransparency;\n(e) Monitoring and evaluation of the program, including evaluating the business\nprocesses of the NPTP, and implementation of short quantitative and qualitative\nsurveys (beneficiary assessments, opinion polls on awareness, etc.);\n(f) Carrying out an outreach campaign to enroll new beneficiaries particularly in the\npoorer and remote areas;\n(g) Providing training to Beneficiaries in the use of Food", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000047:35:0:0", "start": 1660, "end": 1683, "surface": "beneficiary assessments", "probe_tag": "confusion", "probe_score": 0.6411, "luna_label": 0, "luna_reason": "Planned surveys are to be implemented as project monitoring activities."}, {"key": "jdc_operational:000047:35:0:1", "start": 1685, "end": 1711, "surface": "opinion polls on awareness", "probe_tag": "confusion", "probe_score": 0.0912, "luna_label": 0, "luna_reason": "Planned opinion polls are project-generated data activities, not existing data use."}]}, {"key": "paddy2-089", "text": "**The World Bank**\nDecent Employment Creation for Vulnerable Lebanese Citizens and Syrian Refugees in Livestock Value Chains\n\n\nRelationship to CPF\n\n10. The activity is aligned with the _Lebanon - Country Partnership Framework for FY17-FY22 by_\n_contributing to the_ Focus Area 2: Expand Economic Opportunities and Increase Human Capital,\nthrough improving access to finance, skills development, and strengthening safety nets for the\npoorest Lebanese farming households and Syrian refugees. It will help Lebanon mitigate the\neconomic and social impact of the Syrian crisis, financial crisis and the COVID-19 pandemic, safeguard\nthe country’s development gains, and enhance the prospects for stability and development in the\ncoming years.\n\n\n**References**\n\n\nIFC, 2020. Lebanon Agribusiness Deep Dive. Draft, IFC, 2020.\n\n\nILO and FAFO. 2020. Rapid Impact Assessment of COVID-19 on vulnerable workers and small-scale\nenterprises in Lebanon.\n\n\nUNHCR, UNICEF and WFP. 2019. VASYR 2019 - Vulnerability Assessment of Syrian Refugees in Lebanon.\nhttps://reliefweb.int/report/lebanon/vasyr-2019-vulnerability-assessment-syrian-refugees-lebanon\n\n\nWorld Bank, 2021. World Bank Indicators https://data.worldbank.org/indicator accessed 8/19/2021\n\n\nFAO. 2021. Country gender assessment of the agriculture and rural sector – Lebanon. Beirut.\nhttps://doi.org/10.4060/cb3025en\n\n\nDal, E., Díaz-González, A.M., Morales-Opazo, C. & Vigani, M. 2021. Agricultural sector review in Lebanon. FAO\nAgricultural Development Economics Technical Study No. 12. Rome, FAO. https://doi.org/10.4060/cb5157en\n\n\nWorld Bank. 2020. World Development Indicators. Washington, DC: World Bank Group. Accessed January 22,", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000036:5:0:0", "start": 1154, "end": 1175, "surface": "World Bank Indicators", "probe_tag": "confusion", "probe_score": 0.6973, "luna_label": 0, "luna_reason": "Reference-list entry without an attached indicator claim or demonstrated data use."}]}, {"key": "paddy2-090", "text": "schools who return to<br>school once the school<br>system is reopened|Annual<br>|The<br>enrollment<br>will be<br>monitored<br>through the<br>EMIS data.<br>|The enrollment will be<br>monitored through the<br>EMIS data.<br>|MoES/PCU<br>|\n\n\n|Monitoring & Evaluation Plan: Intermediate Results Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|IRI 1: Awareness and health safeguarding<br>messages disseminated to students,<br>teachers, parents and community<br>members through various media (SMS,<br>text, TV and radio) (number)|Defn: Awareness and health <br>safeguarding messages are<br>designed to reach a specific<br>audience (in this case:<br>students, teachers and<br>parents) to stop the spread|Bi-annual<br>|Approved m<br>aterials<br>|Reports on materials<br>disseminated<br>|CIM, Gender Unit<br>|\n\n\nPage 31 of 43\n\n\nOfficial Use\n\n\n\n**ME PDO Table SPACE**", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000034:35:1:0", "start": 141, "end": 150, "surface": "EMIS data", "probe_tag": "confusion", "probe_score": 0.6811, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-091", "text": " that of those of Grade 2 was 14 percent and 7 percent, respectively. The positive difference of this proportion\nbetween Grade 6 and Grade 2 students, either in PASEC 2014 (5 percentage points) or PASEC 2019 (18 percentage points),\nhighlights the potential for preschool attendance to help pursue studies up to the end of the primary education. However,\nunlike Grade 2 students, there is no significant difference in the performance of Grade 6 students, regardless of preschool\nattendance. The difference observed for Grade 2 students underscores the importance of pre-primary in improving\nprimary students’ performance, but only up to that grade-not beyond. If, despite the embryonic state of pre-primary\neducation, such a performance can be achieved, its development through the improving of its pedagogical and learning\nenvironment, and the establishment of a strong and well-coordinated monitoring system, would result in the\nachievement of higher learning outcomes in the primary education. Therefore, it is necessary to have a full diagnostic of\nthe pre-primary education to inform its expansion.\n\n\n16. **The primary education system is not yet fully integrated around the curriculum** . A competency-based approach\nwas officially adopted in 2008, and the primary curriculum has been revised accordingly. However, a recent report found\nthat the approach has not been adequately integrated into the pre-service or in-service teacher training curriculum, with\nthe exception of DP-financed in-service trainings for community teachers. Further, teaching-learning materials and\nevaluative methods are not yet fully aligned with the competency-based approach. <sup>25</sup> [^25: Évaluation des Capacités d’Accueil et de Formation des Écoles Normales d’Instituteurs bilingues (ENIB) et des Écoles Normales Supérieures (ENS)\nde la République du Tchad. Rapport Technique, 2020, pp. 30 ff.] There is also a disconnect between\nthe curriculum’s languages of instruction and the manner in which it is delivered. The primary education system has been\nofficially bilingual (Arab and French) since 1995. However, only 10 percent of primary teachers are bilingual.", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000009:11:1:0", "start": 161, "end": 171, "surface": "PASEC 2014", "probe_tag": "confusion", "probe_score": 0.6209, "luna_label": 1, "luna_reason": "Named assessment cited for performance differences between student grades."}, {"key": "jdc_operational:000009:11:1:1", "start": 197, "end": 207, "surface": "PASEC 2019", "probe_tag": "confusion", "probe_score": 0.4809, "luna_label": 1, "luna_reason": "Named assessment round cited for the 18-percentage-point performance difference."}]}, {"key": "paddy2-092", "text": " on the platform). <br>Data on vaccination by<br>nationality from IMPACT<br>will be used to monitor<br>progress against this<br>indicator based on the<br>assumption that the<br>majority of the Syrians and<br>Palestinians pre-registered<br>on the IMPACT platform|<br> <br>6 months<br>|<br>IMPACT and<br>national<br>surveys by UN<br>(UNCHR and<br>UNRWA) and<br>other<br>available<br>sources<br>|Administrative report<br>and estimation from<br>national surveys<br>|PMU/MoPH<br>|\n\n\nPage 45 of 54", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000000:49:1:0", "start": 441, "end": 457, "surface": "national surveys", "probe_tag": "confusion", "probe_score": 0.0797, "luna_label": 1, "luna_reason": "National surveys are declared as sources for the administrative report and estimation."}]}, {"key": "paddy2-093", "text": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\n**B. Introduction and Context**\n\nCountry Context\n\n1. **South Sudan was beset by decades of armed conflicts prior to its independence in 2011, and these have only**\n**become increasingly complex in the years since.** Southern Sudan, as the region was called before independence, has been\nmarred by conflict since 1955. The region experienced systematic marginalization and underdevelopment under both\nBritish and Sudanese rule, depriving the region of physical and human capital development. At independence in July 2011,\nSouth Sudan ranked almost at the bottom of the global development indicators with little infrastructure, basic services\nprovided almost entirely through humanitarian aid, and an economy completely dependent on oil. Renewed civil conflict\nbroke out in December 2013 as the tensions among different groups intensified and violence continues to date. Beginning\nas in-fighting between the Sudan People’s Liberation Movement (SPLM) led by the President and the SPLM in Opposition\n(SPLM-IO) led by the then Vice President, the conflict grew more fragmented as groups excluded from previous peace\nnegotiations took up arms to establish their claims. There are now over 40 armed groups involved in the conflict. Violence,\nwhich was largely limited to the Greater Upper Nile region in the first years of the war, has spread to other historically\nstable locations such as Western and Central Equatoria States, coming to engulf the entire country. The renewed violence\nhas <mark>undermined the development gains since independence and worsened the humanitarian situation.</mark>\n\n2. **The country faces a challenging economic situation compounded by misplaced priorities which exacerbates**\n**food insecurity and access to basic services.** The economy is estimated to have recovered with a growth rate of 3.2\npercent in fiscal year (FY) 2019. This reflects a strong rebound in the oil sector while non-oil economy", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000014:2:0:0", "start": 671, "end": 700, "surface": "global development indicators", "probe_tag": "confusion", "probe_score": 0.8816, "luna_label": 1, "luna_reason": "Indicators support South Sudan’s near-bottom global development ranking."}]}, {"key": "paddy2-094", "text": "**The World Bank**\nChad Rural Mobility and Connectivity Project (P164747)\n\n\n**ANNEX 3: Climate Change Impact Study**\n\n\nRural Mobility and Connectivity Project in Chad:\nAssessing the Vulnerability to and Cost of Climate Change Impacts on a Road Rehabilitation Project\n\nusing IPSS\n\n\n**Overview and Background**\n\n\n1. The assessment of this road rehabilitation project included in its evaluation an engineering-based\nanalysis tool called the IPSS <sup>12</sup> to further understand the vulnerabilities of the road segments to the impacts\nof climate change. IPSS, developed by researchers out of the University of Colorado, has been used to\nidentify vulnerabilities in the road under study, to help better manage the risk associated with climate\nchange and to help better inform specific adaptation investment options for the road.\n\n\n2. IPSS utilizes stressor-response engineering data coupled with IPCC-approved climate change data\nto estimate the potential impacts from specific climate stressors, in this case flooding and precipitation.\nThe tool is then used to assess the cost of reactively addressing the impacts of climate change (fixing\ndamages) versus proactively mitigating the impacts of climate change (through upgrades in the\nconstruction process of the roads). The tool will shed light on the cost incurred by changing climate in\nterms of keeping the road maintained and will inform decisions regarding investment strategy. IPSS was\nrun for the first phase (75 km) of the Chad Rural Mobility and Connectivity Project and will be utilized to\nanalyze the remaining 325 km stretch of road as well. It is important to note that the analysis does not\nsupport any one of the climate models or support that any outcome is more likely than another. The\nresults displayed in the following paragraph show the predictions of the median model, as noted.\n\n\n3. The climate-induced hazards threatening the project include flooding and change in precipitation.\nThese pose a threat to mobility, accessibility, and thus economic growth. Flooding has the potential to\nin", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000048:58:0:0", "start": 847, "end": 881, "surface": "stressor-response engineering data", "probe_tag": "confusion", "probe_score": 0.2518, "luna_label": 1, "luna_reason": "Existing engineering data are used to estimate climate-stressor impacts."}, {"key": "jdc_operational:000048:58:0:1", "start": 895, "end": 928, "surface": "IPCC-approved climate change data", "probe_tag": "confusion", "probe_score": 0.8432, "luna_label": 1, "luna_reason": "IPCC-approved data are used by IPSS to estimate climate impacts."}]}, {"key": "paddy2-095", "text": "**The World Bank**\nChad COVID-19 Strategic Preparedness and Response Project (P173894)\n\n\n**B.** **Results Monitoring and Evaluation Arrangements**\n\n\n55. **The M&E activities will be the responsibility of REDISSE IV’s PCU at the MOPH** . This unit will be responsible\nfor collecting and compiling all the data related to the PDO and intermediary indicators in the results\nframework. It will evaluate the results and report them to the World Bank before each of the two annual\nsupport missions. Given that REDISSE IV results framework focuses on the JEEs, reporting under this project\nwill be complemented, when possible, by reports on REDISSE IV’s indicators.\n\n56. **The M&E activities will support M&E efforts from the MOPH** . The project’s results framework has been\ndesigned to provide useful information on the implementation of the National Action Plan. As a result, M&E\nactivities under this project will strengthen MOPH’s M&E efforts to track and manage information. The\nproject will closely collaborate with REDISSE IV which will support the roll-out of DHIS2 and the overall\nstrengthening of the country’s health management information system, as well as to facilitate recording\nand real-time sharing of information. Lastly, the project will use Geo-enabled Monitoring Systems (GEMS)\nto supervise project implementation despite the travel restrictions.\n\n57. **It should be noted that given that standard reporting standards from UN agencies are not adequate** for\nthe context of an emergency response, agencies engaged under this project will be required to produce\nweekly reports and to share these with all relevant stakeholders involved in the COVID-19 response in Chad.\n\n58. **Large volumes of personal data, personally identifiable information and sensitive data are likely to be**\n**collected and used in connection with the management", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000039:24:0:0", "start": 634, "end": 657, "surface": "REDISSE IV’s indicators", "probe_tag": "confusion", "probe_score": 0.5767, "luna_label": 0, "luna_reason": "Future reporting use is planned, not an existing indicator analysis."}]}, {"key": "paddy2-096", "text": "<br>of which: (i) women; (ii)<br>host population; (iii)<br>refugees3||Number|0|545,000<br>(245,250)<br>(395,000)<br>(150,000)<br>|NA<br>|NA<br>|545,000<br>(245,250)<br>(395,000)<br>(150,000)<br>|Annual|Surveys and service<br>delivery records of<br>municipalities|Municipalities,<br>MOMA|\n|Participating municipalities<br>ensuring pre-crisis levels of||%|04|0|50|50|50|Annual|Surveys and service<br>delivery records of|Municipalities,<br>MOMA|\n\n\n\n2 Direct beneficiaries include the Jordanian host population who will benefit irrespective of the number of Syrian refugees living in the participating\nmunicipalities.\n3 Conflicted affected people include both the Jordanian host population and the Syrian refugees living in participating municipalities.\n4 Baseline data on municipal pre-crisis investments is available for all participating municipalities.\n\n\n21", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000026:32:4:0", "start": 753, "end": 802, "surface": "Baseline data on municipal pre-crisis investments", "probe_tag": "confusion", "probe_score": 0.4724, "luna_label": 0, "luna_reason": "States data availability without citing analysis, finding, or substantive use."}]}, {"key": "paddy2-097", "text": " and outlines the link with the Project\nactivities. Table 2.2 gives Component-wise key activities that have direct and/or indirect climate co-benefits.\n\n\n**Table 2.1: Climate Change Vulnerability Context, Project’s Intent for addressing it and Link to Project**\n**Activities**\n\n\n\n\n\n\n\n[71 https://preview.grid.unep.ch/index.php?preview=home&lang=eng](https://preview.grid.unep.ch/index.php?preview=home&lang=eng) Global Risk Data Platform (UNEP, UNISDR)\n_72_ Unbreakable - Building the Resilience of the Poor in the Face of Natural Disasters, World Bank Group\n_[73 https://www.emdat.be](https://www.emdat.be/)_ The International Disaster Database - Centre for Research on the Epidemiology of Disasters (CRED)\n_74_ Shock Waves - Managing the Impacts of Climate Change on Poverty, World Bank Group\n_75_ [https://climateknowledgeportal.worldbank.org/country/uganda/climate-data-projections](https://climateknowledgeportal.worldbank.org/country/uganda/climate-data-projections)\n\n\n\nPage 71 of 80", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000050:75:1:0", "start": 412, "end": 437, "surface": "Global Risk Data Platform", "probe_tag": "confusion", "probe_score": 0.6086, "luna_label": 0, "luna_reason": "Platform is cited without shown data use, figures, analysis, or targeting."}, {"key": "jdc_operational:000050:75:1:1", "start": 614, "end": 645, "surface": "International Disaster Database", "probe_tag": "confusion", "probe_score": 0.6562, "luna_label": 1, "luna_reason": "Named existing disaster database cited as a source for vulnerability context."}]}, {"key": "paddy2-098", "text": " such, it is unlikely\nthat Lebanon can exclusively depend on this pipeline for its energy security in the short- to medium-term.\n\n\n10. In addition to reliance on expensive fuel oils, high losses add to the cost of electricity service. EDL’s networks are\ninefficient, with total losses (technical and non-technical) of around 36 percent in 2017. Constituting 21 percent of energy\nsent out, non-technical losses (theft and billing errors) are the primary cause for concern. Taking into account these losses,\nthe total cost is estimated at around US$0.20 per kWh sold. In comparison, EDL’s average tariff, which has not changed\nsince 1994, is around US$0.095/kWh, covering only 45 percent of average operating costs. The low collection rate (68\n\n\n2 A study by the Ministry of Water and Energy and UNDP, 2017, entitled “The Impact of the Syrian Crisis on the Lebanese Power Sector\nand Priority Recommendations”, found that around 45 percent of displaced Syrians do not have metered connections. Similarly, in a\nUNCHR Vulnerability Assessment of Syrian Refugees in Lebanon, 34 percent of households who reported to have legal connections no\nelectricity bills were available amounting to around 44 percent of unbilled connections, which is consistent with the UNDP and MEW\nreport. Regarding differentiated access, the UNHCR finds little difference between male and female head of households in shelters,\nhowever, female head of households resorted to coping strategies more often (i.e. in the case of a power cut, etc.) and are reportedly\nmore vulnerable.\n\n\nMar 05, 2019 Page 4 of 10", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000011:3:2:0", "start": 1007, "end": 1056, "surface": "UNCHR Vulnerability Assessment of Syrian Refugees", "probe_tag": "confusion", "probe_score": 0.8705, "luna_label": 1, "luna_reason": "Named vulnerability assessment supports a concrete finding about electricity bills."}]}, {"key": "paddy2-099", "text": "from web<br>platform and<br>surveys<br> <br>|<br>Survey<br>|PSFU and UBOS<br>|\n|The percentage of jobs saved, that would<br>be lost due to COVID 19,|Percentage of firms<br>reporting an improvement<br>in employment|Annual<br>|<br>EPRC Panel<br>Data<br> <br>|Telephone survey<br>|PSFU/UBOS/EPRC<br>|\n|The number of new loans issued to firms<br>in the manufacturing sectors|<br>Loans issued after project<br>start date<br>|Annual<br>|<br>Reporting by<br>Participating<br>FIs and<br>Project portal<br>|Tracking transactions<br>on project web portal<br> <br>|BoU<br>|\n|Beneficiaries reached with financial<br>services|The indicator measures the<br>number of persons<br>benefited from financial<br>services in operations|Annual<br>|<br>|Web based reporting<br>by Participating<br>Financial Institutions to<br>BoU|BoU<br>|\n\n\nPage 53 of 92", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000021:58:1:0", "start": 229, "end": 239, "surface": "EPRC Panel", "probe_tag": "confusion", "probe_score": 0.8334, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-100", "text": "|Col1|Indicator 2.4: Teacher feedback on training and<br>certification system monitored, analyzed, and<br>included in the annual monitoring and progress<br>reports developed by ETC|Col3|No|Yes/No|No|Yes|Annually|MOE|Teacher surveys|\n|---|---|---|---|---|---|---|---|---|---|\n|Reformed<br>student<br>assessment and<br>certification<br>system<br>|Indicator 3.1: Grade 3 diagnostic test on early grade<br>reading and math implemented|7.2|No|Yes/No|No|Yes|Annually|MOE|Assessments records for a<br>sample of schools|\n|Reformed<br>student<br>assessment and<br>certification<br>system<br>|Indicator 3.2: Legal framework for the_Tawjihi_ exam<br>has been adopted so that its secondary graduation<br>and certification function is separated from its<br>function as a screening mechanism for university<br>entrance|7.4|No|Yes/No|No|Yes|Annually|MOE||\n|Reformed<br>student<br>assessment and<br>certification<br>system<br>|Indicator 3.3: Student and Teacher Feedback on first<br>phase_Tawjihi_ reform inform the", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000041:39:0:0", "start": 216, "end": 231, "surface": "Teacher surveys", "probe_tag": "confusion", "probe_score": 0.7636, "luna_label": 0, "luna_reason": null}, {"key": "sample:jdc_operational:000041:39:0:1", "start": 465, "end": 484, "surface": "Assessments records", "probe_tag": "keep", "probe_score": 0.98, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-101", "text": "**The World Bank**\nUganda Digital Acceleration Program (P171305)\n\n\nmicrofinance and banking service providers, with 96 percent of cyberattacks being unreported or\nunresolved. As a legislative framework, the government has enacted a suite of laws that include the\nComputer Misuse Act 2011, the Electronic Signatures Act 2011 and the Electronic Transactions Act\n2011. A review of the existing cybersecurity and cybercrime legislation and an update to the\nCybersecurity Strategy are being supported under currently active RCIP-5 project and the\ngovernment has stated its intentions to accede to the Council of Europe’s Budapest convention on\ncybercrime. The Digital Uganda Vision of 2019, the National Information Security Framework (NISF)\nof 2014 and the National Information Security Strategy (NISS) of 2011 round out the strategic and\npolicy foundations for cybersecurity. To handle incidents and attacks, Uganda has both a national\nComputer Emergency Response Team (CERT) at NITA-U and a Communications Sector CERT at UCC.\nThe country has benefitted from two in-depth cybersecurity diagnostics: a Cybersecurity Maturity\nModel (CMM) assessment was undertaken in 2016 and updated in 2020; the emanating\nrecommendations, for instance on capacity building and awareness raising are reflected in the\npresent project’s design. Uganda was nominated as the regional lead on Cybersecurity under the\nEast African Northern Corridor Infrastructure Project Regional MoU. In 2018, Uganda ranked 7 <sup>th</sup> in\nAfrica in the ITU’s Global Cybersecurity Index, and 65 <sup>th</sup> globally. <sup>47</sup> [^47: International Telecommunications Union, _Global Cybersecurity Index 2018_ . https://www.itu.int/dms_pub/itu-d/opb/str/DSTR-GCI.01-2018-PDF-E.pdf] The country’s next challenges for\ncybersecurity are therefore to expand technical capacity, implement best practice governance and\nmove towards effective, steady-state implementation and sustainability.\n\n\n**14.** **In the area of Data Protection, Uganda is in the early stages of operationalizing a recently**\n**adopted", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000033:8:0:0", "start": 1521, "end": 1547, "surface": "Global Cybersecurity Index", "probe_tag": "confusion", "probe_score": 0.7891, "luna_label": 1, "luna_reason": "ITU index provides Uganda’s 2018 regional and global rankings."}]}, {"key": "paddy2-102", "text": ">|\n|Women in RHD||<br>||||\n|Refugee women||||<br>||\n|Women microenterprises accessing credit<br>from a formal financial institution<br>(Number)|The number of women-<br>owned microenterprises<br>benefiting from finance<br>from a PFI supported by the<br>project.|Continuous<br>. <br>|PFI data.<br>|The PFIs will maintain<br>databases of the<br>enterprises to which<br>they provide credit,<br>disaggregated by social<br>profiles.<br> <br>|The MGLSD to collect the<br>data from the PFIs each<br>month, and compile and<br>report.<br>|\n|Women small enterprises accessing credit<br>from a formal financial institution<br>(Number)|The number of women-<br>owned small enterprises<br>benefiting from bridging<br>finance from a PFI<br>supported by the project.|Annual<br>|PFI data.<br>|<br>The PFIs will maintain<br>databases of the<br>enterprises to which<br>they provide credit,<br>disaggregated by<br>refugee status, district,|The MGLSD to collect the<br>data from the PFIs each<br>month, and compile and<br>report it.<br>|\n\n\nPage 48 of 77", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000025:52:1:0", "start": 464, "end": 482, "surface": "data from the PFIs", "probe_tag": "confusion", "probe_score": 0.1565, "luna_label": 0, "luna_reason": "The project will collect and compile this data monthly."}]}, {"key": "paddy2-103", "text": "**The World Bank**\nRoads and Employment Project (P160223)\n\n\n12. Lebanon is primarily a mountainous country and has been recently witnessing more extreme weather\nwith shorter yet more severe winters and snow periods. MPWT has currently insufficient number of\nvehicles particularly for snow removal, and most the existing equipment is outdated with an average\nage of 20 years. MPWT has currently 60 wheel loaders, 25 snow blowers, and 7 salt spreaders and is\nhaving difficulty deploying them timely to all mountain roads and regions in Lebanon during extreme\nweather and snow events which can cover up to 70 percent of Lebanon national and local road\nnetworks during winter season. This results in some mountain villages and towns, and some primary\nroads and highways such as the Beirut‐Damascus Highway, being inaccessible for substantial periods\nof time.\n\n\n13. In addition to the purchase of vehicles, this component will assist MPWT revise its winter and snow\nemergency procedures to better plan, communicate, deploy, and respond to winter and snow\nemergencies. Given its strong linkages to the climate change agenda, this component could benefit at\nlater stages from additional support from disaster risk management and climate adaptation funds.\n\n\n**Project Component 3: Capacity Building and Implementation Support (US$7.5 million)**\n\n\n14. This component will finance consultancy services, and related software and IT equipment, to support\nthe following subcomponents:\n\n\n15. **Subcomponent 1.** Strengthen national road asset management (US$2 million). This subcomponent\nwill finance the creation of a road asset database for the trunk network in Lebanon, the collection of\nthe basic information for the database (such as road condition visual surveys, IRAP assessment of road\nsafety, and traffic counts on select road sections), and the revision of design and maintenance\nstandards to reflect changing climate conditions, particularly related to drainage and slope\nstabilization. This subcomponent will also finance the preparation of routine maintenance manual for\nsmall contractors, and", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000008:57:0:0", "start": 1605, "end": 1624, "surface": "road asset database", "probe_tag": "drop", "probe_score": 0.0216, "luna_label": 0, "luna_reason": null}, {"key": "sample:jdc_operational:000008:57:0:1", "start": 1725, "end": 1754, "surface": "road condition visual surveys", "probe_tag": "confusion", "probe_score": 0.5645, "luna_label": 0, "luna_reason": null}, {"key": "sample:jdc_operational:000008:57:0:2", "start": 1756, "end": 1786, "surface": "IRAP assessment of road\nsafety", "probe_tag": "confusion", "probe_score": 0.161, "luna_label": 0, "luna_reason": null}, {"key": "sample:jdc_operational:000008:57:0:3", "start": 1792, "end": 1806, "surface": "traffic counts", "probe_tag": "confusion", "probe_score": 0.3296, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-104", "text": "LG, OPM, NEMA, UCC, PPDA, and other\nsectoral agencies such as the MoES, MAAIF, JLOS, MoH, MTIC, MTWA, NIRA, UBOS; the Ministry of Gender; and\nthe working group of the CRRF for its role among refugees and RHDs. The TC will meet at least once a quarter\nto ensure timely and smooth implementation progress. The Project Coordinator will ensure inter-institutional\ncollaboration and coordination among different agencies. Ad hoc project implementation teams (PITs) will be\nestablished for the purposes of implementing specific activities of the project. The PITs, represented by key\nstakeholders from partner agencies, will be guided by the decisions of the TC. The summary of the technical\nleads and partner agencies involved in the implementation of each sub-component is presented in annex 3.\n\n**B.** **Results Monitoring and Evaluation Arrangements**\n\n\n**65.** **The project results framework will form the basis of the results M&E arrangements.** M&E of the UDAPGovNet will be embedded in the various components of the project, and TA provided through the project will\ninclude support for M&E. The arrangements for results monitoring are detailed in Section VII and will be supported\nusing the Geo-Enabled Monitoring and Supervision (GEMS) Initiative. NITA-U will collect, compile, and analyze the\nresults data and prepare M&E reports. Where surveys are required to populate baseline or progress data for\nspecific indicators, the M&E specialist on the PIU will be coordinating the implementation of such surveys and\nutilizing funds from component 4, Project Management, to procure the needed surveying services. NITA-U will\n\n\nPage 26 of 76", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000023:38:1:0", "start": 1298, "end": 1310, "surface": "results data", "probe_tag": "drop", "probe_score": 0.0119, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-105", "text": " Evaluation**\n\n\n55. **Project monitoring and verification will be undertaken by the implementing agency to ensure**\n**the project is being implemented in line with the proposed objectives and is on track to achieve**\n**expected results.** Project progress reports will be prepared by CDR, with inputs from MPWT and the\nSNRSC where needed, on a semi‐annual basis and submitted to the Bank for review and comments within\n45 days from the end of the reporting period. These reports shall include among others: (a) an update on\nthe results achieved based on the indicators and target values established in the results framework; (b)\nbreakdown of jobs created by type, location, gender, and nationality based on contractors’ and\nsupervision consultants’ reports; (c) the activities carried out throughout the reporting period under each\ncomponent; (d) key issues/constraints or risks affecting project implementation that require attention\nwith corresponding proposed measures to address them; (e) disbursement calendar for the next six\nmonths; and (f) progress achieved in the implementation of the environmental and social safeguards\ninstruments (ESMPs, RAPs, Abbreviated Resettlement Action Plans [ARAPs]). CDR will be responsible for\nproject data collection and compilation as well as the overall project monitoring and evaluation. In\naddition, an in‐depth project implementation progress assessment will be carried out at the midterm\nreview; CDR will prepare a report and make a formal presentation of the progress made during the project\nlife up to that point.\n\n\n56. **The World Bank, with potential support from other donors, will ensure continuous**\n**implementation support.** The key World Bank specialists are based in Beirut and will have regular\ninteraction with CDR and frequent field visits. This will allow the Bank to provide continuous monitoring\nand verification support far exceeding the regular one or two implementation support missions generally\nrequired for such projects. The World Bank will", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000008:32:1:0", "start": 1233, "end": 1245, "surface": "project data", "probe_tag": "drop", "probe_score": 0.0086, "luna_label": 0, "luna_reason": "Project data collection is assigned as a future project activity."}]}, {"key": "paddy2-106", "text": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n\n\n\n\n\n\n\n|Monitoring & Evaluation Plan: PDO Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Beneficiaries of social safety net programs||This indicator<br>will be<br>measured at<br>least on a<br>quarterly<br>basis during<br>missions and<br>ISRs<br>|SNSOP MIS<br>which hosts<br>beneficiary<br>registration<br>and payment<br>data<br>|The implementing<br>partner will collect<br>beneficiary data during<br>targeting and<br>registration. The<br>payment service<br>provider will document<br>payment data and<br>share with the<br>implementing partner<br>|Implementing Partner<br>|\n|Beneficiaries of social safety net<br>programs - Female||This indicator<br>will be<br>measured at<br>least on a<br>quarterly<br>basis during<br>missions and<br>ISRs<br>|SNSOP MIS<br>which hosts<br>beneficiary<br>registration<br>and payment<br>data<br>|The implementing<", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000057:55:0:0", "start": 655, "end": 671, "surface": "beneficiary data", "probe_tag": "confusion", "probe_score": 0.0877, "luna_label": 0, "luna_reason": "Data phrase appears inside a monitoring table and describes planned collection."}, {"key": "sample:jdc_operational:000057:55:0:1", "start": 765, "end": 777, "surface": "payment data", "probe_tag": "drop", "probe_score": 0.0486, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-107", "text": " project design are summarized below:\n\n\n     - _Strategic storage_ : Strategic reserves provide countries with critical lead time to secure alternative grain\nsupplies or supply routes during times of crisis. Reserves also offer psychological benefits that may prevent\nhoarding and pilferage. Moreover, historical data suggest a strong negative correlation between changes in\ngrain stocks and changes in grain prices. Not only could increasing strategic reserves reduce domestic price\nvolatility and the frequency of domestic price shocks, but it could also impact the global grain market and in\nturn mitigate international price risks. Importantly, the benefits of strategic reserves must be measured\nagainst the cost of maintaining them.\n\n\nPage 22 of 54", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000024:26:2:0", "start": 302, "end": 317, "surface": "historical data", "probe_tag": "drop", "probe_score": 0.0002, "luna_label": 1, "luna_reason": "Historical data support a stated negative correlation between grain stocks and prices."}]}, {"key": "paddy2-108", "text": "\napplicable to their interventions. In addition to providing sub-grants and sub-contracting projects to\nachieve project objectives, the IA will support communication and outreach and provide strategic\noversight and coordination vis-à-vis the respective sector interventions.\n\n51. **The IA has extensive operational experience in Lebanon, inclusive of successfully managing a multi-**\n**million US dollar portfolio and engaging with civil society and government actors** . Furthermore, the IA’s\nin-house systems and policies in provide a comprehensive framework for building effective partnerships\nwith beneficiary NGOs, while also allowing for the identification and management of programmatic,\noperational, financial, and reputational risks.\n\n**Citizen Engagement**\n\n\n52. **Project beneficiaries will be consulted regularly throughout implementation on their satisfaction,**\n**suggestions, comments, or concerns** . This will take place through the IA’s standing citizen engagement\nmechanisms, which are strong. The periodicity of the feedback generation will depend on the NGO\npartners’ capacities and systems in place to consult beneficiaries and collect their feedback, through\nquantitative or qualitative participatory data collection mechanisms (i.e. surveys, focus group discussions,\nkey informant interviews, etc.). To ensure these are sufficient for achieving minimum accountability\nstandards, the IA will undertake supplementary assessments and capacity building as needed. The project\nwill further support inclusive outreach campaigns and mid-term and end of project beneficiary satisfaction\nsurveys. Further, the IA will agree with its partners, depending on their capacities and structures, a\nfrequency and modality to disseminate the results of the grievance mechanism to the public. Data\nprotection principles will be applied by removing identifying information of beneficiaries, and results will\nbe disseminated in a thematic/topic manner. Sensitive and critical complaints will be channelled to the\nIA’s PMU for handling and to agree corrective actions with the partners.\n\n53. **The project will be closely aligned with the 3RF program level citizen engagement and outreach**", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000002:17:1:0", "start": 1578, "end": 1610, "surface": "beneficiary satisfaction\nsurveys", "probe_tag": "drop", "probe_score": 0.0428, "luna_label": 0, "luna_reason": "Project will support future beneficiary satisfaction surveys."}]}, {"key": "paddy2-109", "text": " for trade, thereby making the cost of travel cheaper.\n\n94. The cost-benefit analysis indicates that the Economic Internal Rate of Return (EIRR) for the upgrading option\nof Asphalt Concrete pavement (with 50 mm Asphalt Concrete, 200 mm of Aggregate Base Course, and 250\nmm of Granular Subbase) is 19.7 percent when a discount rate of 12 percent is used. A sensitivity analysis\nhas been carried out by increasing or decreasing the critical factors. For the scenario with a 20 percent\nincrease in construction costs, the EIRR is 16.3 percent. For the scenario with a 20 percent decrease in traffic\nvolume, the EIRR is 14 percent. However, if both scenarios are combined, the EIRR is 9.9 percent.\n\n\n95. Reduced travel time and reduced congestion is expected to lower carbon emissions. Based on current and\nfuture traffic forecasts, upgrading of the KYM road corridor is expected to reduce GHG emissions by 42,884\ntons CO2, for the 30 years of operation.\n\n\n**B. Fiduciary**\n\n\n**(i)  Financial Management**\n\n\n96. The project’s financial and other resources will be managed through the existing financial management\narrangements in UNRA as established under the Directorate of Corporate Services in the Finance/Accounts\ndepartment regarding record keeping, accounts, reporting and disbursements. The project planning and\nbudgeting process is mainstreamed into the UNRA procedures. The UNRA Board of Directors has the\nresponsibility of approval of policy, work plans and budget of the entity operations while Bank project\nbudgets are approved in liaison with the World Bank. UNRA will dedicate a project accountant to oversee\nday-to-day financial transactions and ensure proper reporting and controls are in place for the project using\nPastel Accounting System while the GoU IFMIS is used for counterpart funding. The Executive Director of\nUNRA will be the Accounting Officer assuming the overall responsibility for accounting for the project funds.\nDuring the assessment, some risks have", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000050:41:1:0", "start": 791, "end": 827, "surface": "current and\nfuture traffic forecasts", "probe_tag": "drop", "probe_score": 0.0016, "luna_label": 1, "luna_reason": null}, {"key": "sample:jdc_operational:000050:41:1:1", "start": 1764, "end": 1773, "surface": "GoU IFMIS", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-110", "text": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPage 3 of 54", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000032:5:0:0", "start": 19, "end": 52, "surface": "Lebanon Health Resilience Project", "probe_tag": "drop", "probe_score": 0.0407, "luna_label": 0, "luna_reason": "Project title, not a cited or used data resource"}]}, {"key": "paddy2-111", "text": " refuge in neighboring countries.\n\n\n**Conflict has resulted into a near collapse of the economy.** Currently, the country exhibits all the\nsigns of macroeconomic collapse. There have been sharp declines in output, and a spike in the parallel\nexchange market premium. The economy is expected to further contract by about 11 percent with both\nthe oil and non‐oil sectors expected to decrease. The fiscal deficit remains wide, although real magnitudes\nare difficult to estimate given the hyperinflation and lack of real time data. Based on the 2016/17 budget,\nthe fiscal deficit is estimated at about 14 percent of GDP. Export revenues decreased due to declining oil\nprices and lower oil production. There is an accelerated depreciation of the pound, with the SSP\ndepreciating on the parallel market from SSP 18.5 per US dollar in December 2015 to reach SSP 110 per\nUS dollar in March, 2017. This follows the move to a managed floating exchange rate from a fixed\nexchange rate.\n\n\n**Drought that was experienced in parts of the country over the last cropping season, acting in**\n**concert with several other factors** <sup>**28**</sup> [^28: These include: (i) the current drought in the Horn of Africa, which has reduced overall output in primary exporters Uganda and\nSudan and limited the food imports that South Sudan can viably access; (ii) high food prices mainly driven by depreciation of the\nlocal currency and a very high inflation rate; (iii) declines in crop production from already low levels due to insecurity and\ndisplacement of farmers; and (iv) destabilization of markets due to restrictions to movement in commodity‐supply corridors.] **, has led to extreme scarcity of food and famine in some parts of the**\n**country.** Preliminary findings from the FAO/WFP CFSAM show that partly due to the drought, overall food\nproduction for 2016 (the last harvests of which came in January", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000038:69:1:0", "start": 512, "end": 526, "surface": "real time data", "probe_tag": "drop", "probe_score": 0.0008, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-112", "text": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\nprotective support to HHs and investment in resilience building community assets will help sustain livelihoods, strengthen\nresilience, and prevent the most vulnerable from falling into destitution or being forcibly displaced. It will also directly\nsupport the Government’s Community Empowerment and Socioeconomic Development Strategy for Refugee Hosting\nAreas in South Sudan, with cash transfers promoting section 4.6 of the strategy on creation of livelihood and income\ngenerating opportunities given the lack of employment prospects in refugee-hosting environments.\n\n37. **In the absence of an enabling environment for widescale mobile payment systems, beneficiaries will receive**\n**physical cash at the time of payment, except for Juba where mobile money payment will be piloted.** A financial service\nprovider (i.e., paying agent), which will be competitively selected by the MAFS, will deliver cash to beneficiaries. The\nMAFS will provide the recipient list and amount of money to the financial service provider, and the list of beneficiaries\nwill be generated from the MIS. The MIS will capture beneficiaries' biometric data, which will be used to ensure that only\nthe eligible individuals will receive the cash transfer. The financial service provider pays beneficiaries verifying them\nbiometrically. In addition, implementing partners (i.e., UNOPS and NGOs contracted by MAFS to implement the project)\nand community leaders will be present and monitor the transfer process to ensure transparency and accountability.\nBased on the findings of a recently concluded analytical work, the project will pilot the use of mobile money payments\nin Juba. Mobile money payments would help strengthen transparency and safety and were assessed to be feasible in\nlarge urban center like Juba under the SSSNP. This pilot would inform potential future scale up of mobile money payments\nin urban areas.\n\n**Sub-component 1.1: Cash for Labor-Intensive Public Works and Complementary Social Measures** *", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000057:23:0:0", "start": 1169, "end": 1172, "surface": "MIS", "probe_tag": "confusion", "probe_score": 0.1458, "luna_label": 1, "luna_reason": null}, {"key": "sample:jdc_operational:000057:23:0:1", "start": 1178, "end": 1181, "surface": "MIS", "probe_tag": "drop", "probe_score": 0.0462, "luna_label": 1, "luna_reason": null}, {"key": "sample:jdc_operational:000057:23:0:2", "start": 1210, "end": 1224, "surface": "biometric data", "probe_tag": "confusion", "probe_score": 0.2475, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-113", "text": ">sources to support the vaccination sites.<br> <br>Additional mobile vaccination units need<br>to be deployed to vaccinate hard-to-<br>reach populations.<br> <br>Given the success of the large-scale<br>marathons being conducted by the<br>MoPH, additional marathons should be<br>conducted to improve vaccine uptake.<br> <br>|\n|Training and<br>supervision<br>| <br>Vaccination teams were trained on the<br>vaccination process.<br> <br>|<br> <br>With the opening of new vaccination<br>sites with new vaccination teams,<br>reminder trainings may be required. In<br>preparation for vaccination in schools,<br>vaccination teams should also be trained<br>on vaccination in children/ adolescents.<br> <br>|\n|Monitoring and<br>evaluation<br>| <br>Multiple channels for grievance reporting<br>exist (hotline, and the MOPH website) for<br>vaccination.<br> <br>IMPACT platform is used to monitor<br>vaccination data<br> <br>|<br> <br>A Third-Party Monitoring Agency (TPMA)<br>was contracted to verify theGoL’s<br>compliance of the vaccination<br>deployment with the NDVP, WHO<br>standards and WB requirements<br>reflected in the legal agreements,<br>Environmental and Social safeguards and<br>POM.<br> <br>A technical auditor will be hired to<br>monitor the deployment of World Bank-<br>financed vaccines under the proposed<br>operation.<br> <br>|", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000000:19:1:0", "start": 893, "end": 909, "surface": "vaccination data", "probe_tag": "drop", "probe_score": 0.008, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-114", "text": "OPRC Operational Procurement Review Committee\nPAD Project Appraisal Document\nPDO Project Development Objective\nPFS Project Financial Statement(s)\nPIU Project Implementation Unit\nPLM Person with Limited Mobility\nPIM Project Implementation Manual\nPPP Public-Private Partnership\nPPSD Project Procurement Strategy Development\nQCBS Quality- and Cost-Based Selection\nRAP Resettlement Action Plan\nROW Right-of-Way\nRPA Regional Procurement Adviser\nRPTA Railways and Public Transport Authority\nSOE Statement of Expenditure\nSPS Stated Preference Survey(s)\nSTEP Systematic Tracking of Exchanges in Procurement\nUIFR Unaudited Interim Financial Report\nUN United Nations\nUTDP Urban Transport Development Project\nVAT Value Added Tax\nWA Withdrawal Application", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000022:3:0:0", "start": 514, "end": 542, "surface": "SPS Stated Preference Survey", "probe_tag": "drop", "probe_score": 0.0389, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-115", "text": "**S R I** LANKA: **PUTTALAM HOUSING PROJECT**\n**Annex** **1:** **Background and Project Design Framework**\n\n\n**Background**\n\n\nThe District o f Puttalam in North West Sri Lanka i s now home to many refugees displaced from the North\nin 1990. According to the UNHCR supervised census o f IDPs in Puttalam conducted in April 2006,\n63,145 persons or 15,480 families lived in 141 refugee camps. 41% o f the Puttalam IDPs were children\nunder the age o f 18. 72% o f the IDPs originate from Mannar; 14% come from Jafha and 10% from\nMullaitivu. The rest come from other districts in the North. The S A carried out as part o f project\npreparation indicated that 62% of the adult population worked as seasonal day labor in the informal\n\nsector. About 18% o f those surveyed in the UNHCR exercise reported that they had n o schooling while\n23% had a primary school education alone. Just 8% had completed their high school education. The IDPs\nare located in four divisions in the Puttalam district: Kalpitiya (55%), Puttalam (33%), Mundel (8%) and\nVanathavillu (3%). 96% o f Puttalam IDPs (14,928 families) indicated that they wished to remain and\nintegrate in Puttalam, citing security concerns as the major obstacle to return to their original homes.26\n74% o f the IDP households had in fact bought land in Puttalam demonstrating a resolve to remain there.\n\n\nMost refugee camps lack basic services including access to safe drinking water, toilet facilities, proper\ndrainage and garbage disposal. The UNHCR survey indicated that only 40% o f the IDP population had\nprivate permanent toilets. Since the provision", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:refugee_pads:000023:21:0:0", "start": 257, "end": 301, "surface": "UNHCR supervised census o f IDPs in Puttalam", "probe_tag": "keep", "probe_score": 0.988, "luna_label": 1, "luna_reason": null}, {"key": "sample:refugee_pads:000023:21:0:1", "start": 1489, "end": 1501, "surface": "UNHCR survey", "probe_tag": "keep", "probe_score": 0.9949, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-116", "text": " 50<br>74<br>87|\n|Dusti|47|25,507; 48|2,112; 50|100|82|\n\n\n28. Construction/rehabilitation of school sanitation facilities will be accompanied by a school-WASH\neducational program further described below to ensure that facilities are well maintained, and pupils are\nencouraged to adopt improved hygienic behaviors. A review and updating of standard WASH facility\ndesigns for schools in coordination with the Design Institute, MoES, and in collaboration with UNICEF will\nbe supported under this subcomponent. Design options should allow for different solutions and align with\ncriteria for basic service under the SDGs (sex separation, privacy, allow for accessibility of disabled\nstudents, and hygiene room for girls). Similarly, design for WASH facilities for rural healthcare centers will\nbe reviewed with the MoHSP to ensure compliance with national standards, particularly on inclusion\naspects. Design of all WASH facilities will take into account climate resilience considerations and aim for\nthe use of optimal decentralized solutions for wastewater collection, treatment, and disposal/reuse.\n\n\n55 JMP (2018) estimates for rural areas illustrate that 73 percent of school-age population has access to basic drinking water,\nwhile access to basic sanitation is only 38 percent and access to basic hygiene even lower at only 20 percent.\n\n\nPage 79 of 89\n``", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000162:82:5:0", "start": 1102, "end": 1138, "surface": "JMP (2018) estimates for rural areas", "probe_tag": "keep", "probe_score": 0.9453, "luna_label": 1, "luna_reason": "JMP 2018 estimates provide attributed rural WASH access findings."}]}, {"key": "paddy2-117", "text": "16\n\n\naddressed the Donors Roundtable and committed to increase Government resources to education to\nover 25% of the budget and noted that the government viewed education as the main source of future\ngrowth in Djibouti.\n\n\n**5. Value added of Bank support in this project**\n\nIDA has been supporting the national consensus building process through the National Education\nForum. The proposed project will help demonstrate that a consensus building approach that involves\n\nall elements of civil society is effective and produces results. In addition the use of an APL\ndemonstrates the long-term commitment by IDA to assist the Government in its strategic goal of\nreaching full enrollment in basic education. It is also hoped that the use of the IDA credit will further\ndecrease the construction unit cost (as IDA is supporting the use of local construction materials which\nshould be cheaper), help develop more cost-effective classroom designs, and provide the environment\nwith a more efficient procurement process.\n\n\n**E. SUMMARY PROJECT ANALYSIS** (Detailed assessments are in the project file, see Annex 8)\n\n\n**1. Economic (see Annex 4)**\n\n\nOther (specify) NPV=US$ million; ERR = ** % (see Annex 4)\n\n\n_** ERR = Over 11% based on system efficiency gains alone without allowing for development_\n_benefits, public goods nature of education and poverty reduction benefits._\n\n\nDjibouti's main resource base is its population and in order to achieve sustained development, the\ncountry needs to improve the quality of its human resource base. Quality starts with improved basic\neducation and school enrollments. In addition, the issue of equity arises. According to the household\nexpenditure survey data, in urban areas, the net enrollment rate (NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000175:19:0:0", "start": 1661, "end": 1694, "surface": "household\nexpenditure survey data", "probe_tag": "keep", "probe_score": 0.944, "luna_label": 1, "luna_reason": "Survey data supports a concrete enrollment inequality finding."}]}, {"key": "paddy2-118", "text": " may affect the disease burden in the future. According to Jordan’s national\ncancer statistics, Syrian refugees presenting with cancer at health facilities rose from 134 in 2011\nto 169 in the first quarter of 2013, representing a 14 percent increase in Jordan’s total cancer\ndisease burden. Similarly, morbidity data from the MOH show a rise in selected communicable\ndiseases. For example, TB case notification increased from 5/100,000 in 2009 among Jordanians\nto 13/100,000 among Syrian refugees in 2013. While no measles cases have been reported in\nJordan since 2009, MOH data show that 18 Jordanians and 23 Syrians have been diagnosed with\nthe disease in 2013. Polio, which had been eliminated since 1999 in Jordan, was also detected in\ntwo cases in 2013. Demand for services by refugees at MOH facilities has increased\nsignificantly. MOH data show that the number of outpatient visits to MOH primary health care\ncenters (PHCCs) by Syrian refugees increased from 68 in January 2012 to 15,975 in March\n2013. Similarly and during the same period, Syrian refugees attending MOH hospitals increased\nfrom 300 to 10,330; this was associated with a sharp increase in the number of surgeries\nperformed at these hospitals going from 105 to 622 surgeries\n\n\n12. With the higher demand for health services and the GOJ’s policy to provide refugees with\naccess to the country’s health care services, the health sector is facing significant financial\npressures and shortages, particularly in drugs and vaccines, as these are being depleted at a faster\nrate. The response of health facilities has been to run down their emergency stocks. Between\n2011 and 2012 drugs procured by the MOH increased by 15 percent at an additional cost of $14\nmillion (18 percent increase). And between 2013 and 2014, drug costs are expected to increase\nby 23 percent at an additional cost of around US$16 million. Financing some of the immediate\n\n\n3 The team also investigated the impact on the education sector but, for", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000064:11:1:0", "start": 68, "end": 94, "surface": "national\ncancer statistics", "probe_tag": "keep", "probe_score": 0.9746, "luna_label": 1, "luna_reason": "National cancer statistics support concrete reported increases among Syrian refugees."}, {"key": "refugee_pads:000064:11:1:1", "start": 302, "end": 329, "surface": "morbidity data from the MOH", "probe_tag": "keep", "probe_score": 0.9249, "luna_label": 1, "luna_reason": "MOH morbidity data support a reported rise in communicable diseases."}]}, {"key": "paddy2-119", "text": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\ndegree of autonomy. Around 47 percent of the Lebanese population have health insurance coverage;\nand 53 percent who lack any formal coverage are covered by the MoPH, which serves as an “insurer of\nlast resort.” This means a strong role for the ministry, not only in preventive care, public health\nleadership, and regulation, but also in curative care. To provide hospital coverage to about 250,000\ncases per year, the MoPH contracts 26 public and 105 private hospitals. Individual patient copayment to\nthe hospital constitutes 5 percent (public hospital) or 15 percent (private hospital) of the hospitalization\ncosts, and the MoPH directly reimburses the hospital for the 85–95 percent difference.\n\n10. **Despite the considerable resilience of Lebanon’s health system, the health sector indicators**\n**are regressing since the start of the Syrian crisis** . The gains that Lebanon made in meeting the\nMillennium Development Goals (MDGs) before the Syrian crisis are rapidly declining. The latest MoPH\nhospital data show significant setbacks in neonatal and maternal mortality indicators (this excludes\ndeliveries outside the hospitals). As of 2017, the data indicate that the neonatal mortality rate has\nincreased from 3.4 per 10,000 in 2012 to 4.9 per 10,000, with the rate among displaced Syrians (7 per\n10,000) almost double that among Lebanese (3.7 per 10,000). Similarly, the maternal mortality ratio\nincreased from 12.7 per 100,000 in 2012 to 21.3 per 100,000, with the rate among displaced Syrians\n(30.4 per 100,000) double that among Lebanese (15.8 per 100,000). <sup>5</sup>\n\n11. **Lebanon also faces epidemiological risks, the reemergence of some diseases that had been*", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000108:14:0:0", "start": 1061, "end": 1079, "surface": "MoPH\nhospital data", "probe_tag": "keep", "probe_score": 0.9374, "luna_label": 1, "luna_reason": "MoPH hospital data support reported neonatal and maternal mortality findings."}]}, {"key": "paddy2-120", "text": "**The World Bank**\nDjibouti Integrated Slum Upgrading Project (P162901)\n\n\n**<mark>I.</mark>** **<mark>STRATEGIC CONTEXT</mark>**\n\n\n**A. Country Context**\n\n\n1. **Djibouti is a small, strategically located lower-middle-income country in the Horn of Africa with an**\n**estimated population nearing one million inhabitants.** Located at the southern entrance to the Red Sea, the\ncountry is adjacent to the Straits of Mandeb and the Suez-Aden waterway, through which 20 percent of\nglobal commerce transits. It hosts several military bases <sup>1</sup> [^1: Countries that have military bases in Djibouti include: China, France, Germany, Italy, Japan, USA, Saudi Arabia, and Spain.] and has become the primary sea-access route for\nits large landlocked neighbor Ethiopia (population 102 million in 2016), whose imports and exports account\nfor more than 80 percent of Djibouti’s port activities. Djibouti draws significant rents from military bases,\nwhich now account for more than 20 percent of total government revenues. Its economy has been expanding\nat a remarkable pace, estimated to have registered 6.7 percent annual increase in 2017 fueled by debtfinanced public investments in port modernization and transport, particularly the railroad to Ethiopia, the\nconstruction of several new ports, and a water pipeline from Ethiopia. The IMF estimates that the GDP is\nexpected to grow 7-10 percent annually in the medium term, but external debt has also accumulated very\nrapidly, standing at 85 percent of GDP in 2016, up from less than 50 percent in 2014.\n\n\n2. **Despite significant investments and remarkable economic growth, Djibouti ranks very low on**\n**human development**, registering at 172 out of 188 countries on the human development index in 2017\n(UNDP). Weak governance and insufficiently inclusive social and economic development have impeded the\nimprovement of social outcomes. In 2017, an estimated 35", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000015:11:0:0", "start": 1719, "end": 1742, "surface": "human development index", "probe_tag": "keep", "probe_score": 0.9018, "luna_label": 1, "luna_reason": "UNDP’s index supports the stated 172-of-188 human development ranking."}]}, {"key": "paddy2-121", "text": " benefiting from activities under component 2,<br>including capacity-building, matching grant, credit guarantee scheme and graduation programming (this<br>counts HH beneficiaries x 4, being the average HH size in the refugee camps). The data is then disaggregated<br>by gender and by status (refugee/host community).|\n|Frequency|Quarterly|\n|Data source|Project MIS|\n|Methodology for<br>Data Collection|Monitoring project implementation, MIS database. Data collected by BRD, MINEMA and BDF.|\n|Responsibility for<br>Data Collection|MINEMA, BRD, BDF|\n|**Improved environmental management in the target areas**|**Improved environmental management in the target areas**|\n|**People benefitting from enhanced resilience of terrestrial and aquatic systems (Number of people)**|**People benefitting from enhanced resilience of terrestrial and aquatic systems (Number of people)**|\n|Description|Quantitative indicator counting number of beneficiaries in the catchment area where environmental<br>management activities under component 3 have been implemented. Data is disaggregated by gender,<br>youth (16-30 years, in line with GoR guidelines) and status (refugee/host community member). The youth<br>target of 26% is based on the youth population in the five RHDs 2022 census). The beneficiary number<br>includes the camp-based refugee population and people living in the villages surrounding the five camps.|\n|Frequency|Quarterly|\n|Data source|Project MIS|\n|Methodology for<br>Data Collection|Monitoring project implementation. MIS database with population statistics for project sites cross-<br>tabulated with hectarage benefiting from improved terrestrial and aquatic systems.|\n|Responsibility for<br>Data Collection|MINEMA|\n\n\n\n*", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000188:45:1:0", "start": 437, "end": 449, "surface": "MIS database", "probe_tag": "confusion", "probe_score": 0.8278, "luna_label": 0, "luna_reason": "The sentence describes project data collection and monitoring production."}, {"key": "refugee_pads:000188:45:1:1", "start": 1245, "end": 1266, "surface": "five RHDs 2022 census", "probe_tag": "confusion", "probe_score": 0.8478, "luna_label": 1, "luna_reason": "2022 census data informs the 26% youth beneficiary target."}]}, {"key": "paddy2-122", "text": ". The Recipient will prepare a Security Management Plan (SMP) by project effectiveness and a\nsummary will be disclosed in-country and on the World Bank’s external website.\n\n110. **The risk associated with institutional capacity on environmental and social management is**\n**considered Substantial** because the Recipient has little experience or capacity to manage some of the\nsocial risks identified in the ESF, and significant efforts will be required to help build the Recipient’s\ncapacity with the expanded social and environmental remit of the ESF. The Recipient also prepared,\nconsulted upon, and approved an ESCP <sup>37</sup> [^37: _[https://documents1.worldbank.org/curated/en/099115102012230317/pdf/P17449507045c20b70a0b20cbd9ac3ae22d.pdf](https://documents1.worldbank.org/curated/en/099115102012230317/pdf/P17449507045c20b70a0b20cbd9ac3ae22d.pdf)_], which details the material measures and actions to be\nundertaken by the Recipient during project implementation to ensure compliance with the provisions of\nthe ESF as well as the timeline and the responsible party.\n\n111. **The project has been screened for SEA/SH risks using the World Bank SEA/SH risk screening tool**\n**for projects with civil work.** The assessment concluded that the SEA/SH risks are Substantial. Drivers of\nrisk in the context include high rates of child marriage and female circumcision, general social acceptability\nof GBV, conflict, high risks of human trafficking, and lack of legislation on domestic violence and sexual\nharassment. GBV is highly prevalent, and it is estimated that 28.6 percent of women nationwide have\nexperienced physical or sexual violence by an intimate partner at some point in their lives. <sup>38</sup> [^38: Chad, Demographic Health Survey (DHS), 2014–15 (in French).] SEA/SH\nrequirements have been reflected in the ESCP, in contracts, and in the contractor’s ESCP", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000193:46:1:0", "start": 1727, "end": 1752, "surface": "Demographic Health Survey", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 1, "luna_reason": "Cited survey supports the reported national intimate-partner violence prevalence."}]}, {"key": "paddy2-123", "text": "sup>recently</sup> <sup>come</sup> <sup>under Government control.</sup>\n\n\n\n**2.** **Main sector** issues **and** <sup>**Government strategy:**</sup>\n\n\n\n_Sector Issues._\n_Poverty in Sierra Leone._ Sierra <sup>Leone has</sup> <sup>the lowest</sup> <sup>Human Development Index</sup> <sup>**in**</sup> <sup>the world</sup>\n\n\n\nand has a GNP per capita <sup>of only US$130</sup> <sup>compared</sup> <sup>to the average</sup> <sup>for Sub-Saharan</sup> <sup>Africa</sup> <sup>of $470.</sup>\n\n\n\nOver 82% of the population <sup>currently</sup> <sup>lives below</sup> <sup>the poverty line and life expectancy is only</sup> <sup>38 years.</sup>\n\n\n\nFertility, infant and child <sup>mortality are</sup> <sup>high</sup> <sup>and over</sup> <sup>a third</sup> <sup>of children and</sup> <sup>a fourth</sup> <sup>of adults</sup> <sup>are</sup>\n\n\n\nmalnourished. The pnmary <sup>school enrollment</s", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000138:7:1:0", "start": 251, "end": 274, "surface": "Human Development Index", "probe_tag": "confusion", "probe_score": 0.8186, "luna_label": 1, "luna_reason": "Index ranking provides evidence of Sierra Leone’s development status."}]}, {"key": "paddy2-124", "text": " rate in Afghanistan has increased significantly: from 38 percent in 2011/12 to 55 percent in**\n**2016/17.** It is expected to remain high in the medium‐term, driven by weak labor demand (despite an increasing\nlabor force) and security‐related constraints on service delivery. Living standards are further threatened by the\nworsening drought conditions and displacement (more than 1.7 million Afghans are internally displaced, and more\nthan 2 million have been returning to Afghanistan—mostly from Pakistan and Iran—since 2015).\n\n\n4. **Stronger growth is predicated on improvements in security, political stability, steady progress with reform, and**\n**sustained aid.** Growth could also be enhanced by mobilizing investment in extractives, energy and connectivity,\nbuilding and harnessing the skills of Afghanistan’s youth and women, and taking steps to realize the job creation\npotential of agriculture and agribusinesses.\n\n**B. Sectoral and Institutional Context**\n\n5. **About half of the returnees, regardless of when or from where they returned, have settled in urban areas which**\n**has put enormous pressure on Afghanistan’s inundated service delivery systems, as well as on the economic**\n**and physical infrastructure of the communities that host these groups.** About two‐thirds of the Afghan\npopulation has no access to the electricity grid. While electrification rates have improved over the past decade,\nparticularly in urban areas, barriers to access remain high. The poor market infrastructure constrains the enabling\nenvironment, essential for job creation and economic wellbeing, particularly among the urban population.\n\n6. **Afghanistan measures poorly in both the Logistics Performance Index (150th in the World) and the Doing**\n**Business Trading Across Borders indicator (177th in the world).** Inadequate infrastructure has also been a\nconstant complaint of businesses voiced in many recent surveys <sup>1</s", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000123:15:1:0", "start": 1684, "end": 1711, "surface": "Logistics Performance Index", "probe_tag": "confusion", "probe_score": 0.8053, "luna_label": 1, "luna_reason": "Named index provides Afghanistan’s cited global ranking."}, {"key": "refugee_pads:000123:15:1:1", "start": 1751, "end": 1792, "surface": "Business Trading Across Borders indicator", "probe_tag": "confusion", "probe_score": 0.6904, "luna_label": 1, "luna_reason": "Named indicator cited with Afghanistan's global ranking."}]}, {"key": "paddy2-125", "text": " Under the PBCs, the World Bank\nwill finance particular expenditures which are a part of the project’s budget of eligible activities. These\nexpenditures are clearly identifiable in GoU integrated financial management information system and are referred\nto as Eligible Expenditure Programs and include expenditures under Component 1. Following a sector-support\nprogram principle, the World Bank funds earned through PBCs may not be separately tracked and the World Bank\nwill accommodate withdrawal applications from the financing as long as the overall expenditures eligible under\nthe EEPs are more than or equal to the amount to be withdrawn from the World Bank, and fiduciary control and\noversight of the funding is acceptable to the World Bank. Total EEPs will be annually tracked through external\naudits and aggregated for the life of project. The expenditure mechanism satisfies Bank policy and in particular\nthe three pillars in OP 6.00, namely, (a) the expenditures are productive and necessary for the success of the\nsector program; (b) they contribute to solutions within a fiscally sustainable framework; and (c) acceptable\noversight arrangements are in place.\n\n\n99. **Eligible Expenditure Program** for the PBC component will include the following:\n(i) Vote (500-800) LGs School Capitation Grants;\n(ii) Vote (500-800) LG School Inspection; and\n(iii) Vote (500-800) Staff Salaries for Secondary Education.\n\n100. **Audits.** The Ministry has an active Internal Audit department with practical experience on the previous\nand existing IDA projects. The internal audit unit is guided by an internal audit manual issued by the GoU that\nemphasizes a risk-based approach and value for money audits, policy and procedures, compliance reviews, and\nspecial investigations. The department needs to improve on submission of internal audit reports. External auditing\nis primarily a responsibility of the Auditor General for all government programs and projects. The audit may be\nsubcontracted to private auditors, with the final", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000060:38:1:0", "start": 181, "end": 235, "surface": "GoU integrated financial management information system", "probe_tag": "confusion", "probe_score": 0.716, "luna_label": 0, "luna_reason": "Financial management system used for routine expenditure tracking and project bookkeeping."}]}, {"key": "paddy2-126", "text": "**The World Bank**\nMunicipal Services Improvement Project in Refugee Affected Areas (P169996)\n\n\n**ANNEX 2: Detailed Project Description**\n\n1. **Background.** The Project aims to improve host and refugee communities access to safely managed water supply,\nsanitation and solid waste services in targeted municipalities affected by the influx of Syrians Under Temporary\nProtection in Turkey. The project focuses on five municipalities or provinces (i.e. Adana, Kahramanmaras, Kayseri,\nKonya and Osmaniye) out of the ten most impacted by the refugee influx in Turkey as identified in the EU Needs\nAssessment. The selection of the five municipalities to be supported through the current project was based on not\njust the identified needs, but also eligibility for World Bank financing of sub-projects that do not trigger _World Bank_\n_OP 7.50 Projects on International Waterways_ . Sub-projects triggering this policy are to be supported by other\ndevelopment partners, including AFD.\n\n2. **Target Group and Final Beneficiaries.** The final beneficiaries comprise the populations in the affected\nmunicipalities, including the refugees and host populations. Only a small share (less than 10 percent) of the refugee\npopulation resides in camps, while the majority live outside camps, mostly in urban areas. There are two\ndesignated camps in the targeted provinces: Kahramanmaras' Merkez Container Camp which hosts about 14,811\nrefugees, and Adana Sancam Container Camp which hosts about 26,700 refugees. The primary project\nbeneficiaries include both the refugees and host communities in the five municipalities of Adana, Kahramanmaraş,\nOsmaniye, Kayseri and Konya targeted under this project and is estimated to be more than 3.3 million.\nApproximately 301,890 refugees (or 9 percent of the total beneficiaries) and 3,021,000 of the host population will\nbe direct beneficiaries of the environmental infrastructure investments under Component 1", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000125:59:0:0", "start": 584, "end": 603, "surface": "EU Needs\nAssessment", "probe_tag": "confusion", "probe_score": 0.3372, "luna_label": 1, "luna_reason": "Named assessment identifies municipalities most impacted by refugee influx."}]}, {"key": "paddy2-127", "text": " a reduction in the poverty rate (headcount poverty)\nand reduction of the poverty gap – as well as to reinforce systems that should allow for such reduction to continue after\nthe project. Currently, a substantial share of the population in Djibouti remains poor (21.1 percent poverty rate in 2017).\nAs for human capital, Djibouti has one of the lowest rankings in MENA and ranks 172 among 188 countries in the HDI.\nNotable challenges include some of the highest rates of stunting and wasting for children under five. Although poverty\nreduction (though hard to attribute without an expensive impact evaluation) is expected to be the main effect of the\nprogram’s expansion, as a second order effect, the project may have an impact on overall human development outcomes\n(although limited given the scope of the proposed conditionalities).\n\n63. **Simulating the impact of PNSF expansion on headcount poverty in Djibouti** . The proposed project aims to expand\nPNSF to cover 5,000 of the poorest and most vulnerable households in Djibouti, providing critical consumption smoothing\nto selected beneficiaries. Based on the latest plans for the expansion of the program and using the latest available\nhousehold survey in Djibouti (Enquête Djiboutienne Auprès de Ménages, EDAM 4), this economic analysis aims to\ncalculate the impact of the proposed cash transfer program on head count poverty. The simulation approximates a US$56\nper month transfer to 5,000 households. The total allocation of the program is simulated through a three-step process.\nFirst, 5,000 households are selected randomly in regions of the interior based on the percentage of poor population\n(excluding Djibouti Ville). Second, the benefits are distributed only to households in these areas. Finally, households are\nrandomly assigned to receive benefits so that their consumption levels are increased, until the target of 5,000 households\nis reached.\n\n\nPage 21 of 44", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000063:25:1:0", "start": 1193, "end": 1221, "surface": "household survey in Djibouti", "probe_tag": "confusion", "probe_score": 0.5144, "luna_label": 1, "luna_reason": "Used with EDAM 4 data to simulate the cash transfer’s poverty impact."}, {"key": "refugee_pads:000063:25:1:1", "start": 1223, "end": 1261, "surface": "Enquête Djiboutienne Auprès de Ménages", "probe_tag": "confusion", "probe_score": 0.8685, "luna_label": 1, "luna_reason": "Named household survey used to simulate cash transfer impacts on poverty"}]}, {"key": "paddy2-128", "text": "Annex 1\nPage 3 **of** 3\n\n\n**Key Performance**\n**Hierarchy of Objectives** **Indicators** **Monitoring &** **Critical Assumptions**\n**Evaluation**\n**Project Components / Sub-** **Inputs: (budget for each** **Project reports:** **(from Components to**\n**components:** **component)** **Outputs)**\n\n\nImprove Access: provision of US$5.8 million MOE monitoring Capacity within the\nclassrooms. Number of schools reports construction sector to handle\nconstructed per year; the volume of school\nimproved design and construction.\nefficiency.\nCreate Conditions for Quality US$1.1 million School surveys; student Good textbook distribution;\nImprovement: access to Number of textbooks per learning achievement management training\neducational materials; student; autonomous school reports (MOE effectiveness; Government\nimproved school management; salaries paid on monitoring reports). commitment to paying\nmanagement; teacher a timely basis teacher salaries.\nmotivation.\n\n\nImprove Government's US$4.1 million Project monitoring Purpose and integrity\nCapacity to Manage Sector: Project effectively reports; study reports. maintained within project\ncapacity building within the implemented and management; stakeholder\nMOE and its related services; management improved; participation in pilot studies.\npilot studies. reports with implementable\nresults.\n\n\n**Annexe 1 Attachment: Program and Project Monitorin** **Tar** **ets**\n**_Year_** _2001-02 2002-03_ **_2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10_**\nPrimary Enrollment Boys 19,125 21,506 24,300 26,627 29,867 31,696 34,457 37,217 40,129\nPrimary Enrollment Girls 14,875 17,994 20,", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:refugee_pads:000049:31:0:0", "start": 577, "end": 591, "surface": "School surveys", "probe_tag": "confusion", "probe_score": 0.0853, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-129", "text": "decentralized \"partnership\" approach to governance that involves line ministnes, NGOs, CBOs, <sup>and</sup> <sup>civil</sup>\nsociety. NCRRR/NaCSA has been supported by the African Development Bank, UNDP, DflD, and IDA.\nIt has provided assistance for more than 500,000 displaced persons, shelter rehabilitation, vocational\ntraining, trauma healing, and micro-finance programs. It has financed 275 community-based sub-projects\nin the areas of health, education, water and sanitation, agriculture and capacity building. These <sup>tasks</sup>\nhave been carried out with considerable support from the 260 NGOs registered in Sierra Leone, of which\n68 are international. These NGOs have been instrumental in ensuring service delivery to remote <sup>areas</sup>\nwhere public services were absent.\n\n\n**3.** **Sector** **issues** **to be** **addressed** **by the** **project and strategic choices:**\n\n**Poverty in a Post-Conflict** **Environment.** Section 2 above outlines the principal characteristics\nof poverty in Sierra Leone and the condition of the country at the close of the civil war. <sup>Access</sup> <sup>of the</sup>\npoor majority to food, shelter, employment opportunities and social services are among the <sup>principal</sup>\n\n\n\nconstraints to post-conflict reconstruction, economic recovery and poverty reduction. District recovery\nassessments reveal that over 340,000 houses were destroyed dunng the war and only 10,000 have been\nrebuilt so far. Government is particularly concerned with the shelter needs of returnees, IDPs <sup>and</sup>\n\n\n\ngovernment employees such as health workers and", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000117:9:0:0", "start": 1323, "end": 1352, "surface": "District recovery\nassessments", "probe_tag": "confusion", "probe_score": 0.2697, "luna_label": 1, "luna_reason": "Assessments provide a concrete finding on wartime housing destruction."}]}, {"key": "paddy2-130", "text": "23. Jordanian economy is disaggregated into 10 sectors to reflect the major produced and traded\ncommodities, mainly grains and crops, meat and livestock, extraction industries, processed food, textile\nand apparel, light manufacturing, heavy manufacturing, utilities and construction, transports and\ncommunication, and other service sectors. Skills in the labor market are presented as managers and\nlegislators, service providers and sales personnel, professionals, clerks, or elementary occupations.\n\n\n**_Cost-Benefit Analysis_**\n\n\n24. The baseline reflects the Jordanian economy in 2015 following the World Bank statistics and\nmedium-term growth programs without the PforR reforms. In the baseline, the standard GTAP dataset\nand parameters are fine-tuned based on the most recent national statistics to reflect the current economic\nframework. The simulation is defined as expected medium-term impacts of implementing three sets of\nreform, mainly work permits, business environment and trade reform, and investment promotion.\n\n\n25. The simulation results compared to the 2015 baseline shows the net benefits from trade reforms\nand other enabling business environment that are proposed by the DLIs.\n\n\n**Box 4.1. GTAP-CGE Model for Jordan: Reform Scenarios**\n\n\nThe cumulative effect of all of these actions is an additional 6 percent increase in real GDP by 2026, that is, a 0.6\npercent additional annual increase in GDP for the next 10 years.\nThis is in addition to an increase in investment by 25 percent (above the baseline), thus resulting in an accelerated\ngrowth path.\nWith regard to balance of payment, the increase in exports to the EU will more than double (107 percent increase).\nEstimated welfare increase (in equivalent variation) is around US$2.5 billion (8 percent increase compared to the\nbaseline in 2015).\nThe overall net benefits from the proposed reforms (cost US$300 million) are estimated to help the GoJ to reach the\n<mark>DLI targets. The results are likely", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000137:64:0:0", "start": 713, "end": 725, "surface": "GTAP dataset", "probe_tag": "confusion", "probe_score": 0.8768, "luna_label": 1, "luna_reason": "GTAP dataset is used as a model input for reform impact simulations."}, {"key": "refugee_pads:000137:64:0:1", "start": 781, "end": 800, "surface": "national statistics", "probe_tag": "confusion", "probe_score": 0.819, "luna_label": 1, "luna_reason": "Existing national statistics inform fine-tuning of the GTAP simulation parameters."}]}, {"key": "paddy2-131", "text": "**Annex 5: Economic Analysis**\n**Burundi: Social Safety Net System Project**\n\n**Context**\n\n1. The objectives of the proposed Project are to provide regular cash transfers to extreme poor\nand vulnerable households with children in selected areas while strengthening the delivery\nmechanisms for the development of a basic social safety net system. The project will achieve these\nobjectives through (i) supporting the development and implementation of a social safety net\nprogram based on cash transfers and (ii) supporting the development of the delivery mechanisms\nfor a basic social safety net through a targeting process with a beneficiary database, a management\ninformation system with a payment module, and a basic monitoring and evaluation system. The\nProject stands to have an impact on poverty through the direct support provided to the poorest\nfamilies, but also a broader impact through the targeting and coordination of other safety net\nprograms.\n\n2. The proposed Project design is based on the findings of the social safety net review in\nBurundi (2014), which identified the main challenge as needing to both address recurrent\nhumanitarian, emergency interventions and deal with the structural vulnerability of the country’s\npoorest members. The assessment also underscored the need for stronger targeting within\nprograms and for better monitoring and evaluation, to enable the Government and its partners to\nassess the contribution of the interventions to poverty reduction and impacts on human\ndevelopment outcomes. In light of this, the proposed project focuses on two key public goods.\nFirst, developing a mechanism to effectively support Burundi’s chronic poor and help strengthen\ntheir resilience in a context of multiple and recurrent crises and their investments in human capital.\nSecond, putting in place the key delivery mechanisms for targeted and effective safety net\nprograms, specifically through creating a precursor to a registry following a targeting methodology\nthat can be scaled-up.\n\n3. **The proposed Project is expected to support the inscription** **of about 72,000**\n**households in the targeting database and to directly", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000157:85:0:1", "start": 2121, "end": 2139, "surface": "targeting database", "probe_tag": "confusion", "probe_score": 0.7321, "luna_label": 0, "luna_reason": "Future project-supported enrollment into a targeting database"}]}, {"key": "paddy2-132", "text": "6\n\n\nThere is strong support in the Government for increasing resources for education, and the Government\nmade a commitment to increase education's share of budget from 16% in 2001-02 to 25% in 2009-10.\n\n\nOne of the reasons for choosing an APL with a ten-year perspective is that the education budget\nshortages will continue to be a constraint in the next few years. Over this period, Government\n\nexpenditures in non-priority areas will be brought under control and Government expenditures on\neducation can be expected to increase significantly. Despite the manageability in the long-run, the\nshort-run prospects on the budget are more challenging and donors will need to finance some recurrent\ncosts. The proposed APL will be implemented in three phases with distinct triggers (see Section B. 4).\nAs a result, a 10-year projection of enrollments and education costs has been developed (which is the\noverall framework for the APL), and a detailed five year plan and project proposals have been\nprepared (which is the framework for the first phase of the APL).\n\n\n3. Sector issues **to be addressed by the project and strategic choices**\n\nThe project will directly address all the issues below except for higher education.\n\n\n_Issues/Sector Problems_ _Government strategy and project proposal_\n\n**School Places**\n\nThe immediate problem in Djibouti City and The Government's strategy includes a combination\nsurrounding suburbs and other towns is the lack of of building more schools and continuing with the\nschool places due to the strong demand for schooling. double-shifting policy. The project will finance new\nclassrooms, sanitation services, and school furniture.\n\n**Equity, Gender, Disparities**\n\nChildren from poorer families, rural children, and The Government will construct schools in underespecially girls do not always attend school. The served areas, particularly in poorer parts of Djiboutirecent Household Expenditure Survey states that Ville where almost 70% of the population lives.\nmajor reasons for the", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000041:9:0:0", "start": 1906, "end": 1934, "surface": "Household Expenditure Survey", "probe_tag": "confusion", "probe_score": 0.8798, "luna_label": 1, "luna_reason": "Survey provides the attributed population-location finding."}]}, {"key": "paddy2-133", "text": "**Annex 5: Economic Analysis**\n\n\n**Chad: Safety Nets Project**\n\n\n1. This economic analysis provides an ex ante estimate of the program’s potential impact on\npoverty and consumption for different benefit scenarios.\n\n\n2. The main source of data for this analysis is the ECOSIT national household survey that\nwas carried out by the National Statistical Office in 2011. This survey included all 20 regions of\nthe country. In total, 9,259 households were surveyed, covering 49,985 individuals. The sample\nwas stratified into 20 clusters per region, of which 12 were urban and 8 were rural, apart from the\ncapital, N'Djamena, where 100 clusters were surveyed and all were classified as urban. Using the\nweighting methodology provided by the National Statistics Office, this survey corresponds to\nrepresenting a population of 10,015,591. The survey data was collected between June and July\n2011. For estimates of the costs in the United States of different benefit scenarios, the exchange\nrate of XAF 585 per U.S. dollar is used.\n\n\n3. The ECOSIT 2011 data is the most recent nationally representative consumption data.\nHowever, it is five years old and it is likely that the country has experienced changes in\nconsumption at the household level, the average household composition and the distribution of\nthe population across the country. These are key variables in computing estimated potential\nimpacts on poverty and consumption. Therefore, if updated, nationally representative\nconsumption data becomes available, it should be considered.\n\n\n4. The benchmark benefit scenarios considered in this analysis are the following:\n\n\n(a) **CfW pilot.** XAF 1,200 per day wage for 80 days of work implemented in\n\nN'Djamena\n\n\n(b) **CT pilot.** XAF 15,000 per month per household for a period of 24 months (paid\n\nevery two months) implemented in one Sahel region and one Sudanian region\n\n\n5", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000028:64:0:1", "start": 835, "end": 846, "surface": "survey data", "probe_tag": "confusion", "probe_score": 0.8967, "luna_label": 1, "luna_reason": "Existing ECOSIT survey data is declared as the analysis source."}, {"key": "refugee_pads:000028:64:0:3", "start": 1094, "end": 1110, "surface": "consumption data", "probe_tag": "confusion", "probe_score": 0.4996, "luna_label": 1, "luna_reason": "Existing consumption data supports the nationally representative recency claim."}]}, {"key": "paddy2-134", "text": "**The World Bank**\nAfghanistan: Eshteghal Zaiee - Karmondena (EZ-Kar) (P166127)\n\n\n   - **_Annual report:_** MoEC will prepare project level annual financial statements (AFS) in accordance with Cash\nBasis – International Public‐Sector Accounting Standards (IPSAS). The financial statements will cover one\nfinancial year and will be submitted to the auditors within two months of the close of the financial year.\n\n\n6. **Internal Audit Arrangements:** The internal audit of the project will be carried out by a chartered\naccountancy firm to be hired under the project. The semi‐annual internal audit reports will be submitted to the\nWorld Bank within two months after the end of each semester. The same firm will also cover the other World\nBank funded/managed projects implemented by KM and IDLG.\n\n7. **External Audit Arrangements:** The Supreme Audit Office (SAO), with the support of consultants, carries\nout the annual audit of all ARTF/World Bank‐funded projects. The same audit arrangements will be used. The\nSAO will submit to the World Bank, annual audited project financial statements and Management Letters within\nsix months of the close of the fiscal year. The financial statements of the project audit will be prepared by MoF\nbased on AFMIS records. There are common TORs for the audit of all projects that are reviewed by the World\nBank annually. The first audit report will be due on June 21, 2020.\n\n8. **Disbursement Arrangements:** The project will be jointly co‐financed by IDA and ARTF and the withdrawal\ncategories table will reflect that each disbursement will be financed by 75 percent IDA and 25 percent ARTF\nresources. Disbursement will be report‐based. Three implementing agencies (MoFA, KM and MoEC) will have\none separate designated account each to be set up in", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000123:79:0:0", "start": 1243, "end": 1256, "surface": "AFMIS records", "probe_tag": "confusion", "probe_score": 0.3558, "luna_label": 0, "luna_reason": "Financial records used to prepare project audit statements are routine bookkeeping."}]}, {"key": "paddy2-135", "text": "**The World Bank**\nEducation Quality Improvement Project (P179363)\n\n\nResearch increasingly points to positive relationships between the physical conditions of the school and\nstudent learning. Students attending schools with an appropriate learning environment (including modern\ninfrastructure, equipment, technology, and learning materials) have shown improvements in learning\nachievement of 5–10 percent, <sup>17</sup> [^17: Barrett, P., A. Treves, T. Shmis, D. Ambasz, and M. Ustinova. 2019. _The Impact of School Infrastructure on Learning: A Synthesis_\n_of the Evidence_ . International Development in Focus. Washington, DC: World Bank.] leading to higher earnings throughout their lifetime and faster economic\ngrowth at the national level. Without investment in better facilities and modern learning inputs, the\nimpact of the efficiency measures from the school optimization program will not be fully realized in terms\nof better learning outcomes and long-term economic benefits.\n\n\n**<u>Table 1. School Network Trends, 2017/18 to 2022/23</u>**\n\n|Col1|Schools|Students|Teachers|School Size|Class Size|Student-<br>Teacher Ratio|\n|---|---|---|---|---|---|---|\n|**Total**|**Total**|**Total**|**Total**|**Total**|**Total**|**Total**|\n|2022/23|1,216|330,409|32,254|278.8|21.1|10.2|\n|% change from 2017/18|−3.2|−0.2|−8.8|4.8|0.1|0.8|\n|**Urban**|**Urban**|**Urban**|*", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000185:15:0:0", "start": 1001, "end": 1022, "surface": "School Network Trends", "probe_tag": "confusion", "probe_score": 0.2014, "luna_label": 0, "luna_reason": "Standalone table title, not an independently cited data resource."}]}, {"key": "paddy2-136", "text": "conditions in the project area, which were confirmed during appraisal. Three solid waste\ndisposal scenarios were considered to manage the transportation and final disposal of waste **:**\n\nScenario 1 – Two long-term sanitary landfills (2040)\nScenario 2 – One long-term landfill (2040) and one interim landfill (2020)\nScenario 3 – One long-term sanitary landfill (2040)\n\n34. All three scenarios would require the upgrading and expansion of the Al-Fukhari\n(Sofa) landfill to serve the Southern Gaza Strip. During further expansion, this landfill\nwould become the sole landfill disposal site and an integral part of Scenarios 1 and 2.\n\n35. The economic analysis of the project compares costs and benefits to the economy as\na whole, while the financial analysis compares costs and benefits to the investor (JSCKRM). The economic analysis takes into account financial, environmental, economic,\nsocial, and health costs and benefits, while the financial analysis considers only financial\ncosts and benefits. The economic aspects of this proposal are potentially significant,\nparticularly for health and social benefits.\n\n\n36. The financial analyses of the project draw from cost data presented by consultants.\nThis information was obtained from engineering designs and international construction costs\nsupplemented, where possible, with local waste management operating cost data and waste\ncollection fees. Most local data came from the Gaza Municipality, which was taken to\nrepresent the Gaza Strip as a whole.\n\n\n37. Financial costs include capital investment costs, and operation and maintenance\ncosts, including the leasing of land. Financial benefits from composting and materials\nrecovery, as well as savings from reduced waste disposal costs, will be evaluated\nsubsequently by consultants.\n\n38. User charges will only be included in the financial analysis of the project, since they\nrepresent a transfer within the economy and as such are not be included in the economic\nanalysis. The project will encourage municipalities, through its capacity-building\ncomponent, to increase their fee collection by 30 percent. This is", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000035:22:0:0", "start": 1167, "end": 1176, "surface": "cost data", "probe_tag": "confusion", "probe_score": 0.5545, "luna_label": 1, "luna_reason": "Existing cost data from consultants informs the project's financial analysis."}, {"key": "refugee_pads:000035:22:0:1", "start": 1330, "end": 1372, "surface": "local waste management operating cost data", "probe_tag": "confusion", "probe_score": 0.2921, "luna_label": 1, "luna_reason": "Existing local cost data supplemented financial analysis and was sourced from Gaza Municipality."}]}, {"key": "paddy2-137", "text": "up>20</sup> and\nequitable manner, taking into account the needs of the entire population including the most vulnerable among host\nand SUTP populations. The activities will also aim to enhance the resilience of the infrastructure, as well as that of\nthe targeted communities to climate change–exacerbated risks such as droughts, floods, and degraded water quality,\nand also raise awareness of the mitigation measures to be derived from improved efficiency of the water supply and\nsanitation service delivery and improved solid waste management. The Project design ensures that careful attention\nis paid to gender and citizen engagement corporate priorities in the World Bank, both of which are central to the\ndevelopment of an inclusive and responsive approach to development among the host and SUTP communities.\n\n\n28. **Municipality and Sub-project eligibility.** The Project funds will be channeled through a public, national-level financial\nintermediary banking institution, ILBANK, which will in turn on-lend or on-grant it, as applicable to a number of\nmunicipalities or utilities (SKIs) based on a framework approach for sub-projects that meet eligibility criteria for\nparticipating in the project. Eligible municipalities were identified in the EU Needs Assessment. At appraisal, subprojects in five municipalities: Adana, Kahramanmaraş, Osmaniye, Kayseri and Konya, meeting the above criteria\nwere identified to participate in the project. The eligibility criteria for sub-projects will be defined in the Project\nOperational Manual (POM), and include, _inter alia_ : (a) a significant presence of SUTP in the host municipality as\nidentified in the EU Needs Assessment; and (b) municipal investments aligned with the PDO that are: (i) technically\nfeasible; (ii) economically and financially viable; (iii) demand and needs driven, and that demonstrate substantial\nreadiness, including having approved feasibility studies, detailed designs and draft safeguards documentation in line\nwith World", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000125:18:1:0", "start": 1251, "end": 1270, "surface": "EU Needs Assessment", "probe_tag": "confusion", "probe_score": 0.5784, "luna_label": 1, "luna_reason": "Assessment data identified eligible municipalities and informed project participation."}]}, {"key": "paddy2-138", "text": "_Sierra Leone_\n\n\nPRICES and GOVERNMENT FINANCE\n\n1981 1991 2000 2001 Inflation (%)\n_Domest)c_ _pHces_\n_(% change)_ c 1\nConsumer prices 16 7 102 7 -0.9 3 0 30 _< _\nImplicit GDP deflator 8 7 128 8 6 2 6 1 20\n\n_Govemment finance_ _10_\n_(% of GDP,_ _includes curent_ grants) 0\nCurrentrevenue .. 112 182 178 .10. 98 97 93 99 00 01\nCurrent budget balance .. -5 8 -4.5 -7 1 - GDP deflator _ CPI\nOverall surplus/deficit -10 4 -10.6 -12 3\n\n\nTRADE\n\n1981 1991 2000 2001 Export and Import levels (USS mnIll.)\n_(US$ millions)_\nTotal exports (fob) 147 176 75 78 400\nRutile . 72\nDiamonds (recorded) 32 10 21 300\nManufactures\nTotal imports (cHf) 317 158 161 303 20\nFood . 53 66 72 100\nFuel and energy 26 29 3d _ _8_\nCaptal goods .. 38 18 22  - __\n96 D6 97 9o 99 00 01\nExport price index _(1995=100)_ 90 86 87\nImport price Index (1995=100) 93 93 92 mExports ***Mrrports**\nTerms of trade (1995-100) 97 93 94\n\n\n\nBALANCE of PAYMENTS\n\n\n\n1981 1991 2000 2001 Curmnt account balance to GDP _(%)_\n_(US$_ _millions)_\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\n\n\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\nNet income -28 -60 -18 -20\nNet current", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000165:61:0:1", "start": 792, "end": 810, "surface": "Import price Index", "probe_tag": "confusion", "probe_score": 0.1084, "luna_label": 0, "luna_reason": "Standalone table index label, not an independently used data mention."}]}, {"key": "paddy2-139", "text": "**The World Bank**\nChad COVID-19 Strategic Preparedness and Response Project (P173894)\n\n\n|AFD|ABBREVIATIONS AND ACRONYMS Agence Française de Développement (French Agency for Development)|\n|---|---|\n|AFD<br>|_Agence Française de Développement_ (French Agency for Development)<br>|\n|<br>AMR<br>|<br>Anti-microbial Resistance<br>|\n|<br>BFP<br>|<br>World Bank Facilitated Procurement<br>|\n|<br>CDC<br>|<br>Center for Disease Control<br>|\n|<br>CERC<br>|<br>Contingency Emergency Response Component<br>|\n|<br>COVID-19<br>|<br>Coronavirus Disease<br>|\n|<br>CPIA<br>|<br>Country Policy and Institutional Assessment<br>|\n|<br>DA<br>|<br>Designated Account<br>|\n|<br>DFIL<br>|<br>Disbursement and Financial Information Letter<br>|\n|<br>DHIS<br>|<br>District Health Information System<br>|\n|<br>DLI<br>|<br>Disbursement-linked Indicators<br>|\n|<br>ECHO<br>|<br>European Civil Protection and Humanitarian Aid Operations<br>|\n|<br>EID<br>|<br>Emerging Infectious Disease<br>|\n|<br>ESCP<br>|<br>Environmental and Social Commitment Plan<br>|\n|<br>ESF<br>|<br>Environmental and", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000124:2:0:0", "start": 739, "end": 773, "surface": "District Health Information System", "probe_tag": "drop", "probe_score": 0.0056, "luna_label": 0, "luna_reason": "System is merely defined; no use of its data is shown."}, {"key": "refugee_pads:000124:2:0:1", "start": 796, "end": 826, "surface": "Disbursement-linked Indicators", "probe_tag": "drop", "probe_score": 0.004, "luna_label": 0, "luna_reason": "Abbreviation-table entry, not an actual indicator data use."}]}, {"key": "paddy2-140", "text": " assure adherence to policies and procedures; (iii) safeguard, manage and control the assets of the\nproject; (iv) ensure completeness and accuracy of the financial transaction/information; (v) ensure proper\nsegregation of FM-related functions; (vi) ensure proper flow of funds; and (vii) ensure adequacy and accuracy and\nrecording of FM data. The details of these procedures will be documented in the Project FM Manual to be prepared.\nThe Internal Audit Chamber will assign a staff to carry out internal audit reviews on the project on a regular basis.\nThe reports of the internal audit will be shared during supervision missions. The project management will ensure\nthat audit findings are timely resolved.\n\n61. **Disbursement Arrangement:** The following disbursement methods may be used under the project:\nreimbursement, advance, direct payment, and special commitment as will be specified in the Disbursement Letter\nand in accordance with the World Bank Disbursement Guidelines for Projects, dated February 1, 2017.\nDisbursements will be transactions-based whereby withdrawal applications will be supported with Statement of\nExpenditures (SOE). Documentation will be retained at the project for review by World Bank staff and external\nauditors. The Disbursement Letter will provide details of the disbursement methods, required documentation,\ndesignated account (DA) ceiling, and minimum application size. No withdrawal shall be made for payments made\nprior to the Signature Date of the Grant Agreement, except that withdrawals up to an aggregate amount not to\nexceed US$2,315,000 may be made for payments made prior to this date but on or after May 1, 2020, for Eligible\nExpenditures. The Closing Date is February 28, 2021. A period of four months (grace period) after the closing date\nwill be allowed to complete processing of disbursement for eligible expenditures incurred up to and until the closing\ndate of the grant.\n\n62. **Banking Arrangements** :", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:refugee_pads:000024:25:1:0", "start": 334, "end": 341, "surface": "FM data", "probe_tag": "drop", "probe_score": 0.0378, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-141", "text": "**The World Bank**\nTajikistan Water Supply and Sanitation Investment Project (P177325)\n\n\n**Component 1: Institutional Strengthening and Capacity-Building (ISCB) of Water Sector Institutions**\n**(US$3 million)**\n\n\n17. This Component will support activities at the national and regional level (Khatlon region) designed\nto improve policy and regulatory frameworks and institutional capacity to advance the sector reform and\npromote sustainable service delivery, duly accounting for current and expected climate change impacts\n(based on the collection and analysis of relevant data). The ISCB component is structured along the actions\noutlined in the National WSRP (2016–2025) and supports implementation of the upcoming NWSSP. The\nProject will also provide support to the targeted utilities, to execute envisaged activities and improve their\nability to operate and maintain, plan, implement and sustain expansion of safe water supply in the Khatlon\nregion, considering anticipated changes in the patterns of precipitation, evaporation, groundwater\nrecharge, and water quality impact of climate change.\n\n\n18. The RWSSP provides support to development of the NWSSP until 2030, which will provide\nbaseline information on the current status of the WSS services provision in the country, lay out a roadmap\nfor improved institutional set-up of the sector, develop investment plan in line with the agreed\nprioritization criteria and develop a framework of the sector-wide monitoring system. The program will\nbe underpinned by the review of the tariff-setting and subsidy policy in the sector. The project also\nassessed existing institutional arrangements for service delivery in Vosse and Vakhsh zone with the\ndistrict-wide water utility established in Vosse district and establishment of the Vakhsh bulk water utility\n(responsible for the water intake, water treatment plant and transmission pipeline ensuring water supply\nto Kushoniyon, Bokhtar, Vakhsh, Balkhi, Dusti, and Jayhun districts in the long term over the period of the\nprogram).", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000162:80:0:0", "start": 564, "end": 577, "surface": "relevant data", "probe_tag": "drop", "probe_score": 0.0458, "luna_label": 0, "luna_reason": "Data collection and analysis are planned project activities, not existing data use."}]}, {"key": "paddy2-142", "text": " The revenue potential of the BRT will need to be thoroughly\nanalyzed before BRT operation bidding launch and is a major determinant in the feasibility of attracting private sector\ninvestment and participation through a PPP arrangement. The structuring of PPPs or concessions and the\nimplementation of Bank policies will require institutional capacity development. The Bank will be incorporating\nlessons learned from other BRT projects and transport-related PPPs financed by the World Bank Group to mitigate\nthese risks. As is the case for all transport projects, demand forecasting is subject to estimation error and data\nuncertainty. Since travel demand data for the Region is scarce, the Project is also supporting the update of origindestination surveys and the development of a transport demand model to help structure concession agreements. The\ninstitutional strengthening activities under Component 4 will help mitigate these risks. The Project will also provide\n\n\nPage 36 of 77", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:refugee_pads:000182:40:2:0", "start": 642, "end": 660, "surface": "travel demand data", "probe_tag": "drop", "probe_score": 0.0215, "luna_label": 0, "luna_reason": null}, {"key": "sample:refugee_pads:000182:40:2:1", "start": 732, "end": 757, "surface": "origindestination surveys", "probe_tag": "drop", "probe_score": 0.0275, "luna_label": 0, "luna_reason": "Project supports updating surveys, indicating planned data production rather than existing data use."}]}, {"key": "paddy2-143", "text": " from<br>the activities<br>in support of<br>community<br>tourism<br> <br>UWA will compile<br>information based on<br>activity reports.<br> <br>UWA<br>|Community ecotourism enterprises<br>supported<br>This indicator measures the<br>number of community-<br>based ecotourism projects<br>supported under<br>Component 2.1.<br>This indicator measures the<br>transformative capacity of<br>resilience through<br>enhancing economic<br>opportunities for<br>communities.<br>Annual<br> <br>Reports from<br>the activities<br>in support of<br>community<br>tourism<br> <br>UWA will compile<br>information based on<br>activity reports.<br> <br>UWA<br>|Community ecotourism enterprises<br>supported<br>This indicator measures the<br>number of community-<br>based ecotourism projects<br>supported under<br>Component 2.1.<br>This indicator measures the<br>transformative capacity of<br>resilience through<br>enhancing economic<br>opportunities for<br>communities.<br>Annual<br> <br>Reports from<br>the activities<br>in support of<br>community<br>tourism<br> <br>UWA will compile<br>information based on<br>activity reports.<br> <br>UWA<br>|Community ecotourism enterprises<br>supported<br>This indicator measures the<br>number of community-<br>based ecotourism projects<br>supported under<br>Component 2.1.<br>This indicator measures the<", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:refugee_pads:000043:58:1:0", "start": 117, "end": 133, "surface": "activity reports", "probe_tag": "drop", "probe_score": 0.0097, "luna_label": 0, "luna_reason": "Future compilation based on project activity reports is planned monitoring use."}]}, {"key": "paddy2-144", "text": " the situation that was agreed upon with\nthe Borrower.\n\nSigned by:\nFinancial Management v I _N_\n##### Specialist K {dO'.i1, O0\n\n(FMS-OPR) Rafika Chaouali, MNSHD Date\n\n\n**Part II:** **Procurement/Contract Management** System\n\nI have reviewed the procurement/contract management system relating to this project, including\nthe format and content of the section on Project Management Reports (PMRs) on procurement\n\nmonitoring. The objective of the review was to determine whether the procurement/contract\nmanagement system adopted by the project conforms to IDA's guidelines for procurement in\ninvestment projects. My review was based on the \"Assessment of Agency's Capacity to\nImplement Project Procurement, Setting of Prior Review Thresholds and Procurement\nSupervision Plan\" guidelines issued by IDA.\n\nI confirm that the project satisfies IDA's minimum procurement management requirements.\nHowever, in my opinion, the project does not have in place an adequate procurement/contract\nmanagement system that can provide the appropriate data on major procurement and contract\nmanagement (PMR - Section 3) as required by IDA.", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:refugee_pads:000161:54:1:0", "start": 1032, "end": 1081, "surface": "data on major procurement and contract\nmanagement", "probe_tag": "drop", "probe_score": 0.0015, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-145", "text": ".\n\n\n     - **MOSA** SDCs are responsible for: (i) receiving household applications and interface\nwith applicant; (ii) data entry into program application; (iii) conducting household\nvisits; (iv) checking possible data errors in application forms against provided\nofficial documents; (v) transmitting households' application data to **MOSA** central\nunit; and (vi) handling appeals and claims received **by** households..\n\n\n**8.** With respect to the institutional setup of the **NPTP,** the progam has been managed **by** the\n**MOSA** and the Presidency of the Council of Ministers (PCM). <sup>6</sup> This was deemed the best\noption at the time of appraisal of the **ESPISP** II project, which supported the creation of the\n**NPTP.** <sup>**3 7**</sup> The present institutional setup will be retained during the implementation of the SPPP,\nthough the **GOL** has started discussing the possibility of consolidating the **NPTP** under **MOSA**\nand institutionalizing it as an independent program with its own budgetary allocations.\n\n\n**36** **A** central management unit at the PCM and a central unit in **MOSA** manage the program. The former is responsible for: (i) comanaging the central **NPTP** database; (ii) validating data and cross-checking with national databases; (iii) processing household\ndata and generating scores and ranks according to the proxy-means testing (PMT) formula; (iv) maintaining the PMT formula;\n(v) analyzing national data and reporting findings to the Social Inter-Ministerial Committee (Social-IMC); (vi", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:refugee_pads:000109:51:1:0", "start": 1256, "end": 1274, "surface": "national databases", "probe_tag": "drop", "probe_score": 0.025, "luna_label": 1, "luna_reason": null}, {"key": "sample:refugee_pads:000109:51:1:1", "start": 1293, "end": 1307, "surface": "household\ndata", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-146", "text": "24\n\n\n**During negotiations the following assurances were received:**\n\n\n1. Agreement on triggers for subsequent phases\n2. Agreement on monitoring and impact assessment studies\n3. Agreement on project monitoring indicators\n4. Agreement on finalized bidding documents for the first batch of schools\n\n\n**Actions to be included in Development Credit Agreement:**\n\n\n_Financial_\n\n\n1. Audits and Project Management Reports.\n2. Dated covenant on the selection of the auditor before March 31, 2001.\n\n\n_Management_\n\n\n1. Daied covenant on a baseline survey to establish gender and social class distribution of students\nbefore December 31, 2001.\n2. Provide regular reports on monitoring indicators and prepare a draft midterm report for review\nwith IDA before September 15, 2002.\n\n\n**In addition the following Management conditions are included in supplemental letters attached**\n**to the Developinent Credit Agreement:**\n\n\n1. Triggers from Phase I to Phase II in APL\n2. Triggers from Phase II to Phase III in APL\n\n\nH. READINESS **FOR IMPLEMENTATION**\n\n\nL. a) The engineering design documents for the first year's activities are complete and ready for the\n\nstart of project implementation.\nD b) Not applicable.\n\n3 2. The procurement documents for the first year's activities are complete and ready for the start of\nproject implementation.\n\n\nK/ 3. The Project Implementation Plan has been appraised and found to be realistic and of satisfactory\n\nquality.\n##### D 4. \"he following 7tems are lacking and are discussed under loan conditions (Section G):", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000090:27:0:0", "start": 529, "end": 544, "surface": "baseline survey", "probe_tag": "drop", "probe_score": 0.0491, "luna_label": 0, "luna_reason": "Covenant requires a future baseline survey before a specified deadline."}]}, {"key": "paddy2-147", "text": "**The World Bank**\nUganda Investing in Forests and Protected Areas for Climate-Smart Development Project (P170466)\n\n\n\n\n\n|plans|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Tree farmers reached with assets or<br>services (agroforestry and woodlots)<br>This indicator measures the<br>outcomes of activities<br>related to provision of<br>inputs to the agroforestry<br>and woodlots establishment<br>interventions.<br>This indicator measures the<br>transformative and<br>absorptive capacity of<br>resilience.<br>Annual<br> <br>Activity<br>reports<br> <br>Data from activity<br>reports of the technical<br>service providers will<br>be compiled and<br>transmitted to the<br>MWE.<br> <br>MWE<br>|Tree farmers reached with assets or<br>services (agroforestry and woodlots)<br>This indicator measures the<br>outcomes of activities<br>related to provision of<br>inputs to the agroforestry<br>and woodlots establishment<br>interventions.<br>This indicator measures the<br>transformative and<br>absorptive capacity of<br>resilience.<br>Annual<br> <br>Activity<br>reports<br> <br>Data from activity<br>reports of the technical<br>service providers will<br>be compiled and<br>transmitted to the<br>MWE.<br> <br>MWE<", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000043:59:0:0", "start": 558, "end": 576, "surface": "Data from activity", "probe_tag": "drop", "probe_score": 0.0359, "luna_label": 0, "luna_reason": "Future compilation and transmission of activity-report data is planned project reporting."}]}, {"key": "paddy2-148", "text": " from project investments and it provides the overarching framework by which\npotential resettlement issues will be addressed. Finally, the project will also provide resources to\nstrengthen the capacity of the CCEs in environmental and social management. The trainings are\ncurrently being organized for the CCEs and other key stakeholders in all the cities.\n\n\n80. **Safeguards capacity and institutional arrangements.** With regards to capacity, based on\nthe experience gained through the implementation of the PDUE, the PCU is considered to have\nacquired significant experience in implementing World Bank Safeguards Policies. The project\nemploys an Environment Specialist, and will recruit a social development specialist. To ensure\ncontinuity of safeguards supervision at the local municipal/city-level, the project will hire for the\nTLUs five social development specialists who will work in close collaboration with the safeguards\nspecialists at the central level.\n\n\n81. **Youth and gender.** As part of subcomponent 2.3 (Support to local initiatives), the project\nwill support implementation of a series of activities that target youth and women in certain poor\nneighborhoods of the targeted cities. A social assessment of targeted cities is underway and will\nprovide the relevant demographic, social, economic and cultural information regarding the\npopulations, including any baseline data that could be used for M&E. Additionally, the project is\n\n14 For the sludge treatment plant at the Ngombé site, an Abbreviated Resettlement Action Plan (ARAP) had already been prepared,\napproved and implemented under the Cameroon Sanitation Project (P117102). The ARAP was re-disclosed under the proposed\nProject in country and on InfoShop on April 28, 2017.\n15 Due to existing national regulatory and institutional framework for land expropriation and resettlement, World Bank projects\nexperience extensive delays due to compensations. The main constraint in consolidating the World Bank and national framework\nis with regard to the eligibility criteria and the lengthy procedures associated with land acquisition. Based on a request from the", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:refugee_pads:000144:34:1:0", "start": 1205, "end": 1241, "surface": "social assessment of targeted cities", "probe_tag": "confusion", "probe_score": 0.0693, "luna_label": 0, "luna_reason": null}, {"key": "sample:refugee_pads:000144:34:1:1", "start": 1380, "end": 1393, "surface": "baseline data", "probe_tag": "drop", "probe_score": 0.0286, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-149", "text": " the life of the\nproject. This will be an important step in ensuring that communities understand the project and\nthat program management at the local and central level can investigate and take appropriate\nactions to address complaints. The grievance management system will enhance the transparency\nof the project management and its accountability to beneficiaries and stakeholders.\n\n\n32. **Management Information Systems.** The MIS will be developed to provide a\ncomputerized system for the targeting instrument and registry, and for the management of the\nvarious benefits of the two safety nets piloted under the project. Modules will include (a)\nbeneficiary data and registration; (b) monitoring of beneficiaries´ participation in trainings and\naccompanying measures, and/or co-responsibilities (for example attendance at work for the\nCfW); (c) payment of benefits to the beneficiaries; (d) complaints and their resolution.\n\n\n**Component 3: Project Management, Communication, and Monitoring and Evaluation**\n**(US$1.9 million equivalent – IDA Financed)**\n\n\n33. **The objective of this component is to develop the institutional capacity within the**\n**Government of Chad to deliver the activities outlined under components 1 and 2, and**\n**ultimately improve its ability to effectively respond to the needs of vulnerable households.**\nThe project will therefore support the establishment and capacity development of the newly\nestablished CFS, which will effectively be managing the project.\n\n\n34. **The component will finance the salaries of the CFS key staff members deemed**\n**essential to the implementation of the proposed pilot.** This includes a project coordinator, a\nprocurement officer, a FM officer, an accountant, and an M&E expert (who will also serve as a\n\n\n34", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:refugee_pads:000028:45:1:0", "start": 648, "end": 664, "surface": "beneficiary data", "probe_tag": "drop", "probe_score": 0.0204, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-150", "text": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000170:16:0:0", "start": 379, "end": 395, "surface": "statistical data", "probe_tag": "drop", "probe_score": 0.0402, "luna_label": 0, "luna_reason": "Planning unit generates the data, so it is project-produced rather than existing data use."}]}, {"key": "paddy2-151", "text": "A November Winterisation study among vulnerable Syrian refugees found that education levels slightly\ncontributed to the ability to generate income:\n\n- 17% of those with no education were able to generate an income\n\n- 28% of those with primary education levels\n\n- 24% of those with for secondary education or higher\n\n- However, those with higher levels of education were more likely to have permanent employment\n\n- 20% of those with secondary education had permanent employment\n\n- 10% of those with primary education\n\n- 13% with no education\n\n_South_\n\nA Swiss Solidar assessment in Nabatieh and Jezzine Districts in Southern Lebanon in August among around\n700 individuals showed that those employed in Lebanon were doing similar work to that in Syria, although\nthere was a shift away from skilled work such as metalwork and carpentry towards more menial casual labour.\n\n_North and Bekaa_\n\nThe EMMA assessment in April 2013 on construction showed that the construction market can better support\nthe income needs of skilled workers compared to unskilled workers: from 30 to 60% of the overall income\nneeds for unskilled construction workers and60-100% of the needs for skilled workers.\n\n\n_Beirut_\n\nA small-scale assessment by Amel in February 2014 in Beirut and Tyre found that women face challenges in\nsecuring higher incomes, related to a lack of capital, lack of equipment, and difficulty in obtaining a loan. Very\nfew of them would launch a business independently and prefer to work collectively, in order to diminish risks\nand be able to rely on the others.\n\n<u>Palestinian refugees</u>\n\n\nA 2011 labour force survey among Palestinian refugees living in camps and gatherings showed that the\nPalestinian workforce is poorly educated, young and lacking in skills. Most are engaged in low-status jobs\nconcentrated in commerce and construction.\n\n\n25", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000441:24:0:0", "start": 553, "end": 577, "surface": "Swiss Solidar assessment", "probe_tag": "keep", "probe_score": 0.9194, "luna_label": 1, "luna_reason": "Assessment reports employment and occupational shifts among surveyed individuals."}, {"key": "reliefweb:000441:24:0:2", "start": 1593, "end": 1617, "surface": "2011 labour force survey", "probe_tag": "keep", "probe_score": 0.9254, "luna_label": 1, "luna_reason": "Existing survey provides findings about Palestinian refugees’ workforce characteristics."}]}, {"key": "paddy2-152", "text": "MONITOREO DE PROTECCIÓN\n\n##### **1. Introducción y contexto**\n\n\nPanamá es hogar para más de 15,000 refugiados y solicitantes de la condición de refugiado. La\n\npoblación de refugiados reconocidos está compuesta principalmente por personas de Colombia, El\n\nSalvador, Cuba, Nicaragua y Venezuela, y superan las 2,500 personas.\n\n\nACNUR, la Agencia de la ONU para los Refugiados, realizó un tercer monitoreo de protección\n\nutilizando la herramienta de **Encuesta de Alta Frecuencia (HFS, por sus siglas en inglés, en adelante:**\n\n**HSF3)**, del 21 de octubre al 31 de diciembre de 2021, con el fin de continuar recopilando\n\ninformación y datos actualizados sobre los riesgos de protección que enfrentan las personas de\n\ninterés frente a las limitaciones al acceso a derechos y servicios básicos durante el contexto de la\n\npandemia por COVID-19. Se realizaron un total de 358 encuestas a grupos familiares, alcanzando\n\n1025 personas de distintas nacionalidades, dentro del territorio panameño <sup>**1**</sup> : nicaragüense (36%),\n\nvenezolana (25%), colombiana (24%), salvadoreña (8%), cubana (4%) y otras nacionalidades (2%).\n\n\nLa encuesta del HSF3 estuvo compuesta por tres secciones: (1) aspectos generales y sobre su\n\ndesplazamiento, (2)", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001181:2:0:1", "start": 527, "end": 531, "surface": "HSF3", "probe_tag": "keep", "probe_score": 0.9222, "luna_label": 0, "luna_reason": "HSF3 survey data were being collected by the monitoring exercise."}]}, {"key": "paddy2-153", "text": " In\nthe FDS surveys, the estimated prevalence of\ndepression is 16 per cent among refugees and 12 per\ncent among host populations. While the specific\ncircumstances vary across different displacement\nsituations, the surveys show that whatever their\nsituation, refugees are at a higher risk of depression\nthan the host communities. These findings align with\nother studies that have consistently shown similar\ntrends, highlighting the significant mental health\nchallenges faced by refugee populations.\n\n\n\n**106** [See World Mental Health Report, World Health Organization.](https://www.who.int/teams/mental-health-and-substance-use/world-mental-health-report)\n**107** These countries also host 73 per cent of refugees.\n**108** See <u>[New WHO prevalence estimates of mental disorders in conflict settings: a systematic review and meta-analysis, Charlson et al.](https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736%0x2819%0x2930934-1.pdf)</u>\n**109** See <u>[World Mental Health Report, World Health Organization.](https://www.who.int/teams/mental-health-and-substance-use/world-mental-health-report)</u>\n**110** See <u>[Epidemiology of depression among displaced people: A systematic review and meta-analysis, Bedaso and Duko;](https://pubmed.ncbi.nlm.nih.gov/35316692/)</u> <u>[Prevalence of Mental](https://pubmed.ncbi.nlm.nih.gov/30210373/)</u>\n<u>[Distress Among Syrian", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001242:29:2:0", "start": 8, "end": 19, "surface": "FDS surveys", "probe_tag": "keep", "probe_score": 0.9747, "luna_label": 1, "luna_reason": "Survey findings provide estimated depression prevalence among refugees and host populations."}]}, {"key": "paddy2-154", "text": "SGBV SWG\n\n\nin Jordan, along with significant numbers of Somalis and Sudanese. <sup>2</sup> The 2015 Vulnerability Assessment Framework (VAF)\nBaseline Survey found high levels of economic vulnerability, with 86% of Syrian refugee households identified as living under\nthe poverty line of USD 98 per person per month. Their financial resources depleted, many families now increasingly turn to\nnegative coping mechanisms such as exploitative labor, school dropout of children and child labor, and early marriage. While\nthese coping mechanisms may help meet a family’s immediate subsistence needs, they often do so at the cost of increased\nexposure to exploitation or human rights violations, and limitation of future opportunities and prospects. At the close of 2015,\ndespite a reduction in violence in Syria brought by a partial cessation of hostilities, opportunities for voluntary repatriation\nremain only a future hope. While resettlement opportunities were significantly expanded (with 24,374 refugees submitted to\nresettlement countries during the year), the vast majority of refugees remains in Jordan without foreseeable prospects for a\ndurable solution.\n\n## **Types of Sexual and Gender-Based Violence**\n\nThe GBVIMS categorizes the various forms of SGBV into six major types: forced marriage; psychological/emotional abuse;\nphysical assault; denial of resources; sexual assault, and rape. The patterns of types of GBV as per the analyzed GBVIMS data\nremain more or less consistent in 2014 and 2015. During 2015 more than half of survivors (54.8 %) reporting SGBV incidents to\ndata gathering agencies experienced psychological/emotional abuse (28%) and physical assault (26.8%), while 32.7% reported\nforced marriage (including early marriage).\n\n\ni) **<u>Sexual assault and rape</u>** is the most severe form of SGBV and may lead to serious life-threatening consequences,\nincluding death. Sexual assault and rape are often the most difficult", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001658:1:0:0", "start": 95, "end": 156, "surface": "2015 Vulnerability Assessment Framework (VAF)\nBaseline Survey", "probe_tag": "keep", "probe_score": 0.9574, "luna_label": 1, "luna_reason": "Named baseline survey provides the cited 86% refugee poverty finding."}, {"key": "reliefweb:001658:1:0:1", "start": 1444, "end": 1455, "surface": "GBVIMS data", "probe_tag": "keep", "probe_score": 0.9766, "luna_label": 1, "luna_reason": "Analyzed GBVIMS data supports reported patterns and survivor figures."}]}, {"key": "paddy2-155", "text": "**Tabla No.4 Bandas Criminales Responsables de Situaciones de Riesgo o Desplazamiento**\n\n\nFuente: UDFI-CONADEH, con datos del SI-Quejas, Enero-Diciembre de 2017\n\n\npartamental, asesinatos a sueldo (sicariato), robo de carros repartidores, abigeato, abuso sexual, extorsión, entre otros.\n\n\nEn otros casos, debido a que las víctimas fueron testigo o denunciaron la comisión de delitos (relacionadas con bandas\ncriminales dedicadas a la estafa y asalto contra clientes de entidades bancarias o financieras, el secuestro exprés, robo\nde casas, falsificadores o secuestradores), ello provocó amenazas de muerte, persecución, intimidación y otras modalidades violatorias que motivaron la preparación o el desplazamiento de su lugar de origen para salvaguardar la vida.\nPor su parte, las barras bravas son agrupaciones de personas seguidoras de equipos de futbol profesional de Honduras\nque, en apariencia tendrían como único objetivo apoyar los encuentros deportivos en los estadios. Sin embargo, en los\núltimos años, las barras bravas ocasionan batallas campales entre ellas, con consecuencias de lesiones físicas y, en el\npeor de los casos, la pérdida de la vida.\n\n\nDe acuerdo con Insight Crime, las barras bravas parecen tener nexos con las maras y pandillas por ser espacios poten\n\n**49**", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000291:49:0:0", "start": 126, "end": 135, "surface": "SI-Quejas", "probe_tag": "keep", "probe_score": 0.9125, "luna_label": 1, "luna_reason": "Named complaint system cited as the data source for a table."}]}, {"key": "paddy2-156", "text": " compared to\nother non-nationals.\n\n\nIn at least seven countries surveyed, refugees\nare required, as other non-nationals, to obtain a\nwork permit before entering the labour market.\nObtaining a work permit may require payment\nof fees and a minimal duration of prior lawful\nresidence, thereby possibly excluding refugees\nin practice from accessing the labour market.\nWhere obtaining work permits is not clearly\nregulated, the authorities have wide discretion as\n\n\n\nto when and to whom a work permit is provided.\nIn 18 countries surveyed, refugees are explicitly\nallowed to start their own businesses.\n\n\n**In practice, far fewer refugees have**\n**access to decent work**\n\n\nNotwithstanding laws providing access to decent\nwork for refugees, the situation in practice is\noften very different from what the law permits.\nHigh unemployment rates, informal economies,\nadministrative challenges, and unaffordable fees for\nrecruiting refugees make it difficult for refugees to\nhave access to decent work. Furthermore, employers\nmay not be aware of refugees’ right to work.\n\n\n\nRefugees as well as host communities’ access to\nwork has deteriorated further with the COVID-19\npandemic. This jeopardizes efforts to support\nrefugees’ self-reliance, improve their skills to\nbecome competitive on the job market, and\ninclude them in local and national development\nplans. As a result, refugees may only have\naccess to low or unskilled work or may resort\nto work in the informal economy. According to\nUNHCR’s Global Livelihoods Survey from 2021,\nglobally only 38 per cent of refugees live in\ncountries with unrestricted access in practice\nto formal employment, including wage-earning\nor self-employment. However, this is a rough\nestimate, and measuring access to decent work\nin practice would benefit from data collected\nthrough household surveys (e.g., inclusion of\nrefugees in labour force surveys) to know more\nabout the daily experiences of refugees and host\ncommunities.\n\n\n**Close to two-thirds of refugees enjoy**\n**freedom of movement under the law**", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000803:20:2:0", "start": 1487, "end": 1512, "surface": "Global Livelihoods Survey", "probe_tag": "keep", "probe_score": 0.9207, "luna_label": 1, "luna_reason": "UNHCR survey provides the cited global estimate of refugees’ formal employment access."}]}, {"key": "paddy2-157", "text": "Integrated GbV and SRH\nSectoral Impact and Needs Analysis\nHeavy monsoon floods in the northern parts of Bangladesh have caused substantial damage and suffering\nacross many districts. Flood damage, prolonged inundation together with COVID-19 distress has severe and\ndisproportionate impact on the safety and security, i.e.- protection of women, adolescent girls and other\nmarginalized groups. Demographic data is showing out of the affected people, around 1.47 million are\nwomen, almost 50,000 pregnant mothers, and that 160,000 are adolescent girls and children aged 5-18. Loss\nof houses, livelihoods, restricted mobility, lack of privacy, disrupted services and inaccessibility - weaken\nprotection measures and resilience of individuals. Around 40% female responded insecurity as one of the\nsufferings due to the flood. Earlier studies on COVID 19 already indicate an increasing trend of early marriage\nand this prolonged distress can further intensify such negative coping mechanisms. Possession of essential\npersonal items including clothes, GBV and SRH awareness and information can enhance confidence of\nadolescent girls, women and other gender diverse group to protect themselves and adopt GBV risk mitigation\nmeasures. At a household level, increasing food insecurity will impact the female headed households,\nadolescent girls and pregnant mothers the most – around 80% of the unions indicates irregular food intake or\nskipping meal, particularly as key sufferings for women and girls. Additionally, the loss of livelihood due to\nflood will differently impact women – taking away their fundamental rights including decision making and\naccess to services. In rural Bangladesh lifetime partner violence of any form is around 74% (VAW 2015),\ntherefore such distress can potentially lead to domestic violence against women and girls.\nSexual and Reproductive Health (SRH) needs during crisis situations are many times overlooked. For women\nand girls, this can result in life-threatening complications and even death. Primary data shows that health care\nservices and antenatal and neonatal care services have been disrupted in 251 (75%) and 215 (64%", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001664:34:0:0", "start": 392, "end": 408, "surface": "Demographic data", "probe_tag": "confusion", "probe_score": 0.7293, "luna_label": 1, "luna_reason": "Data is attributed to concrete demographic counts of affected people."}, {"key": "reliefweb:001664:34:0:1", "start": 2019, "end": 2031, "surface": "Primary data", "probe_tag": "confusion", "probe_score": 0.7666, "luna_label": 1, "luna_reason": "Primary data supports concrete findings on disrupted healthcare services."}]}, {"key": "paddy2-158", "text": " or sea level rise, are\nlargely qualitative, with few comparative studies. <sup>58</sup>\n\n\nAdditionally, among the limited number of studies\nand research projects that are climate change- and\nmobility-specific, few address children in particular.\nThese significant gaps in the data and evidence are\nnot only concerning when it comes to understanding\nthe situation of climate-related migrant and displaced\nchildren, but also in regard to the entire population\nof children on the move – many of whom are among\nthe most vulnerable children on the planet (see #4,\np. 19).\n\n\nEstimates vary widely when it comes to predicting\n\n\n#### **THE ISSUE:** **11 questions,** **11 insights**\n\n\n\n#1. While we know climate change can be directly and indirectly linked to\npatterns of human mobility and displacement, do we have the data to\nestimate to what extent child mobility has been or will be affected?\n\n\nClimate change is difficult to isolate as a driver of human mobility; this,\ncoupled with a lack of child-specific data and research on the links\nbetween migration, displacement and climate change, means the number\nof children who are and will be on the move as climate change intensifies\nremains unclear.\n\n\n\nthe number of children who will be on the move as a\nresult of climate change-induced threats; it is critical\nthat those cited are derived from empirically based\nconceptual tools that consider the complexities\nof human mobility and climate change, as well as\ncross-cutting issues (e.g., social, economic, political\nand environmental). <sup>59</sup>\n\n\nA few examples of estimates include:\n\n- Slow-onset climate impacts (e.g., water stress,\nfailing crops, sea level rise and storm surges)\ncould result in the (internal) displacement of\n44 to 113 million people by 2050; in a more\npessimistic scenario, this number could reach as\nhigh as 125", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001147:9:1:0", "start": 991, "end": 1010, "surface": "child-specific data", "probe_tag": "confusion", "probe_score": 0.2929, "luna_label": 0, "luna_reason": "States a data gap without citing analysis or a substitute estimate."}]}, {"key": "paddy2-159", "text": "**PROTECTION BRIEF III SLOVAKIA**\n\n**July 2023 – March 2024**\n\n\napartments and houses to refugees at no charge, as well as for owners of non-commercial collective\naccommodation sites, <sup>16</sup> and 2) a subsidy from the Ministry of Transport for commercial accommodation\nproviders (hotels, hostels, private dormitories, etc.), which allowed for the possibility of additional\ncharges to refugees. <sup>17</sup> According to the official data, more than 46,000 refugees benefited from these\nsubsidies in December 2023. <sup>18</sup> Moreover, the Government of Slovakia provided various asylum facilities\nand the largest collective accommodation center in Gabčíkovo, managed by the Migration Office of the\nMinistry of Interior, for accommodation of predominantly vulnerable Temporary Protection holders.\nFinally, it repurposed publicly owned accommodation sites intended for educational or recreational use\nto support accommodation needs of refugees. Together, these measures supported the compliance with\nthe European Union Temporary Protection Directive and safeguarded refugees’ right to accommodation.\nIn focus group discussions with UNHCR, refugees repeatedly expressed strong gratitude for this\nsupport, recognizing the help of the Government, local communities, and landlords.\n\n\nData from Protection Profiling and Monitoring and the MSNA showed that most refugees in Slovakia\nlived in private accommodation (i.e. apartments or houses). At the same time, considerable number of\nrefugees also resided in collective accommodation sites. <sup>19</sup> Specifically, the MSNA data indicated that\n47% of respondents have their own accommodation, 18% were in shared accommodation, 22% in\ncollective sites, and 10% in hotels or hostels. A vast majority of those surveyed through Protection\nProfiling and Monitoring (97% between January and March 2024) reported having a rental contract, and\n84% of the MSNA respondents indicated no issues with living conditions in their accommodation. At the\nsame", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000476:2:0:0", "start": 431, "end": 444, "surface": "official data", "probe_tag": "confusion", "probe_score": 0.7341, "luna_label": 1, "luna_reason": "Official data supports the reported count of refugees benefiting from subsidies."}]}, {"key": "paddy2-160", "text": "Chapter 5\n\n\n\n\n\n**3. Expand access**\n**to third country**\n**solutions.**\n\n\n**4. Support**\n**conditions in**\n**countries of**\n**origin for return**\n**in safety and**\n**dignity.**\n\n\n\n3.1 Refugees in\nneed have access\nto resettlement\nopportunities in an\nincreasing number of\ncountries.\n\n\n3.2 Refugees have\naccess to complementary\npathways for admission\nto third countries.\n\n\n4.1 Resources are made\navailable to support the\nsustainable reintegration\nof returning refugees by\nan increasing number of\ndonors.\n\n\n4.2. Refugees are able\nto return and reintegrate\nsocially and economically.\n\n\n\n3.1.1. Number of refugees who\ndeparted on resettlement from\nthe host country\n\n\n3.1.2. Number of countries\nreceiving UNHCR resettlement\nsubmissions from the host\ncountry\n\n\n3.2.1. Number of refugees\nadmitted through complementary\npathways from the host country\n\n\n4.1.1. Volume of ODA provided\nto, or for the benefit of, refugee\nreturnees in the country of origin\n\n\n4.1.2. Number of donors\nproviding ODA to, or for the\nbenefit of, refugee returnees in\nthe country of origin\n\n\n4.2.1. Number of refugees\nreturning to their country of\norigin\n\n\n4.2.2. Proportion of returnees\nwith legally recognized\ndocumentation and credentials\n\n\n\nAdministrative Records\n\n\n(processed by UNHCR)\n\n\nAdministrative Records\n\n\n(processed by UNHCR)\n\n\nAdministrative Records\n\n\n(OECD and UNHCR)\n\n\nAdministrative Records\n\n\n(OECD Financing for Refugee\nSituations Survey 2020)\n\n\nAdministrative Records\n\n\n(OECD Financing for Refugee\nSituations Survey 2020)\n\n\nAdministrative Records\n\n\n(UNHCR)\n\n\nHousehold surveys /\nadministrative records\n\n\n(UNHCR)\n\n\n\n\n\n74", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:reliefweb:000803:37:0:0", "start": 1208, "end": 1230, "surface": "Administrative Records", "probe_tag": "confusion", "probe_score": 0.3938, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000803:37:0:1", "start": 1374, "end": 1423, "surface": "OECD Financing for Refugee\nSituations Survey 2020", "probe_tag": "confusion", "probe_score": 0.8992, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000803:37:0:2", "start": 1453, "end": 1502, "surface": "OECD Financing for Refugee\nSituations Survey 2020", "probe_tag": "confusion", "probe_score": 0.872, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000803:37:0:3", "start": 1541, "end": 1583, "surface": "Household surveys /\nadministrative records", "probe_tag": "keep", "probe_score": 0.9064, "luna_label": 1, "luna_reason": "Table source identifies surveys and records supporting the refugee returnee indicator."}]}, {"key": "paddy2-161", "text": "<br>-<br>-<br>34<br>-<br>5<br>7<br>-<br>2,216<br>14,257<br>-<br>1,100<br>816<br>57<br>8,097<br>251<br>25<br>122<br>909<br>5,885<br>268<br>6,103|\n\n\n\nUNHCR Mid-Year Trends 2015 **17**", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000912:16:6:0", "start": 148, "end": 174, "surface": "UNHCR Mid-Year Trends 2015", "probe_tag": "confusion", "probe_score": 0.6536, "luna_label": 1, "luna_reason": "Named UNHCR report citation identifies an existing data source."}]}, {"key": "paddy2-162", "text": "*MCI** **ICh**\n**JMDO** **NMunlDIIMi.tlOf'I**\n\n\n\n\n  - **.** .\n\n**111.ao**\n\n\n. **.** ...\n\n\n### - 4UH ·\n\n\n\n**UOJ-\"'O** **CO!lllk1** **l0Pw**\n**101.llO** **Natur** **lDitNI .. IDf'I**\n\n\n**900,9'9**\n\n\n\n**£-11** **KIY,1ou••**\n\n\n\n**1**\n\n**!1** **1���tl'l(>fn Afflc•**\n\n\n\n**�-+** **fot!1**\n\n\n\n?{➔ ��!���o�! **IDP\\**\n\n\n\n?(-+ **�-'!ir��!?stetl�** **A**\n\n\n\n_Figure 2. Number of /DPs in RBSA by Cause as of 30_\n_April 2022_\n\n\n\nData Sources\n\nAmong 16 countries in the region, the data of refugees and asylum-seekers in 11 countries are fully hosted by proGres v4 (PRIMES). In South Africa, the\n\ndata are managed by the government and UNHCR manages only the cases for assistance and durable solutions. In Angola, Democratic Republic of the\n\nCongo (DRC), Zambia and Zimbabwe, some portion of the data is not available in ProGres v4. Overall, more than half of refugees and asylum-seekers\n\nin Southern Africa are available in ProGres v4. For IDP data, UNHCR refers to different sources. Specifically, the source of DRC's IDP figure is the", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000078:1:2:2", "start": 927, "end": 935, "surface": "IDP data", "probe_tag": "confusion", "probe_score": 0.8321, "luna_label": 1, "luna_reason": "Existing IDP data sources are declared as underlying UNHCR figures."}]}, {"key": "paddy2-163", "text": " is both restricted and under-reported.\n\nThe limited data on naturalization of refugees available to UNHCR show that during the past\ndecade, more than 1 million refugees were granted citizenship by their asylum country. The\nUnited States of America alone accounted for more than half of them, even though their 2007\nnumbers are not yet available. Azerbaijan and Armenia also granted citizenship to a significant\nnumber of refugees during the same period (188,400 and 65,000 respectively). UNHCR was\ninformed of refugees being granted citizenship in Belgium (12,000), the United Republic of\nTanzania (730), Armenia (700), Finland (570), and Ireland (370).\n\n### **V. Age and sex characteristics**\n\n\nWomen, men, girls and boys have common, but also specific, protection needs. Collecting sexand age-disaggregated information on the population falling under UNHCR’s responsibility is\ntherefore critical for planning, monitoring and evaluating humanitarian interventions and\nprogrammes. Demographic information on displaced populations, however, is not always\navailable for all countries. It tends to be more available in countries where UNHCR is\noperationally active and less in developed countries where States are responsible for data\ncollection.\n\nAvailability of demographic data also varies, depending on the type of population. It is high for\nrefugees (available for 70%) and returnees (89%) and low for returned IDPs (7%), Others of\nconcern (10%), and stateless persons (28%). The availability also differs by region. In Asia and\nthe Americas, demographic data are available for about three quarters of the population falling\nunder UNHCR’s responsibility. In Africa, demographic information was reported for about half\nof the population, in Europe for one quarter (see Table 2 below). <sup>21</sup>\n\n20 Resettlement statistics for the United States of America may also include persons resettled for the purpose of family\nreunification.\n21 The geographical regions", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000651:10:1:1", "start": 1546, "end": 1562, "surface": "demographic data", "probe_tag": "confusion", "probe_score": 0.1281, "luna_label": 1, "luna_reason": "Availability figure reports demographic data coverage for the Americas."}, {"key": "reliefweb:000651:10:1:2", "start": 1805, "end": 1828, "surface": "Resettlement statistics", "probe_tag": "confusion", "probe_score": 0.8322, "luna_label": 1, "luna_reason": "Statistics are qualified by a concrete claim about possible family-reunification cases."}]}, {"key": "paddy2-164", "text": "Country Overview - ANGOLA\n\n###### Needs and Vulnerabilities\n\n\nIn 2021, the situation in the DRC, particularly in the Kasai region, is expected to remain unstable with continuous\n\nintra-communal conflicts and political disputes, requiring from RRRP partners continuous efforts on emergency\n\npreparedness. However, UNHCR does not foresee any major influx from DRC, although a small-scale but steady\n\ninflow of refugees will continue to cross into Angolan territory. According to the most recent intentions survey, only a\n\nminority of refugees – estimated approximately 1,000 – are willing to return voluntarily to DRC. Therefore, the\n\nCongolese refugee population in Lóvua settlement, as well as in other urban areas will remain largely unchanged,\n\nwith Lóvua settlement hosting around 6,600 Congolese refugees throughout 2021. Discussions continue with the\n\nGovernment of Angola to relocate the refugee population from Lóvua settlement to a new location. If the\n\nGovernment does not proceed with the relocation, RRRP partners will continue to focus on improving infrastructure\n\nas a way of ensuring minimum standards are met, while also investing further in livelihoods, peaceful coexistence\n\nand expanding community self-management structures. This will contribute to boosting refugees’ resilience.\n\n\nThere are challenges to asylum space for new arrivals and urban refugee groups in the country, especially in Lunda\n\nNorte. This has been exacerbated by the closure of borders due to the COVID-19 pandemic, during which time\n\ndeportations have continued while no border movements have been allowed since March 2020. This presents a risk\n\nof asylum-seekers being denied access to territory and protection in Angola as well as a heightened risk of\n\nharassment, detentions and refoulement – particularly but not limited to areas close to the border in Lunda Norte.\n\n\nThe average family size in Lóvua settlement is 3.6, with 75 per cent of the population being women and children.\n\nRefugees in Lóvua are biometrically registered with UNHCR, and therefore", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000093:20:0:0", "start": 493, "end": 510, "surface": "intentions survey", "probe_tag": "confusion", "probe_score": 0.7929, "luna_label": 1, "luna_reason": "Existing survey supports the finding that few refugees intend to return."}]}, {"key": "paddy2-165", "text": "5. Cross Sectors\n\n\n### **5 Cross Sectors**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**5.1** **Gender**\n\n\nGender considerations matter in the majority of the policy sub-dimensions. The four priority areas in which\ngender considerations are most consequential in terms of socioeconomic development are as follows:\n\n\ni. **Social cohesion**, the lack of meaningful participation of women in refugee community-based leadership\n\nstructures;\n\n\nii. **Justice and security**, the lack of effective prevention and remedial measures for gender-based\n\nviolence, including access to legal remedies and securing comprehensive solutions that improve the\nsafety of survivors and promote their social rehabilitation;\n\n\niii. **Education**, the drastic drop in school attendance by girls at all levels; and\n\n\niv. Health care, the difficulty urban refugee women have in accessing sexual and reproductive health\n\nservices for free.\n\n\n**5.2** **Social inclusion**\n\n\nThe priority areas in which considerations of refugees’ distinct characteristics are most consequential in\nterms of socioeconomic development are as follows:\n\n\ni. Social protection, the lack of practical integration of elderly and disabled refugees in the emerging\n\nnational social safety nets\n\n\nii. **Health care**, limitations on refugees accessing health-care services legally available to them and the\n\nneed to expand inclusion in national health care programmes\n\n\niii. **Freedom of movement**, barriers on refugee freedom of movement continue to exist in practice and\n\nimpact upon refugees’ self-reliance\n\n\n    - The refugee numbers reported here do not fully match the numbers on the front page because demographic characteristics are not\navailable for all refugees (e.g., pre-registered refugees, etc.).\n\n\nR E F U G E E P O L I C Y R E V I E W F R A M E W O R K - C O U N T R Y S U M M A R Y > **B U R U N D", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000432:12:0:0", "start": 1552, "end": 1567, "surface": "refugee numbers", "probe_tag": "confusion", "probe_score": 0.6912, "luna_label": 0, "luna_reason": "Bare magnitude phrase without an eligible data source noun."}]}, {"key": "paddy2-166", "text": "Adult (15+) literacy rate [%]|ND|57.7|52.8|62.8|98.4|57.4|54.9|91.2|\n|Percentage of women (15+) in<br>labour force|15.7|57.3|66.4|28.8|55.9|54.3|24.4|35|\n|Percentage of men (15+) in<br>labour force|79.7|84.1|76.9|80.9|77.1|63.2|82.9|76.4|\n|Average household size17|7.3|4.68â|4.6|4.8â|7.4|4.9â|6.6|3.9â|\n\n\n_Source: World Bank Data and UNDP_\n\n\n**Table 3:** Comparative country level data: carbon dioxide emissions per capita\n\n\n\n|Col1|Afghanistan|Bangladesh|Bhutan|India|Maldives|Nepal|Pakistan|Sri Lanka|\n|---|---|---|---|---|---|---|---|---|\n|Carbon dioxide emission per<br>capita (tonnes)|0.29|0.37|0.66|1.67|3.3|0.14|0.93|0.62|\n\n\n_Source: UNDP_\n\n\n\n\n\n17 Variety of sources: UNFPA, 2012, <u>http://goo.gl/JY6Yyd; DGHS,2012,</u> <u>http://goo.gl/OJwnA9; Bhutan Multiple Indicator Survey 2010;</u>\nCMIE, 2011, <u", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001169:14:2:0", "start": 314, "end": 329, "surface": "World Bank Data", "probe_tag": "keep", "probe_score": 0.909, "luna_label": 1, "luna_reason": "Source line identifies World Bank data underlying presented comparative indicators."}, {"key": "reliefweb:001169:14:2:1", "start": 752, "end": 784, "surface": "Bhutan Multiple Indicator Survey", "probe_tag": "confusion", "probe_score": 0.7816, "luna_label": 1, "luna_reason": "Named survey cited as a source for comparative country-level data."}]}, {"key": "paddy2-167", "text": "Key Take-Away\n\nIn contrast to the results for other demographic subgroups, receiving a cash transfer or cash+mentorship did not\nresult in refugee women opening new businesses. Therefore, the program had virtually no effect on major business\nsuccess metrics for refugee women. These results may be explained by the high rates of business ownership\namong refugee women at baseline and the challenges with growing existing micro and small enterprises.\n\n\n4.4 The addition of a 1:1 mentorship component to the cash transfer provided modest\n**economic and psychological benefits, but only for Kenyan participants**\n\n\nIf we pool data from all the post-intervention rounds, the mentorship arms increased monthly profits by 26 USD on\naverage, while the cash arm increased profits by 19 USD. This difference was statistically significant and was largely\ndriven by differences in profit for Kenyan men between the cash and the cash+mentorship arms. In the short term,\nKenyan men in the cash+mentorship arms also reported higher levels of productive investments relative to their\ncounterparts in the cash arm. In other words, while Kenyan men were still meeting with their mentors, they invested\nmore of their capital in productive assets. This suggests that Kenyan men may be uniquely positioned to action the\nadvice provided by their mentors.\n\n\nThe mentorship arms also increased participants’ overall network size (i.e., the number of contacts such as other\nbusiness, suppliers, and collaborators with whom clients discuss business/economic things) and the size of their advice\nnetwork relative to the control condition three months after the start of the intervention, but not beyond that. This\nwas true for every demographic subgroup except refugee women, whose networks did not change as a result of the\nintervention.\n\n\nImportantly, the cash+mentorship arms (but not cash alone) improved participants’ psychological well-being three\nmonths after the start of the program and after the cash transfer to participants. This boost in well- being only endured\nuntil the sixth month for Kenyan men and women", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001171:8:0:0", "start": 622, "end": 664, "surface": "data from all the post-intervention rounds", "probe_tag": "confusion", "probe_score": 0.3152, "luna_label": 1, "luna_reason": "Existing post-intervention data support pooled profit analysis and reported effects."}]}, {"key": "paddy2-168", "text": "PROTECTION\n\n\nIn addition, while the data collected through the\nsample do not offer extensive insights about the\nnumber of children under 5 registered with a civil\nauthority, with only 2 respondents declaring their\nchildren have been registered with civil\nauthorities in another country, there are two\nimportant aspects to be discussed. Firstly, the\nquestions from future surveys need to be clearer\nand to offer explanations about the meaning of\ncivil authorities and the process of recording.\nSecondly, the question needs to be splitted, one\nasking if the caregivers have registered the birth\nusing consular services or in Ukraine and another\none asking if they recorded the birth to the\nRomanian civil authorities.\n\nMoreover, when asked about the challenges\nfaced in replacing/renewing identity documents,\nthe most commonly reported issue is long\nprocessing or waiting times, indicated by 45% of\nrespondents, underscoring administrative\ninefficiencies. Restrictions in consular services\nrelated to new mobilization rules affect 35%,\nreflecting policy constraints impacting document\naccessibility. Additionally, 18% reported that the\ndocuments are not issued in the host country, but\n\n\n\nneed to be obtained in Ukraine. Financial\nbarriers are also present, with 7% unable to\nafford administrative or associated costs. A lack\nof knowledge about the procedure (5%) and\nabsence of supporting documents (3%) further\ncomplicate the process. These findings\nemphasize the importance of reducing\nbureaucratic backlogs with consular services and\nthe cost of renewing identity documents. The\nrestrictions relating to the new mobilization\nrules are also a significant source of concern and\nuncertainty among those who are affected by\nthem. Equally important, when asked about the\ndocuments needed to be replaced since their\ndeparture from Ukraine, the international\nbiometric passports (32%), the internal\npassports (9%) and the ID cards (3%) were the\noptions frequently mentioned. However, 52% of\nrespondents chose the “none of the above”\noption, indicating that either the question was\nnot properly understood or there may be other\ndocuments not listed in the response options, or\nthey were not in", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001333:35:0:0", "start": 36, "end": 69, "surface": "data collected through the\nsample", "probe_tag": "confusion", "probe_score": 0.6361, "luna_label": 1, "luna_reason": "Collected sample data supports a concrete finding about birth registration."}]}, {"key": "paddy2-169", "text": "hcr.org/statistics/populationdatabase)</u>\n\n18 As demographic breakdown was not available for 2013 at the time of writing, this percentage\nbreakdown has been extrapolated from 2012 data. UNHCR, _Statistical Yearbook 2012_, “Table 14:\nDemographic composition of refugees and people in refugee-like situations, end 2012”, p126.\n\n19 Member states of the Council of Europe, and most other industrialized states formally grant the\nright to work, along with many other social and economic rights to recognized refugees. As well as\nEuropean states, Australia, Canada, New Zealand, and the USA grant refugees the right to work.\nThe rights granted to asylum seekers vary considerably. Other countries recognizing in legislation\nthe right to work of refugees include Burundi, Cameroon, Democratic Republic of Congo, Gabon,\nGuinea, Mali, Mauritania, Republic of South Africa, Rwanda, Senegal, Uganda, Argentina, Brazil,\nPeru, Ecuador, Mexico, Bolivia, Paraguay, Chile, Panama, Venezuela, Costa Rica, Uruguay, Israel.\n\n11", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:reliefweb:001036:10:3:0", "start": 19, "end": 37, "surface": "populationdatabase", "probe_tag": "keep", "probe_score": 0.9814, "luna_label": 0, "luna_reason": null}, {"key": "sample:reliefweb:001036:10:3:1", "start": 176, "end": 185, "surface": "2012 data", "probe_tag": "confusion", "probe_score": 0.8868, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-170", "text": "\nfollowed a parent who had arrived in the destination area before\nthem (FGDs in Tripoli), or had numerous relatives in the area\n(FGDs in Tripoli and Akkar). Several participants counted men\nwho were married to Lebanese women from Tripoli or Zahle\n(FGDs in Tripoli and Zahle).\n\n\n\nsurveyed households fell in this category, indicating that they\ncame to Lebanon before 2011, mostly for work but also to visit\nrelatives ( **Figures 9** and **10** ). These figures further suggest that\nthis pattern of migration connected workers from lower-income\nneighbourhoods in Homs (UFAs 1, 3 and 5) to Lebanese cities\nand towns (e.g. Zahle) following employment opportunities,\nwhile middle-income groups (from UFAs 2 and 4 in Homs)\nhad mainly come to Lebanon to visit family members, staying\nmostly in the northern regions, especially in Tripoli, but also in\nAkkar and Minieh-Dennieh. In total, 1,056 or almost 70 percent of\nhouseholds considered networks of importance in the selection\nof a particular district for their shelters. Furthermore, around 40\npercent of respondents across all regions described proximity to\nrelatives or community as a main factor motivating their district\nof choice; a proximity they mostly balanced with the imperative\nof affordability ( **Table 2** ).\n\n\nSurveyed\n\n\n\nMount\nLebanon\n\n\n\nSouth\n\n\n\nNorth Akkar\n\n\n\nBekaa Baalbek\nHermel\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<mark>18</mark>", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000666:16:2:0", "start": 248, "end": 273, "surface": "FGDs in Tripoli and Zahle", "probe_tag": "confusion", "probe_score": 0.8044, "luna_label": 1, "luna_reason": "Focus group discussions support participant findings about migration and family networks."}]}, {"key": "paddy2-171", "text": "Cooking in Displacement Settings: Engaging the Private Sector in Non-wood-based Fuel Supply\n\n\nneeds. It is likely that the figure for average energy usage calculated here is low, since in\na displacement setting people are constrained by resources and cook less than they would\nlike to.\n\n\n**•** The survey was conducted in Kakuma I, which is the oldest and most established subcamp within the Kakuma complex. The results seen in Kakuma I may not be fully reflective\nof the stove type, fuel use, cooking spend, income and general expenditures seen across\nthe remaining camp areas. Projections across the full camp complex are provided as\nestimations only.\n\n\n44   movingenergy.earth", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:reliefweb:000683:44:0:0", "start": 298, "end": 330, "surface": "survey was conducted in Kakuma I", "probe_tag": "confusion", "probe_score": 0.8418, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-172", "text": " been excluded from this review. This is the case for two main reasons: 1) we did not want this work\n[to overlap with work being done on refugee financing and associated data, for example, from Save the Children (2023), as well as work from the World Bank and UNHCR](https://resourcecentre.savethechildren.net/document/the-price-of-hope/)\n(2021).; and 2) as a result, this review did not include an explicit focus on data on financing (e.g. government budgets, ODA, humanitarian aid allocations from sources\nsuch as OCHA Financial Tracking Services, the OECD Creditor Reporting Service, or International Aid Transparency Initiative data) in order not to expand the number of\nDCEs to an unmanageable level.\n\n**16**", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000382:15:3:0", "start": 516, "end": 548, "surface": "OCHA Financial Tracking Services", "probe_tag": "confusion", "probe_score": 0.7593, "luna_label": 0, "luna_reason": "Named data service is cited as an excluded example, with no demonstrated data use."}, {"key": "reliefweb:000382:15:3:1", "start": 554, "end": 585, "surface": "OECD Creditor Reporting Service", "probe_tag": "confusion", "probe_score": 0.5562, "luna_label": 0, "luna_reason": "Named reporting service is mentioned as an excluded financing-data source, without data use."}]}, {"key": "paddy2-173", "text": "COMMUNITY PERCEPTION SURVEY ANALYSIS 2024\n\n# **CONTENTS**\n\n\nUNHCR Somalia / June 2025 2", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000151:1:0:0", "start": 0, "end": 27, "surface": "COMMUNITY PERCEPTION SURVEY", "probe_tag": "confusion", "probe_score": 0.5151, "luna_label": 0, "luna_reason": "Survey title alone shows no existing data use or attributed finding."}]}, {"key": "paddy2-174", "text": "accurate enumeration, and urged that generous overestimates would suffice. In still another\ncase, UNHCR field staff attempting a sample survey have been criticized by voluntary agency\nstaff for their ‘intrusive bureaucracy’.” <sup>17</sup> [^17: P. Romanovsky and R. Stephenson, ‘A review of refugee enumeration: proposals for the\ndevelopment of a unified system’, UNHCR, Geneva, September 1995, p. 3.]\n\n\n**The politics of refugee numbers**\n\n\nHow does politics impinge upon the collection of comprehensive, reliable and up-to-date\nstatistical data on refugees and other groups of displaced people? The simple answer to this\nquestion is: in many different ways and at many different levels of the international refugee\nregime. Before going on the substantiate that assertion, it should be made clear that this paper\nuses the notion of ‘politics’ in its broadest sense, to denote the efforts of individuals and\ninstitutions to pursue their own interests and to influence the behaviour of others. In the context\nof refugee situations, those actors fall into a number of conventional categories: countries of\norigin; countries of asylum; donor states; refugee populations and humanitarian organizations.\nThis section uses such categories as a convenient (if somewhat simplistic) framework to\nexamine the politics of refugee numbers and to introduce some illustrative case studies, drawn\nmainly from the author’s personal experience over the past 15 years.\n\n\n**_Countries of origin: the Horn of Africa and Uganda_**\n\n\nRefugee movements are in many senses a symbol of political failure. Few states like to\nacknowledge that their citizens have been obliged ‘vote with their own feet’ by leaving their\ncountry of origin, even if that state has deliberately engineered their departure. In some\nsituations, governments address this issue by claiming that the ‘refugees’ who have left the\ncountry are not refugees at all, or that they are not even citizens of that state. The Bhutanese\ngovernment’s explanation of the ethnic Nepali exodus in 1991-92 and the Burmese", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000558:7:0:0", "start": 531, "end": 547, "surface": "statistical data", "probe_tag": "confusion", "probe_score": 0.1449, "luna_label": 0, "luna_reason": "Generic data is discussed as a collection target, without an attributed finding or actual use."}]}, {"key": "paddy2-175", "text": "2Fuser_upload%2FMineduc%2FPublications%2FEDUCATION_STATISTICS%2FEducation_statistical_yearbook%2F&cHash=f4907f021d7175fc28e6cdebcc8bf83a)</u>\n\nUNHCR’s regional and global refugee education data reports, as well as for reporting and\n\n[monitoring of earmarked education projects, such as reports for Educate A Child (EAC),](https://educateachild.org/)\n\n[Albert Einstein German Academic Refugee Initiative (DAFI) scholarship and other regional](https://www.unhcr.org/dafi-scholarships.html)\n\nrefugee response plan.\n### NFI & Shelter\n#### Post Distribution Monitoring (PDM) - UNHCR\n\n\nThe purpose of PDM assessments is to collect feedback from refugees on the quality,\n\nsufficiency, utilization, and effectiveness of assistance received as it relates to shelter. The\n\nPDM is conducted periodically after relief items are distributed. These have been discontinued\n\nby the UNHCR Rwanda Operation since the operation is relying on the JPDM for these data\n\ncollection efforts.\n\n\nThe previous data collection of UNHCR PDMs are solely qualitative with a combination of FGDs\n\nand KIIs. However, they have not been systematically collected and documented. No resources\n\nare publicly available.\n\n\n\nUNHCR / June 2022 / Version 1\n\n\n\n11", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001182:10:2:0", "start": 151, "end": 201, "surface": "regional and global refugee education data reports", "probe_tag": "confusion", "probe_score": 0.5443, "luna_label": 1, "luna_reason": "UNHCR reports are existing data resources used for reporting and monitoring."}, {"key": "reliefweb:001182:10:2:1", "start": 927, "end": 931, "surface": "JPDM", "probe_tag": "drop", "probe_score": 0.0457, "luna_label": 0, "luna_reason": "Names a data-collection mechanism without showing existing data being used."}]}, {"key": "paddy2-176", "text": "|-|-|121,368|\n|Syrian Arab Rep.³⁴|16,213|-|16,213|12,069|94,977|6,146,994|477,360|160,000|30,971|-|6,938,584|\n|<br>Tajikistan|3,791|-|3,791|1,413|-|-|-|7,151|-|-|12,355|\n|Thailand³⁵|50,067|47,504|97,571|847|-|-|-|475,009|119|-|573,425|\n|Timor-Leste|-|-|-|-|-|-|-|-|-|-|-|\n|Togo|11,968|-|11,968|696|30|-|-|-|-|-|12,694|\n|Tonga|-|-|-|1|-|-|-|-|-|-|1|\n|Trinidad and Tobago|2,321|-|2,321|17,367|-|-|-|-|200|7,664|27,552|\n|<br>Tunisia|1,746|-|1,746|1,523|-|-|-|-|17|-|3,286|\n|Turkey³⁶|3,579,531|-|3,579,531|328,257|-|-|-|1|-|-|3,907,789|\n\n\nUNHCR > **GLOBAL TRENDS 2019** 75", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001657:74:5:0", "start": 545, "end": 563, "surface": "GLOBAL TRENDS 2019", "probe_tag": "drop", "probe_score": 0.0338, "luna_label": 0, "luna_reason": "Report heading adjacent to tabulated figures, not an independent data-use mention."}]}, {"key": "paddy2-177", "text": "### 6\n\n#### Table of content\n\n\n**[1]** **Introduction** **7**\n\n\n**[2]** **Profile** **9**\n\n\n[2.1] General description 9\n\n[2.2] Key demographic, cultural, social and economic data 11\n\n[2.3] Natural hazards 17\n\n[2.4] Environment and climate change impacts 21\n\n[2.5] Humanitarian crisis and shelter sector response 22\n\n\n**[3]** **Access to land, housing, and basic services** **26**\n\n\n[3.1] Overview of access to land and housing 26\n\n[3.2] Access to water, sanitation, and other services 28\n\n\n**[4]** **Description of local housing and settlements** **31**\n\n\n[4.1] Households’ description 31\n\n[4.2] Settlements 31\n\n[4.3] Cultural aspects in housing 37\n\n[4.4] Summary of local affordable construction types 38\n\n[4.5] Construction materials and techniques 47\n\n[4.6] Organization of construction 51\n\n\n**[5]** **Analysis of local building practices** **52**\n\n\n[5.1] Lifespan, maintenance and adaptation 52\n\n[5.2] Bioclimatic comfort 53\n\n[5.3] Environmental issues 56\n\n[5.4] Hazard-resistant practices 57\n\n[5.5] Health and hygiene issues related to housing 59\n\n[5.6] Use and aesthetics 60\n\n[5.7] Economic aspects 60\n\n[5.8] Socio-cultural practices that promote resilience 61\n\n[5.9] Improvable building practices and recommendations 62\n\n\n**[6]** **Projects based on local building practices** **64**\n\n\n[6.1] Qatar red crescent / Binaa – (idp", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001407:5:0:0", "start": 131, "end": 178, "surface": "demographic, cultural, social and economic data", "probe_tag": "drop", "probe_score": 0.0203, "luna_label": 0, "luna_reason": "Table-of-contents heading, not a cited or used data resource."}]}, {"key": "paddy2-178", "text": " health related data in a\n\nstandardized manner, albeit the sampling tends to focus on a specific subgroup of the refugee\n\npopulation (households with children under 5 years old, and households with members with\n\nadolescent girls, pregnant and lactating mothers); with the exception of two rounds of SENS\n\nsurvey that is representative of the entire refugee population. In addition to the SENS survey,\n\nthe recent JPDM is another survey, that informs us regularly on the state of food security of\n\nrefugees that relies on a relatively robust Food Consumption Score (FCS) measure.\n\n\nFigure 2: Overview of data mapping on POCs in Rwanda, by sector/theme\n\n\nUNHCR / June 2022 / Version 1", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:reliefweb:001182:17:1:0", "start": 1, "end": 20, "surface": "health related data", "probe_tag": "drop", "probe_score": 0.0022, "luna_label": 0, "luna_reason": null}, {"key": "sample:reliefweb:001182:17:1:1", "start": 299, "end": 311, "surface": "SENS\n\nsurvey", "probe_tag": "drop", "probe_score": 0.0002, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:001182:17:1:2", "start": 388, "end": 399, "surface": "SENS survey", "probe_tag": "confusion", "probe_score": 0.6193, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:001182:17:1:3", "start": 413, "end": 417, "surface": "JPDM", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-179", "text": " Use Therapeutic Food<br>|\n|SAM<br>|Severe Acute Malnutrition<br>|\n|SC<br>|Stabilization Centre<br>|\n|SENS<br>|Standardised Expanded Nutrition Survey<br>|\n|SFP<br>|Supplementary Feeding Program<br>|\n|SMART<br>|Standardised Monitoring and Assessment of Relief and Transitions<br>|\n|TFP<br>|Therapeutic Feeding Program<br>|\n|TSFP<br>|Target Supplementary Feeding Program<br>|\n|UNHCR<br>|United Nations High Commissioner for Refugees<br>|\n|UNICEF<br>|United Nations Children's Fund<br>|\n|WFP<br>|World Food Program<br>|\n|WHO<br>|World Health Organization<br>|\n|WHZ|Weight-for-Length/Height Z-Score|", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001340:2:1:0", "start": 111, "end": 149, "surface": "Standardised Expanded Nutrition Survey", "probe_tag": "drop", "probe_score": 0.0089, "luna_label": 0, "luna_reason": "Survey acronym is merely defined in a glossary, with no data use shown."}]}, {"key": "paddy2-180", "text": " Sudan)<br>   South West-Burundi(SW-Burundi)<br>   South West-DRC(SW-DRC)<br>   South West-South Sudan(SW-South Sudan)<br>   South West-Somalia(SW-Somalia<br>   West Nile-South Sudan(WN-South Sudan)<br>Data from the 2018 representative refugee household survey was used to<br>calibrate the weights for the URHFPS.|The displaced sample is representative at seven strata constructed as a<br>combination of country of origin and region:<br>   Kampala-Somalia<br>   Kampala-other (Burundi, DRC, South Sudan)<br>   South West-Burundi(SW-Burundi)<br>   South West-DRC(SW-DRC)<br>   South West-South Sudan(SW-South Sudan)<br>   South West-Somalia(SW-Somalia<br>   West Nile-South Sudan(WN-South Sudan)<br>Data from the 2018 representative refugee household survey was used to<br>calibrate the weights for the URHFPS.|The displaced sample is representative at seven strata constructed as a<br>combination of country of origin and region:<br>   Kampala-Somalia<br>   Kampala-other (Burundi, DRC, South Sudan)<br>   South West-Burundi(SW-Burundi)<br>   South West-DRC(SW-DRC)<br>   South West-South Sudan(SW-South Sudan)<br>   South West-Somalia(SW-Somalia<br>   West Nile-South Sudan(WN-South Sudan)<br>Data from the 2018 representative refugee household survey was used to<br>calibrate the weights for the URHFPS.|\n|", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000604:54:1:0", "start": 216, "end": 260, "surface": "2018 representative refugee household survey", "probe_tag": "drop", "probe_score": 0.0239, "luna_label": 1, "luna_reason": "Existing survey data calibrated URHFPS weights."}]}, {"key": "paddy2-181", "text": "**UNHCR recommends the Government of Bulgaria to:**\n\n\n- **Amend legislation to ensure effective access to rights** for individuals in the SDP and those\ngranted stateless status, particularly by removing legal barriers that restrict access to the\nprocedure.\n\n- **Review and consider lifting remaining reservations to the 1954 Convention**, especially those\nrelated to identity and travel documents in line with Bulgaria’s pledges made during the 2023\nGlobal Refugee Forum.\n\n- **Provide free legal assistance to stateless people and people at risk of statelessness**, supporting\ntheir access to nationality, civil status registration, and identity procedures and documents, and\nempowering them to claim their rights. This includes ensuring that free legal assistance is also\navailable at the administrative stage of the SDP.\n\n- **Amend primary and secondary legislation to ensure effective access to rights** for applicants for\nstatelessness status and those granted statelessness status, such as access to national health\ninsurance, employment and social assistance programs.\n\n- **Ensure the collection and recording of data on statelessness throughout the migration**\n**management and asylum process** to protect people against arbitrary detention, and ensure they\nare provided with appropriate assistance. The collection and recording of statelessness data will\nalso assist Bulgaria with their reporting obligations under the EU Pact on Migration and Asylum.\nConsider conducting a comprehensive mapping survey to improve the quantitative data and\nqualitative analysis of the situation of stateless population residing in Bulgaria and engage with\nthe ongoing UNHCR exercise on mapping statelessness in Bulgaria.\n\n- **Join the Global Alliance to End Statelessness**, a collaborative multistakeholder platform, which\nbrings together Governments, regional intergovernmental organizations, stateless-led and civil\nsociety organizations and other stakeholders to increase collective advocacy efforts, catalyse\npolitical commitments and accelerate action to secure permanent solutions to statelessness.\n\n\n**With respect to undocumented Roma communities:**\n\n\n- Provide resources and clear guidance to municipalities and cooperate with civil society", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:reliefweb:000842:6:0:0", "start": 1119, "end": 1140, "surface": "data on statelessness", "probe_tag": "confusion", "probe_score": 0.1273, "luna_label": 0, "luna_reason": null}, {"key": "sample:reliefweb:000842:6:0:1", "start": 1339, "end": 1357, "surface": "statelessness data", "probe_tag": "confusion", "probe_score": 0.0724, "luna_label": 0, "luna_reason": null}, {"key": "sample:reliefweb:000842:6:0:2", "start": 1482, "end": 1510, "surface": "comprehensive mapping survey", "probe_tag": "drop", "probe_score": 0.0145, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-182", "text": "c-istatistikleri](https://www.sg.gov.tr/duzensiz-goc-istatistikleri)\n[6 Turkish Coast Guard, https://www.tsk.tr/Home/GunlukFaaliyetler](https://www.tsk.tr/Home/GunlukFaaliyetler)\n\n\nUNHCR / January 2024 13", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000759:12:2:0", "start": 0, "end": 16, "surface": "c-istatistikleri", "probe_tag": "drop", "probe_score": 0.0133, "luna_label": 0, "luna_reason": "Fragment of a URL citation, not an independently usable data resource."}]}, {"key": "paddy2-183", "text": " to Commission_\n_(on Human Rights) Resolution 1997/39_, United Nations, 1998, E/CN.4/1998/53/Add2.\n\n\n**44** This sub-category is descriptive in nature, and includes groups of people who are inside their country of nationality or habitual residence, and who face protection risks similar to\nIDPs but who, for practical or other reasons, could not be reported as such.\n\n\n\n**36** UNHCR Global Trends 2011 **UNHCR Global Trends 2011** **37**", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001077:18:4:1", "start": 377, "end": 401, "surface": "UNHCR Global Trends 2011", "probe_tag": "drop", "probe_score": 0.0497, "luna_label": 0, "luna_reason": "Standalone report title without cited finding or demonstrated data use."}]}, {"key": "paddy2-184", "text": " ente los refugiados\nacogidos. Entre los países que reportaron datos\ndesglosados por sexo en 2018 para más de\n1,000 refugiados, Serbia y Kosovo (S/RES/1244\n(1999)) y Bosnia y Herzegovina tuvieron la mayor\nproporción femenina con un 58%, seguido de\nTogo, con 56%, y Nigeria y Chad con el 55%. La\nmenor proporción fue reportada por Ecuador, un\n24%, seguido de Malta (27%), Indonesia (28%) y la\nRepública de Corea (29%).\n\n\nLa proporción de menores entre la población\nrefugiada también varió ampliamente en 2018.\nEntre los países que reportan datos desglosados\npor edad para más de 1.000 refugiados, la RDC\nreportó la mayor proporción de menores de 18\naños con un 63%, seguida de Sudán del Sur\n(62%) y Uganda (62%), lo que refleja la joven\nestructura de edad de la población de muchos\npaíses de la región. La menor proporción fue\nreportada en 2018 por Serbia y Kosovo (S/\nRES/1244 (1999)), con sólo alrededor del 1 por\nciento de la población, seguidos de Bosnia y\nHerzegovina (6%) y Argentina (9%).\n\n\nEstas diferencias también se aprecian a nivel regional\n\n[gráfico 22]. La proporción más baja de menores y\nmujeres se vio entre la población de refugiados\nen Europa, donde solo el 44% de la población\n\n\n\n60 ACNUR > **TENDENCIAS GLOBALES 2018** ACN", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:reliefweb:000519:30:4:0", "start": 63, "end": 89, "surface": "datos\ndesglosados por sexo", "probe_tag": "confusion", "probe_score": 0.4462, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000519:30:4:1", "start": 539, "end": 565, "surface": "datos desglosados\npor edad", "probe_tag": "drop", "probe_score": 0.0411, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-185", "text": "alojamiento de los NNAS. Sin embargo, al no contar\ncon un espacio privado <sup>59</sup> en donde implementar los\ncuestionarios individuales, se privilegió la realización\nde discusiones grupales. De tal forma que en esta\nestación se obtuvieron 65 cuestionarios individuales\ny se abordaron 170 NNAS de forma grupal.\n\nA pesar de las restricciones institucionales, esta\ninvestigación procuró establecer un perfil de los niños,\nniñas y adolescentes a entrevistar que involucrara las\nsiguientes variables: nacionalidad, género, edad y\ncondición étnica. Cabe aclarar que por la naturaleza\nde la dinámica institucional impuesta y debido a las\ncaracterísticas propias del flujo de NNAS, el cual es\naleatorio y poco consistente, no se pudo establecer\nuna muestra que fuera representativa del flujo de\nNNAS centroamericanos en México. Por tal razón,\nlos resultados numéricos presentados refieren\núnicamente a la tendencia marcada para los 72 NNAS\nque participaron del cuestionario individual.\n\nEsta restricción institucional incluyó el no acceso a\nlas estaciones migratorias con grabadoras, cámaras\n\n- material tecnológico de registro, los cuáles son\nherramientas fundamentales para la recolección\nde información sistemática desde la perspectiva\ncualitativa. Por ello, el análisis de la información obtenida\na través del método de discusión grupal se resguardó\nen fichas de registro diseñadas específicamente para\neste estudio, en las cuales se vació la información\nobten", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001434:17:0:0", "start": 1353, "end": 1371, "surface": "fichas de registro", "probe_tag": "drop", "probe_score": 0.0466, "luna_label": 0, "luna_reason": "Study-specific registration sheets record information generated by the research exercise."}]}, {"key": "paddy2-186", "text": "\na lack of understanding, expertise or medication for\nthe treatment of chronic illnesses.\n\n\n**Case study: West Darfur, Sudan**\n\nBy 2011, the Darfur emergency of 2003/4 had become\na protracted humanitarian crisis, with as many as\n2 million people becoming internally displaced –\nmany living in camps throughout Darfur. Of these, an\nestimated 8 per cent of the camp population were made\nup of older people.\n\nHelpAge had worked in West Darfur since 2004.\nIn 2005/6, it carried out a series of assessments and\nsurveys to consult older people about their\nvulnerabilities and health and nutrition needs. <sup>19</sup>\nResults showed that older people in Darfur were not\naccessing health services despite clinics being\navailable. This was for a number of complex reasons.\nMany older people were experiencing isolation and\nneglect, and were excluded from food aid and health\nprogrammes, while others with mobility concerns\nlacked transport. These factors left many older people\nreticent and unable to seek medical care.\n\nIn response to this gap in health services provision,\nHelpAge established a roster of community health\nworkers to visit housebound older people, providing\ncare and referral as required. They also introduced a\ndonkey cart ambulance to transport older people to\nclinics for emergency care. Another initiative involved\ndistributing supplementary food baskets to older people\nat risk of malnutrition, or who were caring for multiple\ndependents.", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:reliefweb:001104:5:2:0", "start": 490, "end": 513, "surface": "assessments and\nsurveys", "probe_tag": "drop", "probe_score": 0.0141, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-187", "text": "¨ **Increased awareness among the population of HIV/AIDS transmission and methods of**\n**prevention**\n¨\nThere have been considerable achievements in knowledge: the indicator that at least 50% of the target\npopulation is able to cite two acceptable ways of protection from HIV has been met (aggregated 78% of\nwomen and 90% of men know 2 or more programmatic ways of avoiding the disease although gender gaps\npersist) Abstinence based on a spontaneous answers, condoms and reduced partners after prompting to cite\nspecific methods; in a nationally representative sample survey of 7,246 women aged 15-49 and 1,962 men\naged 15-54.\n\n\n**<u>Table 1: Knowledge of HIV Prevention by Gender in Uganda 2000/01</u>**\n\n|Prevention Method|Men|Women|\n|---|---|---|\n|Using Condoms|83%|69%|\n|Abstinence|65%|50%|\n|One Sexual Partner|91%|84%|\n\n\n\n**Source** UDHS 2000/20001\n\n\nThere are also poverty gaps showing the need to strengthen the pro-poor targeting of IEC messages: 25%\nof women and 15% of men with no education do not know any way to prevent AIDS compared with 2% of\nboth women and men with secondary education who know no method; as well as marked rural/urban\ndifferentials (DHS 2000/01).\n\n\nWhile there was an initial delay in sexual debut amongst males quoted as from 14-16 years in selected\nKAPB study sites, the UDHS 2000/01 only shows delayed sexual debut for men: the median age of first\ncoitus for men and women aged 20-49 years was 18.8 and 16.7 years. There has been no change for\nwomen. For males delayed debut is inferred by looking at age subsets: men aged 50-54 have", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:019022:34:0:1", "start": 838, "end": 842, "surface": "UDHS", "probe_tag": "confusion", "probe_score": 0.8711, "luna_label": 1, "luna_reason": "Named survey cited as the source for the table's HIV prevention findings."}]}, {"key": "paddy2-188", "text": "In addition to describing who is credit constrained and how firms finance themselves, we\n\n\nalso analyze the link between access to credit and firm performance and the association between\n\n\naccess to credit -at the firm level- and equivalent macro variables. First, we find that firms with\n\n\nhigher performance, as measured by labor productivity, are less likely to be credit constrained,\n\n\nwhich we take as an indication of well-functioning financial markets. A closer examination of\n\n\nthis result shows that this relationship is weaker for small firm than for medium and large firms.\n\n\nSecond, we find that countries with a higher level of private credit-to-GDP ratios have on\n\n\naverage lower percentages of firms that are credit constrained. These results are based on\n\n\ncorrelations and should not be interpreted as causal.\n\n\nThe structure of the paper is as follows. The next section describes the data set being used\n\n\nin detail, highlighting its richness and uniqueness. Section 3 explains the grouping of firms\n\n\naccording to their level of being credit constrained. Section 4 presents both the descriptive results\n\n\nand the regression analysis on the determinants of being credit constrained. Finally, section 5\n\n\nconcludes the paper.\n\n#### **2. Data**\n\n\nAs part of its strategic goal of building a climate for investment, job creation, and\n\n\nsustainable growth, the World Bank has promoted improving business environments as a key\n\n\nstrategy for development, which has led to a systematic effort in collecting enterprise data across\n\n\ncountries. The Enterprise Surveys (ES) are an ongoing World Bank project in collecting both\n\n\nobjective data based on firms’ experiences and enterprises’ perception of the environment in\n\n\nwhich they operate. The studies are implemented using firm-level surveys and over the last 10\n\n\nyears have evolved into a mature product that since 2005 uses a standardized methodology of\n\n4", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:005797:5:0:3", "start": 1787, "end": 1805, "surface": "firm-level surveys", "probe_tag": "confusion", "probe_score": 0.7454, "luna_label": 0, "luna_reason": "Generic surveys are mentioned methodologically without an attributed finding."}]}, {"key": "paddy2-189", "text": "The role of the Gender Focal Points is to support their nominating sector to incorporate and monitor\ngender equality measures. The Network uses a range of strategies to support its members, including\npeer-learning, information sharing, coaching, training, training others, and sharing useful resources.\nFor more detailed info on the network, please see the Sector Gender Focal Points Network page at\n<u>https://data2.unhcr.org/en/working-group/47</u>\n\n\nThe network assists all refugee sectors, UN agencies and INGO/NGO partners that are part of the Syria\nRefugee Response in Jordan, to ensure that women, girls, boys and men have equitable access to\nhumanitarian assistance through the ADAPT & ACT C Framework.\n\nThe **ADAPT & ACT C** Framework is a simple tool to help project staff review their projects or actions\nwith a gender equality lens. All nine steps should be used to validate that the actions address the equal\nneeds of women, girls, boys and men in the humanitarian response. The framework captures the key\nprinciples that underpin gender mainstreaming in humanitarian action:\n\n  - **A** nalyse gender roles and responsibilities;\n\n  - **D** esign services that meets everyone’s needs;\n\n  - **A** ccess to services for Women, Girls, boys and Men;\n\n  - **P** articipation of women and men is ensured;\n\n  - **T** raining should benefit men and women equally;\n\n  - **A** ddress Gender-Based Violence in sector programmes;\n\n  - **C** ollect, analyse and report sex- and age-disaggregated data (SADD);\n\n  - **T** arget actions based on a gender analysis;\n\n  - **C** oordinate actions with all partners.\n\n\nThere is a series of resources at the disposal of sector coordinators and working", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001427:3:0:0", "start": 1468, "end": 1499, "surface": "sex- and age-disaggregated data", "probe_tag": "confusion", "probe_score": 0.4277, "luna_label": 0, "luna_reason": "Framework instructs collecting and reporting data; no existing data are used."}]}, {"key": "paddy2-190", "text": "up>14</sup> At the lower secondary level, barely any progress has been made\nto increase enrollment since 2000 (Figures 4 and 5). This is considerably worse than most countries in the region.\nUganda’s GER for lower secondary has not moved beyond 35 percent since 2010 (Figure 4). Very low enrollment\nrates in secondary education and the lack of progress require an urgent, emergency-like response.\n\n\n9 UNESCO 2014, Teacher Issues in Uganda: A shared vision for an effective teachers’ policy.\n10 Uganda job diagnostics/strategy, World Bank, 2018, draft.\n11 Bashir S., Lockheed M., Ninan Dulvy E., Tan J.P. Facing Forward: Schooling with Learning in Africa. World Bank, Washington DC, 2017.\n12 While in December 2019, Uganda Bureau of Statistics completed a mapping exercise of all education institutions in the country, until now the data has\nnot been officially released and is still being validated, and therefore was not included in this document. Instead, the 2017 EMIS is used as the source of\nthe most recent government data.\n13 World Development Report, 2018.\n14 UNESCO Institute of Statistics.\n\n\nPage 9 of 96", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000060:14:2:0", "start": 962, "end": 971, "surface": "2017 EMIS", "probe_tag": "confusion", "probe_score": 0.6537, "luna_label": 1, "luna_reason": "2017 EMIS is explicitly used as the source of recent government data."}]}, {"key": "paddy2-191", "text": "➢❨¢ List of key performance indicators (KPIs) identified including metrics of disease burden,\nequity and efficiency of health sector, as well as health financing and economic metrics. The KPI\nand\nhealth metrics will be constructed using internationally accepted best practice\n➢❨¢ National Health Accounts (NHA) analysis and report finalized\n➢❨¢ Improved capacity of SD staff in in the areas of statistical analysis, health policy analysis\nand formulation, and National Health Accounts\n➢❨¢ An ICT system for ensuring interoperability of the existing databases\n\n\n**III.** **Preliminary Description**\n\n**Concept Description**\nProposed Activities:\n\nThe MoPH recognizes that data and information management is vital to the success of planned\nreforms to improve the efficiency and access to health services, address equity, and improve\ntransparency and governance in key areas, including hospital and primary health care, morbidity and\nmortality, and health financing. To achieve these objectives, the MoPH collaborated in several\nprojects in the past with several agencies mainly with World Health Organization (WHO) and the\nUnited Nations Population Fund (UNFPA). This included the work on births and deaths➢❨ data\ncollection from the Ministry of Interior and Municipalities (MOIM) through MOPH district health\noffices; and the Maternal Neonatal Mortality Notification System, which collects data from\nhospitals on maternal and neonatal deaths. Currently, the SD is collaborating with WHO in a major\ninitiative aimed at collecting certificates of death for the Beirut Governorate through the MOIM.\n\nThe proposed program will build on these achievements as well as on past and existing WB projects\nin Lebanon, namely:\n\ni) The Second Emergency Social Protection Implementation Support Project (P111849),\nComponent II: Rationalize Health Sector Expenditures. One of the objectives of this component was\nto improve the efficiency of MOPH hospital expenditures through the Automation of the Billing\nSystem (ABS) and the establishment of a system for performance-based contracting with hospitals.\nii", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000046:2:0:0", "start": 1324, "end": 1371, "surface": "Maternal Neonatal Mortality Notification System", "probe_tag": "confusion", "probe_score": 0.8836, "luna_label": 0, "luna_reason": "Named notification system is mentioned without showing its data being used."}]}, {"key": "paddy2-192", "text": " and the specific resettlement site in particular. The secondary data was\ncollected from previous studies on social, economic, environmental and physical situation of the\nhistoric and cultural sites. Primary data was collected through site visits and discussions with\nrelevant stakeholders.\n\n#### **_Public consultation_**\n\nConsultation with various stakeholders was an integral part of this environmental impact\nassessment study. The community in the Core Zone and the host community were consulted about\nthe resettlement area. The PAPs were not happy about the relocation site at first stance as they\nthought it was far and a nearer location could be found. However, through discussions, Kurakur\nwas found to be the best possible relocation site. Social acceptability of the resettlement has a\ngreater significance for the sustainable development of the resettlement area. Such consultations\nwere conducted with government and non-government organizations,.\n\n#### **_Consultations with Government and Non-government Organizations_**\n\n\n2 Convention on Biological Diversity, Framework Convention on Climate Change, the Vienna Convention on the\nProtection of the Environment, the United Nations Convention to Combat Desertification, the Basel Convention, and the\nStockholm Convention\n\n\nPrepared by WUB Consult", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:020076:9:1:0", "start": 55, "end": 69, "surface": "secondary data", "probe_tag": "confusion", "probe_score": 0.0921, "luna_label": 0, "luna_reason": "Data is described as collected for the assessment, indicating production rather than prior analytical use."}]}, {"key": "paddy2-193", "text": "SILC)<br>|<br>Eurostat<br>|\n|<br>Comprehensive Food Security and Vulnerability Analysis (CFSVA)<br>|<br>WFP<br>|\n|<br>Integrated, Multi-topic Surveys<br>• Living Standards Measurement Study (LSMS)<br>• Integrated Survey (IS)<br>• Family Life Survey (FLS)<br>|<br>World Bank, RAND, NSOs|\n\n\n\n**2.1.** **LSMS Survey Collection and Characteristics**\n\n**2.1.1.** **LSMS Research Collection**\n\nTo capture the up-to-date survey questions for understanding household transport\ncharacteristics, the paper focuses on the LSMS surveys conducted in 30 countries after 2010 (see\nTable 2). These surveys mainly fall into two categories; 12 in of 30 country surveys are from the\nLSMS collection included in the World Bank Microdata Library. The other 18 country surveys are\nfrom other multi-topic household surveys, most of which are used as the data sources for\nPovcalNet <sup>3</sup> [^3: PovcalNet program website: http://iresearch.worldbank.org/PovcalNet/home.aspx.], an online analysis tool for global poverty monitoring, covering more than 1,500\nhousehold surveys spanning 1967 – 2018 and 166 economies (138 economies after 2010). Since\nthese surveys are included in the regional collections and are tagged “LSMS” in the Microdata\nLibrary searching tool, in this report they will be labelled as “LSMS-tagged” surveys <sup>4</sup> [^4: Six “LSMS-tagged” countries surveys used to be supported by the LSMS program before 2010.] .\n\n\n2 LSMS program website: https://www.worldbank.org/en/programs/lsms. The data of 129 LSMS studies can be\ndownloaded by external users through https://microdata.worldbank.org/index.php/", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:001672:5:1:2", "start": 155, "end": 189, "surface": "Living Standards Measurement Study", "probe_tag": "confusion", "probe_score": 0.8388, "luna_label": 1, "luna_reason": "Named survey collection cited as an existing data resource."}]}, {"key": "paddy2-194", "text": "**Limitations**\n\n\nA number of challenges arose during the implementation\nof the conflict scan. First, SFCG and its partners operated\nwithin extreme time constraints as the data collection\nwas completed within one month. This factor limited\nthe possibility of adjustment and fine tuning of the data\ncollection methods. While the survey was tested through\na pilot and adjusted accordingly, focus groups and\ninterviews were conducted in a very short period of time.\n\n\nTherefore, we could only partially assess the\neffectiveness of the discussion guides which limited\nour ability to adjust and thus to ensure that the\nrelevant information was collected. Quantitative\ndata showed that data collectors require closer\nsupervision while administering the survey on\nthe ground in order to ensure consistency and\nsoundness of the information collected.\n\n\nSecond, the security situation, especially in Tripoli, caused\nseveral delays for the data collection while at the same\ntime influenced respondents’ attitudes and answers,\nwhich changed depending on the levels of tensions\nexperienced in the city at the time of data collection.\n\n\n\nIn the target communities of the South, the data\ncollection team faced reluctance from the Lebanese\nrespondents to share their experience and\nperspectives. Lebanese participants required more\nintense probing during facilitated sessions. On the\nother hand, Syrian respondents were not used to\nexpressing their thoughts on such issues and therefore\nfound it difficult to articulate their opinions about the\ntopics covered by the conflict scan.\nTo overcome such challenges, it is crucial to work with\nvery experienced and conflict/context sensitive data\ncollectors, including facilitators and note takers for\nfocus groups.\nResearch findings show the need for further\nresearch on the role of municipalities in lowering\npotential violent conflict. In addition, contradictory\nresponses regarding Lebanese and Syrians’ need\nfor separation, while confessing weak cultural\nbarriers, shows the need for an anthropological\nassessment of these communal dynamics. This\nis something that goes beyond the scope of this\nstudy but at the same time it is essential for a\nclearer understanding of the conflict dynamics.\n\n\n### **MAIN FINDINGS**\n\nThe relationship between Syrians and Lebanese", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000273:9:0:0", "start": 650, "end": 667, "surface": "Quantitative\ndata", "probe_tag": "confusion", "probe_score": 0.3012, "luna_label": 1, "luna_reason": "Quantitative data supports a concrete finding about required collector supervision."}]}, {"key": "paddy2-195", "text": "Refugees in Turkey. Livelihoods Survey Findings._ Ankara: Turk Kizilay\nand World Food Programme.\n7 World Bank and World Food Programme. 2019. _Vulnerability and Protection of Refugees in Turkey: Findings from the Rollout of_\n_the Largest Humanitarian Cash Assistance Program in the World_ . Washington, DC: World Bank and World Food Programme.\n8 Enterprise Surveys (database), International Finance Corporation and World Bank, Washington, DC,\nhttps://www.enterprisesurveys.org/.\n9 Enterprise Surveys (database), International Finance Corporation and World Bank, Washington, DC.,\nhttps://www.enterprisesurveys.org/.\n10 Ayyagari, M., A. Demirgüç-Kunt, and V. Maksimovic. 2011. “Small vs. Young Firms Across the World: Contribution to\nEmployment, Job Creation, and Growth.” Policy Research Working Paper 5631, World Bank, Washington, DC.\n11 World Bank. 2014. _Turkey’s Transitions: Integration, Inclusion, Institutions_ . Report 90509-TR. Washington, DC: World Bank.\n12 World Bank 2014 and 2018 data of the Survey on the Access to Finance of Enterprises (database), European Central Bank,\nFrankfurt, https://www.ecb.europa.eu/stats/ecb_surveys/safe/html/index.en.html.\n\n\nPage 11 of 86", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:refugee_pads:000025:15:2:0", "start": 346, "end": 375, "surface": "Enterprise Surveys (database)", "probe_tag": "confusion", "probe_score": 0.186, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-196", "text": "ing communities and evidence of trade activity\n\n\n6 Office of the Prime Minster (OPM), Government of Uganda, February 2020 available at:\nhttps://ugandarefugees.org/en/country/uga\n7 World Bank 2019, Informing the Refugee Policy Response in Uganda, Results from the Uganda Refugee and Host Communities\n2018 Household Survey\n[8 https://www.worldbank.org/en/topic/fragilityconflictviolence/brief/ugandas-progressive-approach-refugee-management](https://www.worldbank.org/en/topic/fragilityconflictviolence/brief/ugandas-progressive-approach-refugee-management)\n\n\nApr 07, 2020 Page 5 of 16", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000001:4:2:0", "start": 263, "end": 320, "surface": "Uganda Refugee and Host Communities\n2018 Household Survey", "probe_tag": "confusion", "probe_score": 0.8611, "luna_label": 1, "luna_reason": "Named household survey cited as the source of refugee policy evidence."}]}, {"key": "paddy2-197", "text": "<** **84** **1361** **103**\n**Shortfall in Recurrent Buget in US$** <sup>**millons**</sup>\n**-IDA** **(teacher salaries)** **0.0** **0.2** **0.6** **0.6** **0.4** **1.01** **1.0** **1.0** **1** 0 **1.0**\n\n\n\n\n - **Other Donors** **0.1** **0.1** **0.3** **0.5** **0.41** **0.4** **0.61** **0.5'** **0.8** **0.**\nFootnotes:\n\n\n\n**I.** Recurrent costs include all levels of education in addition to Ministry <sup>overheads and cost of other related bodies.</sup>\n2. **Data** in Italics are based on Government simulations as presented <sup>**to**</sup> <sup>donors.</sup>\n3. Mission estimates are **in** bold and are more conservative than **Government** <sup>simulations.</sup>\n**4.** Among other donors France provides **a** sigrnficant amount <sup>of support for Lyc&es, Teacher Training and Higher Education.</sup>", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:021107:8:5:0", "start": 494, "end": 516, "surface": "Government simulations", "probe_tag": "confusion", "probe_score": 0.7941, "luna_label": 1, "luna_reason": "Government simulations provide the basis for reported table data."}]}, {"key": "paddy2-198", "text": "next lowest five deciles receive the largest subsidy amounts when expressed on a per capita\n\n\nbasis. The bottom decile gets around the same as the seventh. Given the less than universal\n\n\nenrollments and the lack of a private schooling option, these results would seem to be driven by\n\n\nthe higher share of school aged children in the poorer groups.\n\n\nVietnam presents a very different situation. In stark contrast to Morocco, Vietnam\n\n\nexperienced a dramatic reduction in income poverty in just 5 years during the 1990s from 58\n\n\npercent of the population in 1993 to 37 percent in 1998 (Government- Donor –NGO Working\n\n\nGroup, 1999). In rural areas, where 90 percent of the population lives, poverty fell from 66 to 48\n\n\npercent during the same period. Rapid economic growth, accompanied by only a small increase\n\n\nin inequality  the Gini of consumption expenditures rose from 0.33 in 1993 to 0.35 in 1998 \n\n\nunderlies this trend. It should be noted that the rise in inequality is from a very low base and is\n\n\nprimarily attributed to an increase in inequality between urban and rural areas (Glewwe et al.\n\n\n2000).\n\n\nSocial indicators have also improved during this period. In the education area, primary\n\n\nschool enrollment rates, already high as a result of the communist regime’s emphasis on\n\n\neducation, increased from 87% to 91% for girls and from 86% to 92% for boys. More dramatic\n\n\ngains were found for lower secondary enrolment rates, which doubled to 61% for girls and to\n\n\n62% for boys. Upper secondary enrollment rates have likewise increased substantially. Yet,\n\n\nthese high enrollment rates and the lack of a gender gap hide the fact that there are still regions \n\n\nprimarily mountainous and more isolated areas  and groups of people  primarily ethnic\n\n\nminorities  that are particularly disadvantaged in term of access and quality. Ethnic minority\n\n\nchildren account for half of the children not in school. Enrollments also tend to rise with\n\n\nhousehold consumption expenditures", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:003565:14:0:0", "start": 1200, "end": 1233, "surface": "primary\n\n\nschool enrollment rates", "probe_tag": "confusion", "probe_score": 0.675, "luna_label": 1, "luna_reason": "Enrollment rates support concrete gender-specific changes in the education analysis."}]}, {"key": "paddy2-199", "text": "**Top Ten: UNHCR Resettlement Submissions in**\n**2009**\n\n\n\nCountry of asylum Submissions\n(persons)\nNepal 22,139\n<mark>Thailand</mark> <mark>19,879</mark>\nSyrian Arab Republic 18,888\n<mark>Kenya</mark> <mark>10,904</mark>\nMalaysia 10,228\n<mark>Jordan</mark> <mark>8,920</mark>\nTurkey 6,744\n<mark>Ethiopia</mark> <mark>6,014</mark>\nLebanon 3,000\n<mark>Tanzania</mark> <mark>2,306</mark>\nAll Others 19,536\n**<mark>Total</mark>** <mark>128,558</mark>\n\n\nCountry of origin Submissions\n(persons)\nIraq 36,067\n<mark>Myanmar</mark> <mark>30,542</mark>\nBhutan 22,114\n<mark>Somalia</mark> <mark>19,838</mark>\nDR of the Congo 5,023\n<mark>Afghanistan</mark> <mark>2,440</mark>\nOccup. Palest. Terr. 1,971\n<mark>Eritrea</mark> <mark>1,554</mark>\nEthiopia 1,477\n<mark>Sudan</mark> <mark>1,351</mark>\nAll Others 6,181\n**<mark>Total</mark>** <mark>128,558</mark>\n\n\nCountry of Submissions\nresettlement (persons)\n\nUSA 102,586\n<mark>Canada</mark> <mark>6,985</mark>\nAustralia 5,638\n<mark>Germany</mark> <mark>3,603</mark>\nSweden 2,462\n<mark>Norway</", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000480:46:0:0", "start": 11, "end": 41, "surface": "UNHCR Resettlement Submissions", "probe_tag": "confusion", "probe_score": 0.211, "luna_label": 0, "luna_reason": "Table title naming resettlement submissions, not an independently used data resource."}]}, {"key": "paddy2-200", "text": ", ONSER, SNDE, the PPP unit, ARE and UNHCR in the refugee camp.\n\n - DA will implement the sanitation Sub-components 1.2 a) and b); and 2.2 a) to e). It will do so in cooperation\nwith UNHCR in the refugee camp.\n\n - Contractors will be hired to undertake the water and sanitation works planned under Components 1 and 2 of\nthe project. A quality control and supervision firm will be hired to oversee day-to-day implementation of civil\nworks. The firm will report to both MHA and the PIU, with the latter responsible for processing payments and\nthe former verifying the firm’s technical reports through the DRHA.\n\n - An memorandum of understanding (MoU) will be developed with UNHCR on the transfer of sanitation and\nwater operations in the M’Bera camp to the DA on sanitation and with MHA/ SNDE on water supply.\n\n - SNDE will implement the water supply sub-component in seven small towns and Kiffa, the latter as per the\nspatial convergence approach described in paragraph 17.\n\n - Component 3 will be implemented by the PIU in collaboration with the technical departments of the MHA,\nONSER, SNDE, CNRE, ARE and the PPP unit.\n\n# B. Results Monitoring and Evaluation (M&E) Arrangements\n\n\n55. **M&E will be managed by the PIU**, which will collect and consolidate data from the technical\nimplementation agencies and works supervision teams. Specific indicators on citizen engagement and gender\nhave been included in the result framework. Monitoring will be based on user satisfaction surveys at project\ninitiation, midterm, and completion. To the extent possible, these results will be disaggregated by gender. In\naddition, a gender indicator on the number of women in MHA trained on project management and strategic\nplanning has been included as a PDO level indicator and an intermediate indicator on the proportion of female\ninterns hired by MHA to boost its pipeline for", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000106:26:1:0", "start": 1460, "end": 1485, "surface": "user satisfaction surveys", "probe_tag": "confusion", "probe_score": 0.2226, "luna_label": 0, "luna_reason": "Planned project monitoring surveys at initiation, midterm, and completion"}]}, {"key": "paddy2-201", "text": "**\n**reducing the number of shipments, with mitigation co-benefits** . Additionally, the component would benefit from a\nbetter management plan, which would reduce food loss and waste along the wheat value chain and, therefore, generate\nclimate change mitigation co-benefits.\n\n\n**Component 2: Project management and capacity building (US$2.5 million)**\n\n\n33. **This component will finance all aspects of project management,** including equipment and materials, consultant\ncosts, compliance with fiduciary, procurement (including internal controls and auditing), and safeguards (environmental\nand social) requirements (including a citizen engagement mechanism and a strengthened GM for better risk\nmanagement), monitoring and evaluation, and impact assessment, knowledge management and communication.\n\n34. **The component will specifically finance mechanisms to improve the mitigation of risks associated with wheat**\n**imports and access to affordable bread under Component 1.** To address fiduciary risks and ensure the integrity of the\nwheat procurement process, it will finance semi-annual financial audits focused on participating importers (as described\nunder Section IV.B). To address technical risks, such as misuse or misappropriation of project-financed wheat imports,\nthe project will finance consultancy services and technical assistance to strengthen the role of the consumer protection\nagency under MOET and of Lebanon’s Central Inspection agency, as well as technical audits upstream in the value chain\nthrough specialized providers. Such technical audits will be contracted under the project according to clearly defined\nterms of reference and will collect data on: (1) declared prices/quantities at loading port to compare with declared and\nactual prices/quantities at destination (port of Beirut or Tripoli), for each shipment; (2) quantity of wheat received at\neach mill as well as quantity of flour produced and sold by each mill, daily for each mill; and (3) quantity of flour procured\nby bakeries as well as quantity of bread produced and", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000019:20:1:0", "start": 1684, "end": 1726, "surface": "declared prices/quantities at loading port", "probe_tag": "confusion", "probe_score": 0.0735, "luna_label": 0, "luna_reason": "Technical audits will collect these data for future shipment comparisons."}, {"key": "jdc_operational:000019:20:1:1", "start": 1848, "end": 1887, "surface": "quantity of wheat received at\neach mill", "probe_tag": "confusion", "probe_score": 0.2031, "luna_label": 0, "luna_reason": "Technical audits will collect these quantities as new project data."}]}, {"key": "paddy2-202", "text": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:fcv_pads_east_africa:020575:16:0:0", "start": 379, "end": 395, "surface": "statistical data", "probe_tag": "confusion", "probe_score": 0.582, "luna_label": 0, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:020575:16:0:1", "start": 1487, "end": 1500, "surface": "random survey", "probe_tag": "drop", "probe_score": 0.012, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-203", "text": "Policy Research Working Paper\n7269\nWomen Managers and the Gender-Based Gap \nin Access to Education\nEvidence from Firm-Level Data in Developing Countries\nMohammad Amin\nAsif Islam\nDevelopment Economics \nGlobal Indicators Group\nMay 2015\nWPS7269\nPublic Disclosure Authorized\nPublic Disclosure Authorized\nPublic Disclosure Authorized\nPublic Disclosure Authorized", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:006332:0:0:0", "start": 113, "end": 128, "surface": "Firm-Level Data", "probe_tag": "confusion", "probe_score": 0.0898, "luna_label": 1, "luna_reason": "Firm-level data are identified as the evidence underlying the paper's analysis."}]}, {"key": "paddy2-204", "text": " they are a refugee. Determination of\nrefugee status can only be of a declaratory nature. Indeed, any person\nis a refugee within the framework of a given instrument if they meet\nthe criteria of the refugee definition in that instrument, whether they are\nformally recognized as a refugee or not (UNHCR Note on Determination\n[of Refugee Status under International Instruments). [source]](https://www.unhcr.org/excom/scip/3ae68cc04/note-determination-refugee-status-under-international-instruments)\n\nA \"migrant\" refers to any person who is moving or has moved across\nan international border or within a State away from their habitual place\nof residence, regardless of (1) the person’s legal status; (2) whether\nthe movement is voluntary or involuntary; (3) what the causes for the\n[movement are; or (4) what the length of the stay is. [source]](https://www.iom.int/who-is-a-migrant)\n\n###### About the factsheet\n\n\nThis factsheet is jointly produced by UNHCR, UNICEF and IOM\nwith the aim to support evidence-based decision-making and\nadvocacy on issues related to refugee and migrant children.\n\nThe document provides an overview of the situation in Europe with\nregards to migrant and refugee children (accompanied and UASC).\nIt compiles key child-related data based on available official\nsources: arrival, asylum applications, asylum decisions, profiling\nof arrivals, relocation from first arrival countries under the EU\nrelocation scheme, as well as returns from Greece to Türkiye under\nthe EU-Türkiye statement.\n\nThe present factsheet covers the period January to December\n2023, which provide up-to-date information on migrant and\nrefugee children, including unaccompanied and separated children,\nwho arrived via mixed Mediterranean and Western African Atlantic\nroutes in Europe.\n\n\n####", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001543:7:1:0", "start": 1236, "end": 1254, "surface": "child-related data", "probe_tag": "confusion", "probe_score": 0.5057, "luna_label": 1, "luna_reason": "Compiles existing official data to present the situation of migrant and refugee children."}]}, {"key": "paddy2-205", "text": ". Re-energizing o f health committees around health centers would be done\n\nby ensuring that health centers who serve poor populations receive their\ngovemment allocation - as they only receive 30% now according to the\nHealth Expenditures Tracking Survey carried out in 2003. In order to\nimprove governance, the publication o f the budget received by each\nhealth structure and how the money was spent would be done throughout\nthe country so that the population i s aware and government officials are\naccountable to them.\n\n\n_o_ Sub-component C: Oualitv Insurance: the M O H has taken the option to improve\nutilization o f health services by strengthening their quality. Such a system has\nbeen put in place with the help o f GTZ in two prefectures. Evaluation o f this pilot\nwas carried out end o f 2004, preliminary evidence seems to indicate that this\napproach i s successful. Lessons leamt from the evaluation would be taken into\naccount and based on this evaluation, the project would help extend this\nimproved system to all 18 targeted prefectures. Following a self-evaluation,\nhealth structures decide on a plan to improve six basic aspects o f health care:\ntechnical skills, client satisfaction, continued training, community participation,\nmanagement o f the district, financial management. The best plans would be\nrewarded. Then each structure plans its annual operation plan based on its\ndiagnosis. The project would help finance both the self-evaluation process as\nwell as parts o f the annual operation plan. GTZ would be hired as technical\nassistance on a sole source basis to strengthen the MOH and help it manage this\ncomponent. This decision was made since GTZ i s already doing so for other\nprefectures and since the German govemment would co-finance in a parallel way\nsome o f the technical assistance required for the extension to the 18 targeted\ndistricts.\n\n\n_9_ **Component 11: Institutional Strengthening (US$8.37** **", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000092:34:0:0", "start": 217, "end": 252, "surface": "Health Expenditures Tracking Survey", "probe_tag": "confusion", "probe_score": 0.6369, "luna_label": 1, "luna_reason": "Named 2003 survey supports the cited 30% health-center allocation finding."}]}, {"key": "paddy2-206", "text": "Community teachers account for the largest portion of the teaching force at the primary level and\nrepresent a growing phenomenon in lower secondary education.\n\nFinance, Management and Strategy.\n\nPublic funding of education is low. Only 2.5% of GDP and 10.3% of the state budget was allocated\nto education in the past 10 years. Most of the education budget is used to cover salaries.\nNevertheless education expenditures have grown by nearly 7% annually since 2001: FCFA 89\nbillion in 2010. The share of expenditures going to primary education was 38% in 2010, 90% of\nwhich is in wage bill and subsidies. Budget execution rate is about 90% and executed allocations to\neducation were only about 60% and 78% of the established national poverty reduction strategy\ntargets in 2004-07 and 2008-09 respectively.\n\nManagement in the education sector is facing many challenges. This includes the sub-optimal\nallocation of human and material resources to schools, highly centralized financial and human\nresources management, as well as a limited capacity and funding among the decentralized structures\nincluding inspections and pedagogical advisers. Furthermore, the sector’s capacity in mo nitoring\nand evaluation (M&E) is also limited. Production of national statistics on education is regularly\ndelayed by more than a year, there is no standardized assessment system, and statistics and results\nfrom M&E are rarely used to inform planning and operational decisions.\n\nThe Interim Strategy for Education and Literacy. The Government recently prepared an Interim\nStrategy for Education and Literacy (Stratégie Intérimaire pour l’Éducation et l’Alphabétisation,\nSIPEA) covering the period from 2013 to 2015 which addresses issues of quantity and quality\nindicating that, although goals with regards to access have not yet been reached, the Government\nacknowledges that ensuring that conditions are met for the delivery of a quality education is\nimportant. The SIPEA was developed in consultation with civil society, relevant ministries as well\nas the financial and technical", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000020:2:0:0", "start": 1240, "end": 1272, "surface": "national statistics on education", "probe_tag": "confusion", "probe_score": 0.6876, "luna_label": 0, "luna_reason": "The sentence describes delayed production of national education statistics."}]}, {"key": "paddy2-207", "text": " public randomization, over 2200 youth were selected to take part in the Entrepreneurship Aptitude Test (EAT). From\nthe youth who took the EAT, 1100 were ultimately selected to receive grants. The first grant orientation sessions were held in March 2018. These\norientation sessions were one-day classes where the youth were able to develop simple business plans and determine how they would utilize the first\ngrant tranche.\n\n**Component 2 Business Plan Competition:** Micro and Small Enterprises Authority (MSEA) has started the procurement process to bring on a firm to\nmanage the competition. The impact evaluation for the business plan competition has also progressed since the last status report.\n\n**Component 3 LMIS:** The Ministry of Labour and Social Protection (MLSP) has made progress in undertaking an informal sector survey, updating the\nKenyan National Occupational Classification (KNOCS), and designing a labor market information system (LMIS). The informal sector survey is the most\ndeveloped of all the activities under the MLSP with a pilot completed on May 5, 2018. However, preparation of a roadmap for the LMIS has been\ndelayed.\n\n\n**Risks**\n\n\n**Systematic Operations Risk-rating Tool**\n\n\nRisk Category Rating at Approval Previous Rating Current Rating\n\n\nPolitical and Governance  Substantial  Substantial  Substantial\n\n\nMacroeconomic  Moderate  Moderate  Moderate\n\n\nSector Strategies and Policies  Low  Low  Low\n\n\nTechnical Design of Project or Program  Substantial  Substantial  Substantial\n\nInstitutional Capacity for Implementation and\n High  High  High\n<u>Sustainability</u>\n\nFiduciary  High  High  High\n\n\nEnvironment and Social  Low  Moderate  Moderate\n\n\nStakeholders  Moderate  Moderate  Moderate\n\n\nOther  --  --  -\n\nOverall  Substantial  Substantial  Substantial\n\n\n5/17/2018 Page 2 of 8", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:017047:1:1:0", "start": 812, "end": 834, "surface": "informal sector survey", "probe_tag": "confusion", "probe_score": 0.881, "luna_label": 0, "luna_reason": "Survey undertaking is project activity; data production is ongoing."}]}, {"key": "paddy2-208", "text": "Bangladesh produces three crops of rice per year: _aman_ is typically planted during\n\n\nthe summer prior to the onset of monsoon rains and harvested in the winter, _aus_ is\n\n\nplanted in the spring and harvested in the summer, and a high-yielding irrigated rice\n\n\nvariety, _boro_, planted in the winter and harvested in the spring or early summer (Del\n\n\nNinno et. al. 2003). As revealed by the 1995-96 and 2000 HIES, the most notable change\n\n\nin the agricultural sector in Bangladesh in the recent years is a significant increase in the\n\n\nproduction of _boro_ rice, made possible by the wider availability of small-scale imported\n\n\nirrigation equipment following trade liberalization. The shift is particularly pronounced in\n\n\nSouth Ganges Flood Plain and East Hills regions with an 18 and 15 percentage point\n\nincrease in the share of _boro_, respectively. <sup>2</sup> [^2: In order to capture some of the regional diversities, six broad agro-ecological regions were constructed,\nfollowing the classification by World Bank (2000b). These regions were created in accordance with several\nmajor criteria: consistency with broad agro-ecological zones, hydrological regions, division boundaries,\nand the need to limit the number of regions to get a statistically representative sample from the Household\nIncome and Expenditure Survey (HIES 2000) for the region (see Appendix Map 1).] The increase in the _boro_ production share in\n\n\nthe North Central, Meghna Flood Plain and Northwest regions has been in the range of 10\n\n\npercentage points, and the smallest change is observed in the Coastal region (Figure 1).\n\n\n**Figure 1. Change in rice production structure, 1995-2000.**\n\n\n20%\n\n\n15%\n\n\n\n10%\n\n\n5%\n\n\n0%\n\n\n-5%\n\n\n-10%\n\n\n-15%\n\n\n-20%\n\n\n\n\n\n_Boro_\n\n_Aman_\n\n_Aus_\n\n\n\n\n\n\n\n\n\nNote: Change in percentage points was calculated by subtracting the shares of rice by variety in\ntotal rice production in 2000 from 1995-96. Calculated from summary statistics in the two\nhousehold-level data sets. Source: 1995-96 and 2000 HIES.\n\n\n2 In order to capture some of the", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:003193:9:0:0", "start": 409, "end": 413, "surface": "HIES", "probe_tag": "confusion", "probe_score": 0.5096, "luna_label": 1, "luna_reason": "HIES surveys provide evidence of changes in rice production structure."}, {"key": "prwp:003193:9:0:1", "start": 1950, "end": 1975, "surface": "household-level data sets", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 1, "luna_reason": "Figure calculated from their summary statistics, with HIES identified as source."}]}, {"key": "paddy2-209", "text": "ada por la Federación Rusa. Las cifras de apatridia se**\n**refieren a las cifras del censo de 2010 ajustadas para reflejar el número de**\n**personas apátridas que adquirieron la nacionalidad en 2011-2017.**\n\n\n\n68 ACNUR > **TENDENCIAS GLOBALES 2018** ACNUR > **TENDENCIAS GLOBALES 2018** 69", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000519:34:19:0", "start": 85, "end": 98, "surface": "censo de 2010", "probe_tag": "confusion", "probe_score": 0.8738, "luna_label": 1, "luna_reason": "Census figures are used as the basis for adjusted statelessness figures."}]}, {"key": "paddy2-210", "text": "Annex 11\nPage 2 of 4\n\n\nThe country's General Environmental Law, expected to be promulgated very shortly, is divided into four\nmajor titles:\n\n\nTitle 1: Concepts, Objectives and General Principles, and Institutional\nOrganization\nTitle 2: Protection of Environments\nTitle 3: Protection of Animal and Plant Species\nTitle 4: Regulation of Pollution\n\n\nImplementing decrees should quickly specify the conditions for putting the main chapters of this\nframework legislation into effect.\n\n\n_Other Agencies And Bodies Involved_\n\n\nAs regards environmental education, the Directorate of the Environment maintains close collaboration\nwith the National Education Research and Pedagogic Information Center _[Centre de Recherche, et de_\n_Production dInformation de l 'Education Nationale-_ CRIPEN], in particular through the formulation of an\n\nawareness campaign strategy on environmental problems.\n\n\nInfrastructure facilities in the education sector are provided by the Directorate of Housing, Urban\nDevelopment, Environment, and Regional Development (DHU). However, as the current reform process\nis not yet completed, a number of serious malfunctions are preventing the Directorate from perforning\nthe role of executing agency assigned to it in the past. The Planning Unit of the Ministry of Education\nwill be the contracting authority's representative for implementation of this project.\n\n\nBecause the system for gathering and analyzing data on the public health system is no longer operational,\nas was confirmed during the visit made to Djibouti's Pelletier Hospital and to the Djibouti-City health\ndistrict, reliable country-wide epidemiological data are unfortunately unavailable. This state of affairs\napplies to the school population in particular. Under these conditions, it will be difficult to define and use\nindicators capable of measuring the success of actions to mitigate the environmental impacts of the\nproject.\n\n\n**Potential Impacts of the Project**\n\n\nThe mission by an IDA environment specialist to the Republic of Djibouti in June 2000 confirmed the\ndegraded situation of the sanitary facilities in all of the schools visited. Discussions with school staff and\nparents of students revealed the concern felt by the latter regarding the", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000038:65:0:0", "start": 1605, "end": 1638, "surface": "country-wide epidemiological data", "probe_tag": "confusion", "probe_score": 0.3364, "luna_label": 0, "luna_reason": "States epidemiological data are unavailable without analyzing or substituting estimates."}]}, {"key": "paddy2-211", "text": "**The World Bank**\nChad COVID-19 Strategic Preparedness and Response Project (P173894)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Number of communication campaigns<br>about COVID-19 broadcast to<br>communities|Number of awareness<br>communications<br>campaigns conducted|weekly|COVID-19<br>report|routine data|MOPH|\n|---|---|---|---|---|---|\n|<br>National COVID-19 risk communication<br>and community engagement strategy<br>established|<br>Establishment of a risk<br>communication and<br>engagement strategy in<br>Chad <br>|once<br>|<br>COVID-19<br>report<br>|routine data<br>|MOPH<br>|\n|Number of technical crisis coordination<br>meetings issuing an official report on<br>epidemic surveillance and response|<br>Number of meetings<br>conducted/official reports<br>issued by the emergency<br>crisis committee|weekly<br>|COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|Number of treatment, isolation &<br>quarantine centers preparing daily report <br>|<br>Number of centers<br>preparing daily reports|weekly<br>|COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|Number of centers assessed monthly<br>(using check list) treatment, isolation &<br>quarantine|Number of centers<br>assessed monthly|monthly<br>|<br>COVID-19<br>report<br> <", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000039:38:0:0", "start": 277, "end": 289, "surface": "routine data", "probe_tag": "confusion", "probe_score": 0.4384, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-212", "text": "### 1.8 11\n\n\n\nCurrent account balance . **.2**\n\n\n\nFinancing items (net)\nChanges in net reserves .. .\n_Memo:_\nReserves including gold _(US$ millions)_\nConversion rate _(DEC, locaW/US$)_ 177.7 177.7 177.7\n\n\n**EXTERNAL DEBT and RESOURCE FLOWS**\n\n**1979** **1989** **1998** **1999**\n_(US$ millions)_ **Compositlon of total debt, 1998 (USS milIlona)**\nTotal debt outstanding and disbursed 26 **179** 288\nIBRD 0 0 0\nIDA 0 26 50 49 G 15 B\n\nTotal debt service 2 15 6\nIBRD 0 0 0 C: 9\nIDA 0 0 1 1\n\nComposition of net resource flows E: 119\nOfficial grants 5 32 48\nOfficial creditors -1 3 2\nPrivate creditors 0 -1 0\nForeign direct investment 0 0 6 D: **95**\nPortfolio equity 0 0 0\n\nWorld Bank program\n\nCommitments 0 9 3 A  - IBRD E - Bilateral\nDisbursements 0 2 2 1 B - IDA D - Other rrultilateral F **-** Private\nPrincipal repayments 0 0 0 0 C- IMF G - Short-term\nNet flows 0 2 2 1\nInterest payments 0 0 0 0\nNet transfers 0 2 1 1\n\n\nNote: This table was produced from the Development Economics central database. 9/13/00", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:fcv_pads_east_africa:012139:63:1:0", "start": 960, "end": 998, "surface": "Development Economics central database", "probe_tag": "confusion", "probe_score": 0.6996, "luna_label": 1, "luna_reason": null}]}, {"key": "paddy2-213", "text": "** **𝒄** _L_ denotes labor) is derived and can be written in log-linear form as: **𝐥** **𝒕** **𝒕** **𝒄** **𝒄** **𝒄** **𝒔**\n\n\n\n**𝐥** Due to the lack of comparable data for r and p, we rely on a vector of country-sector, country-time and sector- **𝒄** **𝐥** **𝒕** **𝒕** **𝒄** **𝒄** **𝒄** **𝒔**\n\ntime fixed effects. While data for w are available, we exclude wages from the regressions to be able to directly\ncompare trade-employment with trade-income elasticities. <sup>27</sup> [^27: Our results suggest that elasticities are very similar in both specifications.]\n\n\n\n**Trade-income elasticities**\n\n\n\nWe apply the same estimation equation, with the exception of the dependent variable which becomes labor value\n\n**𝐥** **𝑳** **𝒄** **𝐥** **𝒕** **𝒕** **𝒄** **𝒄** **𝒄** **𝒔**\n\n\n\nadded (LVA).\n\nSince LVA = w*L, a larger (smaller, resp.) trade-income elasticity than trade-employment elasticity, β 𝐥 **𝐥** 𝑳 **𝑳** 𝑳𝑳𝒄 **𝒄** 𝒄𝒄 = 𝜶𝜶+ 𝜷𝜷𝟐𝟐 𝐥 **𝐥** 𝒕 **𝒕** 𝒕 **𝒕** 𝒕𝒕𝒄 **𝒄** 𝒄𝒄 +𝑫𝑫𝒄 **𝒄** + 𝑫𝑫𝒄 **𝒄** + 𝑫𝑫𝒔 **𝒔**\n\n\n\nadded (LVA). **𝐥** **𝑳", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:000944:38:1:0", "start": 319, "end": 329, "surface": "data for w", "probe_tag": "confusion", "probe_score": 0.3957, "luna_label": 0, "luna_reason": "Data are merely noted as available and explicitly excluded from regressions."}]}, {"key": "paddy2-214", "text": "5.2 This section provides examples of instances where\ncooperation between UNHCR and faith-based actors\nhas yielded ‘protection dividends’ for forcibly displaced\npersons. The nature of this cooperation can vary depending upon whether faith actors are UNHCR ‘implementing\npartners’, ‘operational partners’ or ‘informal partners’ in\nprotection networks or for the purposes of advocacy. The\nexamples are drawn from a survey conducted by UNHCR\nand a coalition of faith-based organizations. The Survey\nidentified examples of good practices and shed light on\nthe breadth of existing –and potential –partnerships between faith-based organizations and UNHCR at all stages\nof the refugee and forced displacement cycle. A number\nare summarized here, by way of example.\n\n\n5.3 A total of 23 examples were submitted by UNHCR staff,\nand 32 examples by faith-based organizations and local\nfaith communities. <sup>4</sup> (See **Annex A** for the complete list of\ncontributors to the Survey on good practice examples.)\nThe following section gives examples drawn from\nUNHCR responses. <sup>5</sup>\n\n\n4 A preliminary overview of these examples, including from\nfaith-based organizations, is contained in two publications\nentitled “Overview of the Survey on Good Practices Examples”\n<u>(http://goo.gl/nLdEeN) and “Analysis of the Survey on Good</u>\nPractices Examples” (http://goo.gl/YsFnFM).\n\n_5_ _Ibid._", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001577:10:0:1", "start": 967, "end": 999, "surface": "Survey on good practice examples", "probe_tag": "confusion", "probe_score": 0.6109, "luna_label": 1, "luna_reason": "Named completed survey cited as the source of identified good-practice examples."}]}, {"key": "paddy2-215", "text": " which would amplify this impact. However, these benefits\nare difficult to estimate and have been excluded from the analysis. <sup>27</sup> The NPV of these investments is\nestimated at US$712,000 at a 12 percent discount rate, with an ERR of 21 percent.\nd. _Public health investments:_ The analysis assumes approximately 50,000 people will be served by health\n\ncenters, resulting in 50 maternal lives saved per year and a 15 percent reduction in other causes of morbidity\n(baseline morbidity of 19 percent). <sup>28</sup> The NPV of these investments is estimated at US$1.3 million at a 12\npercent discount rate, with an ERR of 29 percent.\n\n61. _Communal WASH_ investments reduce morbidity from diarrhea and other waterborne diseases, along with\ntime and cost savings to access water. The analysis assumes the mortality rate due to unsafe water will reduce by\n10 percent (from 25 deaths per 100,000 to 22.5), along with time savings of two hours per week per beneficiary\nhousehold in accessing clean water and US$20 in annual cost savings per household (CEIC data). The NPV of these\nWASH investments is estimated at US$1.1 million at a 12 percent discount rate, with an ERR of 28 percent.\n\n62. Additional assumptions used in the analysis for this component include: (a) value of a statistical life:\nUS$2,394; <sup>29</sup> and (b) annual O&M costs of five percent of total investment value. <sup>30</sup>\n\n63. The results of the analysis for this component and the sensitivity analysis are summarized in the tables below:\n\n\n**Table 6: NPV and ERR results** **Table 7: Sensitivity Analysis**\n\n\n\n\n\n\n|NPV (12 percent discount rate)|", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000188:32:1:0", "start": 1054, "end": 1063, "surface": "CEIC data", "probe_tag": "confusion", "probe_score": 0.8843, "luna_label": 1, "luna_reason": "CEIC data supports the quantified annual household cost-savings assumption."}]}, {"key": "paddy2-216", "text": "65. No Designated Account will be opened for this project. A Blanket Commitment will be\nset up for WFP and FAO for the full amount to be transferred to each UN agency as an Advance.\nThe Grant will finance 100 percent of eligible expenditures of the project, inclusive of taxes.\n\n\n66. On August 22, 2014, the Financial Management Operation Review Committee approved\nthe Request for Elimination of Audit Requirements for the proposed emergency project,\ncoordinated by the EAPSP, as part of project preparation. Alternative mechanisms (detailed in\nthe request) will be put in place to support the elimination of the Bank’s audit requirements,\nhowever. First, at least two field-based visits will be conducted during the first 12 months of the\nproject implementation period. The supervision intensity will be adjusted over time, taking into\naccount the project’s financial management performance and financial management risk level.\nSecond, the Government of Chad will have the entire responsibility to ensure during the project\nimplementation period that goods and services are delivered effectively to the beneficiaries.\nWhere deemed appropriate, however—for example, if the UN agencies’ systems or periodic\nreports have showed some weaknesses or deficiencies—the Bank team may request the\ngovernment to institute arrangements to physically inspect works, goods, and services delivered\nby WFP and FAO.\n\n\n**D.** **Procurement**\n\n67. **_Guidelines._** Procurement for the proposed project will be carried out in accordance with\nthe World Bank “Guidelines: Procurement of Goods, Works, and Non-Consulting Services under\nIBRD Loans and IDA Credits and Grants by World Bank Borrowers,” dated January, 2011, and\n“Guidelines: Selection and Employment of Consultants under IBRD Loans and IDA Credit and\nGrants by World Bank Borrowers,” dated January, 2011, and the provisions stipulated in the\nLegal Agreement. Contract awards will also be published in UNDB, in accordance with the\nBank’s Procurement Guidelines", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:jdc_operational:000007:27:0:0", "start": 1943, "end": 1947, "surface": "UNDB", "probe_tag": "confusion", "probe_score": 0.4866, "luna_label": 0, "luna_reason": null}]}, {"key": "paddy2-217", "text": "OCHA Office of Commission for Humanitarian <sup>Assistance</sup>\nPAMC Project Approval and Monitoring Committee\nPETS Public Expenditure Tracking Survey\nPOM Project Operational Manual\nPPA Participatory Poverty Assessment\nQER Quality Enhancement Review\nRUF Revolutionary United Front\nSAPA Social Action and Poverty Alleviation <sup>Program</sup>\nSHARP Sierra Leone HIV/AIDS Response Project\nSLRA Sierra Leone Roads Authority\nSOCAT Social Capital Assessment Tool\nSPP Strategic Planning and Action Process\nTEP Training and Employment Program\nTSS Transitional Support Strategy\nUNAMSIL United Nations Mission for Sierra <sup>Leone</sup>\nUNHCR United Nations High Commission for <sup>Refugees</sup>\nUNICEF United Nations Children's Fund\nUNOPS United National Operations Support\n\n\nVice President: Mr. Callisto Madavo\nCountry Director: Mr. Mats Karlsson\nSector Manager: Mr. Alexandre Abrantes\nTask Team Leader/Task Manager: Ms. Eileen Murray", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:018491:2:0:0", "start": 112, "end": 151, "surface": "PETS Public Expenditure Tracking Survey", "probe_tag": "confusion", "probe_score": 0.0633, "luna_label": 0, "luna_reason": "Survey is defined in a glossary without evidence of data use."}]}, {"key": "paddy2-218", "text": "<br>Mexico<br>Bosnia<br>Cambodia<br>Indonesia<br>Turkey<br>Lao|To<br>Alb<br>Egypt<br>Malay<br>Mexico<br>Bosnia<br>Cambodia<br>Indonesia<br>Turkey<br>Lao|To<br>Alb<br>Egypt<br>Malay<br>Mexico<br>Bosnia<br>Cambodia<br>Indonesia<br>Turkey<br>Lao|\n|||Slov<br>Myanmar<br>South Africa|Cro<br>Bela<br>Syria<br>Brazil<br>Philippines<br>enia||||||\n|||Slov<br>Myanmar<br>South Africa|Cro<br>Bela<br>Syria<br>Brazil<br>Philippines<br>enia||||||\n|||Slov<br>Myanmar<br>South Africa|Cro<br>Bela<br>Syria<br>Brazil<br>Philippines<br>enia||||||\n|||Slov<br>Myanmar<br>South Africa|||||||\n|||Slov<br>Myanmar<br>South Africa|||||||\n\n\n\n**-100%** **-80%** **-60%** **-40%** **-20%** **0%** **20%** **40%** **60%** **80%**\n\n\n_Source:_ COMEXT, values for 2006 are estimated based on data for first 11 month and historical ratio", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:003550:9:3:0", "start": 760, "end": 783, "surface": "data for first 11 month", "probe_tag": "confusion", "probe_score": 0.24, "luna_label": 1, "luna_reason": "Existing monthly data supports estimated 2006 values from COMEXT."}]}, {"key": "paddy2-219", "text": " for\nimplementation.\n\n\n3.1.2 Administrative data sources\n\n\nSome countries have well-developed administrative\ndata systems that can support the production of\nstatistics for subpopulations of interest, including\nFDPs. The “Country in Focus” cases included in this\nreport, Colombia and Norway, illustrate an example\nof how such systems can work. Those systems\nhave been developed over time, driven by national\ninformation needs, accompanied by legislation\nthat provides the mandate and resources for their\nestablishment and maintenance. In addition to the\ntechnical and resource requirements to establish\nsuch systems, it must be highlighted that unless\nintegration across datasets from different sources\nis possible in the country, the data available may\nnot be suitable for estimation of statistics about\nSDG indicators.\n\n\nEven where effective administrative data sources\nare available, it is important to be aware that they\nare useful to provide data for information needs that\n\n\n\n**17** Principles and Recommendations for Population and Housing Censuses, Revision 3, UN Department of Economic and Social Affairs Statistics\n[Division. https://unstats.un.org/unsd/demographic-social/Standards-and-Methods/files/Principles_and_Recommendations/Population-and-](https://unstats.un.org/unsd/demographic-social/Standards-and-Methods/files/Principles_and_Recommendations/Population-and-Housing-Censuses/Series_M67rev3-E.pdf)\n[Housing-Censuses/Series_M67rev3-E.pdf](https://unstats.un.org/unsd/demographic-social/Standards-and-Methods/files/Principles_and_Recommendations/Population-and-Housing-Censuses/Series_M67rev3-E.pdf)\n\n\nDATA DISAGGREG", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000141:17:1:0", "start": 843, "end": 870, "surface": "administrative data sources", "probe_tag": "confusion", "probe_score": 0.3996, "luna_label": 0, "luna_reason": "States availability of administrative sources without citing an analyzed finding."}]}, {"key": "paddy2-220", "text": ". To ensure the success of CDD-type projects,\nexperience with the **CDP** has demonstrated the need to have local actors capable of\nperforming outreach to local communities in order to stimulate proposal\nsubmissions, and conducting or reviewing needs assessments for proposed subprojects. To this end, under Component **1,** the project envisions providing SDCs\nwith appropriate equipment and training to facilitate the staff's effective and\nefficient performance of the mandated activities.\n\n\n**(b)** **The** **availability** **of** **timely** **and** **reliable** **data** **is** **necessary** **to** **evaluate** **(both** **ex-**\n\n**ante** **and** **ex-post)** **the** **effectiveness** **of** **CDD-type** **projects and** **SSN** **programs.**\nWhile the **CDP** has asked for baseline data to be included in proposals submitted **by**\nNGOs, this requirement was not enforced, making any systematic ex-post evaluation\nof the project impact extremely difficult. Quality and timely data are also vital for\nthe success of proxy-means tested **SSN** interventions, as the targeting formula is\nderived from household survey data, and the assessment of the program's\nperformance is evaluated using the same data source. The prime importance of data\nwill be emphasized in the project design **by:** (i) making collection of verifiable\nbaseline data a selection criterion for **CSD** proposals (in both windows); and (ii)\ninvesting project resources in the collection of household survey data to evaluate\n**N", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000109:20:1:0", "start": 1107, "end": 1128, "surface": "household survey data", "probe_tag": "confusion", "probe_score": 0.6589, "luna_label": 1, "luna_reason": "Used to derive targeting formula and assess program performance."}]}, {"key": "paddy2-221", "text": "-vulnerable populations on vaccine\ndelivery to increase their awareness and reduce vaccine hesitancy. The plan will also focus on improving access of\nCOVID-19 vaccination services to climate vulnerable populations (poor Lebanese, refugees, and host communities)\nliving in rural areas.  The component will also support effective health care waste management, such as use of\nnon-burn technologies and support for the development of micro-plans that promote the use of high energy\nefficiency or hybrid energy consumption. Another adaptation measure is the purchase solar equipment/supplies\nthat will be off grid such as cold chain equipment with solar powered fridges and freezers that will provide reliable\n24/7 power and efficient cooling. The NDVP includes measures to deal with any unexpected disruptions to the\nvaccine supply chain, distribution and storage from climate change impacts and other unexpected disasters (i.e.,\npower outages). The immunization program data is managed through an innovative platform (IMPACT) which uses\n\n\nPage 33 of 54", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000000:37:2:0", "start": 946, "end": 971, "surface": "immunization program data", "probe_tag": "confusion", "probe_score": 0.8204, "luna_label": 0, "luna_reason": "Names program data infrastructure without showing analysis, figures, targeting, or findings."}]}, {"key": "paddy2-222", "text": " At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA M&E data - NaCSA maintains lean and\n**community** **sub-projects and** decision-making by NaCSA; efficient organizational\n**NSAP** **partners monitored** structure\n**and evaluated** **in order to**\n**improve** **program**\n**effectiveness.**\n\n\n**3(d)** **Technical** **Assistance** 3d. 1 NaCSA staff indicate - IDA aide-memoires and\n**services** **effectively** **provided** satisfaction with technical project status reports\n**to support program** assistance, including skill\n**implementation** transfer activities\n\n\n**3(e)** NaCSA **management** 3e. 1 Project management - IDA Project Status reports\n**systems** **functioning** costs (NaCSA staff salaries at (including disbursement\n**effectively** **to ensure** all levels as well as operating reports);\n**program success** expenditures) are 13.5% or - NaCSA proposed annual\nless than total budgeted annual work program and budget\nexpenditures;                 - Annual audit reports;\n3e.2 NaCSA staff and                  - GOSL semi-annual PETS\npartners indicate satisfaction reports\nwith the performance of\nNaCSA's management;\n3e.3 NaCSA performance in\n\n\n                                  - 27", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:010396:31:1:0", "start": 170, "end": 184, "surface": "NaCSA M&E data", "probe_tag": "confusion", "probe_score": 0.149, "luna_label": 0, "luna_reason": "Logframe monitoring data source, without an attributed finding or demonstrated substantive use."}]}, {"key": "paddy2-223", "text": "|<br>742,356|<br>359,744<br>0.48|<br>677,844<br>0.91<br>1.88|\n\n\nRemark: values are in constant 2007 US$ million.\n\n\n\n\n\nThe relationships among damages, losses, and total impacts of each disaster type\n\nshow some interesting features. The loss-damage ratio, dividing the value of estimated\n\nlosses by the damage value, looks very similar across the different disaster types, at\n\naround 0.5. On the other hand, total impact-damage ratios, dividing the value of\n\nestimated total impacts by damage value, have noticeable differences among them:\n\ngeophysical disasters have the largest ratio (0.96), followed closely by meteorological\n\ndisasters (0.96), while climatological and hydrological disasters have relatively smaller\n\nvalues, 0.86 and 0.84, respectively. At the same time, the impact multipliers, total\n\nimpact-loss ratios, have a slightly different order: meteorological disasters have the\n\nlargest impact multiplier (2.02), followed by geophysical (1.88), hydrological (1.80),\n\nand climatological (1.78). Because highly aggregated SAMs for each country are used\n\nfor the estimation in this study, the interpretation of these results requires some caution.\n\nNonetheless, in general, geophysical disasters seem the most costly in absolute value,\n\nand the impacts may become large (larger total impact-damage ratio and impact\n\nmultiplier) than other types of disaster. Meteorological disasters are not so\n\nstraightforward: in total, their economic impacts in absolute value are about average\n\n(around 25% for damages, losses, and total impacts); however, their total\n\n\n15", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:004158:16:1:0", "start": 1035, "end": 1039, "surface": "SAMs", "probe_tag": "confusion", "probe_score": 0.7237, "luna_label": 1, "luna_reason": "Aggregated social accounting matrices are used to estimate disaster impacts."}]}, {"key": "paddy2-224", "text": "Capítulo 6\n\n\ninterés en el retorno voluntario. <sup>**106**</sup> El ACNUR comenzó\na facilitar el retorno desde Ruanda en agosto y desde\nla República Democrática del Congo en septiembre. En\ntotal, el ACNUR y sus socios facilitaron la repatriación\nde unas 40.900 personas burundesas durante el año,\nprincipalmente desde la República Unida de Tanzania\n(30.600), Ruanda (8.000) y la República Democrática del\nCongo (2.000).\n\n\nEn 2020, también se informaron 38.600 retornos a\nSiria <sup>**107**</sup>, principalmente desde Turquía (44%), el Líbano\n(24%) e Irak (22%). El ACNUR mantiene un enfoque\nintegral de las soluciones para las personas refugiadas\nsirias, <sup>**108**</sup> pues reconoce que muchas personas pueden\nno retornar a corto plazo, y es posible que algunas no\nlo hagan jamás. Sigue siendo fundamental mantener y\nmejorar el apoyo a los Gobiernos y las comunidades de\nacogida, así como ampliar el acceso al reasentamiento y\na las vías complementarias.\n\n\n\nA principios de 2021, realizó la sexta encuesta de\nintención de retorno entre las personas sirias. <sup>**109**</sup> Esta\nencuesta, centrada en Egipto, Irak, Jordania y el Líbano,\nllegó a más de 3.", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000160:45:0:0", "start": 1004, "end": 1036, "surface": "encuesta de\nintención de retorno", "probe_tag": "confusion", "probe_score": 0.8174, "luna_label": 1, "luna_reason": "Completed sixth return-intention survey is explicitly cited as an existing source."}]}, {"key": "paddy2-225", "text": ", entrepreneurship, and business training as local citizens, but the employment rate of refugees\nremains lower than that of the national average, with a geographical distribution in 2020 of: 25.5 percent in Ali Addeh,\n26.2 percent in Hol-Hol, 26.9 percent in Markazi, and 46 percent in Djibouti-Ville. <sup>10</sup> [^10: Government of Djibouti (2024), Stratégie Livelihoods et Inclusion Economique Djibouti 2024 – 2028] Livelihood opportunities in refugee\nvillages are scarcer than in the capital, exacerbating food security challenges, and even highly educated refugees struggle\nto find employment, without a command of French. Refugees’ **access to finance** is limited by their lack of inclusion in the\nnational ID system; underdeveloped credit markets; and limited awareness of their right to work. Their self-sufficiency is\nlimited by a lack of access to vocational training, business development support services, and decent jobs <sup>11</sup> [^11: UNHCR, African Development Bank Group, IGAD, EAC (2024), Regional Report Draft: Regional Program on Enhancing the Investment Climate for\n<u>the Economic Empowerment of Refugee, Returnee and Host/Return Community Women in the East and Horn of Africa and Great Lakes Region.</u>] .\n\n\n[6 UNHCR (2023), Republic of Djibouti - Country Summary as at 30 June 2023](https://www.refworld.org/reference/countryrep/unhcr/2024/en/147860)\n7 UNHCR (2025), Djibouti Education Statistics for Refugees; Ministry of Education and Vocational Training of the Republic of Djibouti (2024),\n[Annuaire Statistique 2023/2024; World Bank (2024),](http://www.education.gov.dj/index.php?option=com_k2&view=item&id=631:annuaire-statistique-2023-2024&Itemid=784&lang=en) <u>[Djibouti: Giving Refugee Children a Chance", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000180:13:2:0", "start": 1399, "end": 1441, "surface": "Djibouti Education Statistics for Refugees", "probe_tag": "confusion", "probe_score": 0.8056, "luna_label": 1, "luna_reason": "Named UNHCR education statistics source cited in a footnote."}, {"key": "refugee_pads:000180:13:2:1", "start": 1526, "end": 1556, "surface": "Annuaire Statistique 2023/2024", "probe_tag": "confusion", "probe_score": 0.426, "luna_label": 1, "luna_reason": "Named statistical yearbook cited as the source for education statistics."}]}, {"key": "paddy2-226", "text": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\n**Implementation Support**\n\n\n13. The implementation support strategy for the ECRP considers (a) the project’s high-risk nature, (b)\nthe relative complexity of implementation requiring coordination at multiple levels engaging multiple\nproject stakeholders in a volatile operating environment, and (c) the geographic focus on some of the\nmost vulnerable counties in South Sudan with high levels of insecurity and lower capacities.\n\n\n14. The project will be implemented in phases. Implementation will start with ‘quick wins’ in relatively\nmore stable areas among the selected vulnerable areas. The project will then roll out in clusters in the\nnew, more conflict-affected counties, incorporating lessons learned from the ‘quick wins’. Further, given\nthe regional variation in terms of the capacity of county governments and communities, the engagement\nwill start with county-level social and conflict assessment which includes some basic functionality\nassessment to tailor the interventions.\n\n\n15. In addition, the implementation support strategy is built to support the decentralized nature of\nthe project, where transactions will be small, numerous, and highly dispersed throughout hundreds of\n_bomas_ and _payams_ in around 21 counties across the country. The project design builds in a robust\nimplementation and oversight mechanism by UNOPS and IOM, a strong M&E mechanism with georeferenced monitoring system, engagement of a TPM to provide independent monitoring and a strong\nGRM. The implementation support plan is further complemented by the World Bank’s implementation\nsupport including supervision missions once every four months. The task team will undertake continual\nsocial and conflict monitoring to identify any negative repercussions on the local dynamics and adjust the\nproject approach. Further, the project may engage an agency to undertake periodic studies and analyses\nrelating to specific areas of interest or concern such as HLP issues or intercommunal tensions to help shed\nlight on the project implementation.\n\n\n16. To", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000049:65:0:0", "start": 1482, "end": 1513, "surface": "georeferenced monitoring system", "probe_tag": "confusion", "probe_score": 0.0537, "luna_label": 0, "luna_reason": "Names a monitoring system without showing its data being used."}]}, {"key": "paddy2-227", "text": "sup>recently</sup> <sup>come</sup> <sup>under Government control.</sup>\n\n\n\n**2.** **Main sector** issues **and** <sup>**Government strategy:**</sup>\n\n\n\n_Sector Issues._\n_Poverty in Sierra Leone._ Sierra <sup>Leone has</sup> <sup>the lowest</sup> <sup>Human Development Index</sup> <sup>**in**</sup> <sup>the world</sup>\n\n\n\nand has a GNP per capita <sup>of only US$130</sup> <sup>compared</sup> <sup>to the average</sup> <sup>for Sub-Saharan</sup> <sup>Africa</sup> <sup>of $470.</sup>\n\n\n\nOver 82% of the population <sup>currently</sup> <sup>lives below</sup> <sup>the poverty line and life expectancy is only</sup> <sup>38 years.</sup>\n\n\n\nFertility, infant and child <sup>mortality are</sup> <sup>high</sup> <sup>and over</sup> <sup>a third</sup> <sup>of children and</sup> <sup>a fourth</sup> <sup>of adults</sup> <sup>are</sup>\n\n\n\nmalnourished. The pnmary <sup>school enrollment</s", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:008964:7:1:0", "start": 251, "end": 274, "surface": "Human Development Index", "probe_tag": "confusion", "probe_score": 0.8186, "luna_label": 1, "luna_reason": "Named index supports a concrete global ranking claim."}]}, {"key": "paddy2-228", "text": "insurance, crop yield insurance and commodities futures and options tend to be\ncomplementary in efficient risk financing strategies.\n\n\n**7. Conclusions**\n\nA comprehensive review of the data that are available and credible is a fundamental\nstep in the design and rating of any insurance scheme. Individual coverage is typically\npreferred by farmers. However, the data needed to derive accurate insurance rates for\nindividual farmers are almost never available. In the event that consistent data are lacking\nat the individual level, two options are available. One may wish to use aggregate data in\nan attempt to measure individual contract parameters. An alternative approach is to\nconsider coverage based upon observable indices that reflect as close as possible the loss\nincurred by the farmer. Examples include area-yield insurance and weather-based\ninsurance.\n\nThe availability and credibility of data are also a central issue in production risk\nmodeling. In cases where a significant amount of reliable data is available, one may\nchoose to adopt nonparametric approaches to modeling yield risks. More common,\nhowever, is the case where data are limited. In such cases, parametric methods may be\npreferable. The choice essentially involves a tradeoff between bias and efficiency.\n\nRatemaking procedures are also based on data availability. When historical losses are\navailable, rating procedures are based on the historical loss cost ratios. In contrast, the\nrating of a new insurance scheme in the absence of historical losses usually relies on\nsimulated losses derived from crop yield models.\n\nThis paper has laid out recommendations on the design and rating of viable\nagricultural insurance policies. They rely on recent statistical and actuarial developments\nas well as empirical work based on the U.S. experience. They provide Bank staff and\npolicymakers with technical guiding principles for the development of viable agricultural\ninsurance programs in developing countries.\n\nFinally, prior to any considerations regarding the contract design, one must\ninvestigate the demand for the insurance plan, i.e., willingness and ability to pay on the\npart of those targeted by the insurance plan. This issue has not been", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:002659:28:0:0", "start": 578, "end": 592, "surface": "aggregate data", "probe_tag": "confusion", "probe_score": 0.8753, "luna_label": 1, "luna_reason": "Aggregate data are used to estimate individual insurance contract parameters."}]}, {"key": "paddy2-229", "text": "|Table 5. Origin of asylum applications lodged in the European Union (27), 2008 and 2009<br>Covering 27 European Union countries which provided monthly data to UNHCR.|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n|Origin|2008|2009|Total|Annual<br>change|Share|Share|Share|Rank|Rank|\n|Origin|2008|2009|Total|Annual<br>change|2008|2009|Total|2008|2009|\n|Iraq|27,603|17,544|45,147|-36%|11.6<br>|7.2<br>|9.4<br>|1|4|\n|Russian Federation|18,182|17,887|36,069|-2%|7.6<br>|7.4<br>|7.5<br>|2|3|\n|Somalia|17,112|18,653|35,765|9%|7.2<br>|7.7<br>|7.4<br>|3|2|\n|Afghanistan|13,514|19,393|32,907|44%|5.7<br>|8.0<br>|6.8<br>|4|1|\n|Serbia*|12,633|16,791|29,424|33%|5.3<br>|6.9<br>|6.1<br>|5|5|\n|Pakistan|12,007|9", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000810:15:0:0", "start": 144, "end": 156, "surface": "monthly data", "probe_tag": "confusion", "probe_score": 0.6071, "luna_label": 1, "luna_reason": "Monthly UNHCR data underpin the table's reported asylum application figures."}]}, {"key": "paddy2-230", "text": " companies as suppliers, installers, and service providers. These systems\nare attractive to residential and commercial sectors and being extensively deployed, through donor\nsupport, in public facilities. Pillar 3 seeks to enable faster and more sustainable growth in the rooftop solar\nsector. There is a need to continue to scale up the ongoing efforts through the rooftop solar financing\nmechanism to both increase the availability of zero-cost financing and good quality equipment to\ncustomers, especially SMEs in WB&G. The financing mechanism requires certainty of repayment to ensure\nits sustainability, which led to it being restricted to salaried people and financially robust SMEs, with the\nadditional requirement of having access to sufficient roof space. This is excluding a vast majority of the\nhouseholds, especially poor and vulnerable families, that live in densely populated areas in high-rise\nbuildings. To address this issue, this pillar will also focus on the opportunity to construct community solar\nplants that provide dedicated supply to these neighborhoods, thereby increasing the hours of supply while\ndecreasing the subsidy burden. All new supply—small and large scale, IPPs, or own use—creates an\noperational challenge in terms of evacuating the electricity. This challenge is addressed through Pillars 1\nand 2. The ability of the electricity sector to benefit from the prevalence of IPPs depends on robust\napplication of the processes for selecting IPPs, licensing, and establishing wholesale and retail tariffs.\nThese issues are discussed in Pillar 4.\n\n\n**_Component 3: Enabling Private Sector Engagement in Renewable Energy_**\n\n\n13. The renewable energy offers a growing source of energy in WB&G due to obvious advantages of\nthis technology in WB&G. As per the Securing Energy for Development study, with 3,000 sunshine hours\nper year and global horizontal irradiance of over 2,000 kWh/m <sup>2</sup>, WB&G ranks among the world’s top\nlocations for construction of solar systems. Solar energy represents one of the", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "refugee_pads:000132:62:1:0", "start": 1788, "end": 1825, "surface": "Securing Energy for Development study", "probe_tag": "confusion", "probe_score": 0.8541, "luna_label": 1, "luna_reason": "Named study supports sunshine-hour and irradiance findings about solar potential."}]}, {"key": "paddy2-231", "text": "**The World Bank**\nUganda: Investment for Industrial Transformation and Employment (P171607)\n\n\n\n\n\n\n\n|Col1|Col2|Col3|M&E systems<br>on web<br>based<br>platform|Col5|Sector Foundation)|\n|---|---|---|---|---|---|\n|Value of investment in manufacturing|Firm level investment<br>reported by investors to the<br>Uganda Investment<br>Authority|Annual<br>Abstract<br>|<br>Uganda<br>Investment<br>Authority<br>|Data reported by firms.<br> <br>|Uganda Investment<br>Authority, Investment<br>and Aftercare division.<br>|\n|Income Generating Opportunities for<br>Refugees|<br>Refugee Economic<br>Opportunities: Refugee in<br>self employment, micro<br>enterprises, suppliers and<br>formally employed.|Annually<br>|<br>Project web<br>platform and<br>survey<br> <br>|Data collection from<br>MFIs and other<br>intermediaries, project<br>web platform and<br>surveys.<br>|<br>PSFU in collaboration<br>with UBOS<br>|\n|Number of firms benefiting in RHDs|All MSMEs benefiting RHDs<br>|Annual<br>|Tracking data<br>from web<br>platform and<br>surveys<br> <br>|<br>Survey<br>|PSFU and UBOS<br>|\n|The percentage of jobs saved, that would<br>be lost", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000021:58:0:0", "start": 401, "end": 423, "surface": "Data reported by firms", "probe_tag": "confusion", "probe_score": 0.1346, "luna_label": 0, "luna_reason": "Generic data reference lacks an attributed finding or demonstrated analytical use."}]}, {"key": "paddy2-232", "text": " spending much more time fetching water than those with access to piped supplies.\n\nIn 1999 the government adopted its new National Water Policy, setting ambitious targets for\naccess to improved water and sanitation services. The Millennium Development Goals for Kenya\nare that 70 percent of the population should have access to safe water by 2015, while 93 percent\nshould have access to improved sanitation. In 2000, about 51 percent of the population had\naccess to safe drinking water, and 41 percent had access to improved sanitation. <sup>2</sup> The government\nrealized that the targets could not be achieved without comprehensive reform of sector\ninstitutions and large new investments, and in response prepared the Water Act, which parliament\nenacted in 2002. The Act is one of the most far reaching and comprehensive reforms of the water\nsector undertaken in any country. The Act called for a completely new institutional setup, aimed\nat harmonizing and streamlining the management of water resources and water supply and\nsewerage services. A central tenet of the new service delivery framework is the separation of\nfunctions between each aspect of service delivery: policy making, regulation, asset ownership or\ncontrol, and service delivery. This change was expected to reduce conflicts of interest and\nincrease transparency and accountability.\n\n\n1 In this paper, the terms informal settlements and slums are used interchangeably, and refers to areas refer to areas\nthat lack at least two of the following: secure tenure, adequate infrastructure, planning at the settlement level, and\nquality housing. About 30 percent of Nairobi’s population lives in slums.\n2 World Development Indicators database.\n\n\n14", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:015928:13:1:0", "start": 1670, "end": 1707, "surface": "World Development Indicators database", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 1, "luna_reason": "Named database cited as source for population water and sanitation access figures."}]}, {"key": "paddy2-233", "text": "assessment of non-experimental measures, there has been much recent debate as to the\n\n\nability of propensity-score matching methods to obtain better results (e.g. Heckman,\n\n\nIchimura and Todd, 1997; Dehejia and Wahba 2002; Smith and Todd 2005; Dehejia\n\n\n2005). The migration example we consider here offers many of the features identified by\n\n\nthese studies as conducive to more accurate non-experimental estimation. The non\n\nmigrant control group were administered the same survey instrument as the migrants,\n\n\nincluding retrospective earnings information, and live in the same villages and work in\n\n\nthe same labor markets. Unlike in many labor program settings, there is no substitution\n\n\nbias, as the ability of the controls to migrate other than through the program we consider\n\n\nis severely limited. Moreover, the size of the “treatment” considered here is large and\n\n\nstrongly significant. This contrasts with the treatment effect in Lalonde’s NSW male\n\n\nsample of only a 29% increase in earnings (with a t-statistic of only 1.82). Even with\n\n\nthese favorable conditions, the non-experimental estimators still overstate the income\n\n\ngains. However, we find that the more recent refinements of propensity-score matching\n\n\ndo enable more precision, and provide point estimates which are not statistically different\n\n\nfrom the experimental estimator.\n\n\nThe remainder of this paper is structured as follows. Section 2 describes the immigration\n\n\nprocess used as the natural experiment and the sampling method and data from the\n\n\nPacific Island-New Zealand Migration Study. Section 3 constructs the experimental\n\n\nestimates. Section 4 estimates five different types of non-experimental estimates. Section\n\n\n5 looks directly at selection, Section 6 considers cost-of-living adjustments and Section 7\n\n\nconcludes.\n\n\n                          - 6", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:003119:5:0:0", "start": 1532, "end": 1574, "surface": "Pacific Island-New Zealand Migration Study", "probe_tag": "confusion", "probe_score": 0.7286, "luna_label": 1, "luna_reason": "Named migration study supplies data for experimental and non-experimental estimates."}]}, {"key": "paddy2-234", "text": "**Protection Monitoring Analysis Report**\n### Afghanistan\nAccess to Basic services/Vulnerabilities 2023\n\n\n\n**Reasons for displacement**\n\n\n\n**Reasons for intending to return or**\n\n**move onward**\n\n\n\nSecurity concerns (armed\n\nconflict)\n\n\nNatural disasters\n\n\nVulnerable migration\n\n\nOther\n\n\nCommunal tension\n\n\nHousehold security\n\n\n\n\n\n67%\n\n\n\nEconomic hardship\n\n\nJoining family and/or community\n\nnetwork\n\n\nSecurity concerns (armed\n\nconflict)\n\n\nLack of humanitarian assistance\n\n\nChildren's education\n\n\nThreats to myself/family\n\n\n\n\n\n\n\n\n\n\n\n\n\n78%\n\n\n\n**PAKISTAN RETURNS EMERGENCY**\n\n- Between 1 January 2023 and 31 December 2023, a total of 75,948 Afghan refugees and persons in\nrefugee-like situations returned to Afghanistan. The vast majority (75,324) returned from Pakistan, of\nwhich 79% or 59,836 individuals returned between during November and December 2023 following the\nimplementation of the Government of Pakistan’s “Illegal Foreigners Repatriation Plan” (IFRP).\n\n- Between 1 January – 31 December 2023, there were 3,286 returnee monitoring interviews (2,047 males\nand 1,239 females) conducted with randomly selected newly arrived returnees at Kabul, Kandahar,\nJalalabad, and Herat Encashment Centres (ECs). These interviews included 3,025 returnees from Pakistan,\n223 from Iran, and 38 with from other countries, of these some 1,746 interviews were conducted in the\nlast four months of 2023, of which 1,675 interviews were conducted with returnees from Pakistan.\n\n- The reasons influencing returns identified by refugee returnees from Pakistan have significantly changed\nin the lead-up to the announcement and implementation of the GOP’s IFRP. In the beginning of 2023 until\nearly September, socio-economic challenges (high cost of living, inflation, limited job opportunities), as\nwell as protection concerns in Pakistan influenced refugees’ decision to return to Afghanistan. Since\nSeptember 2023, returnees increasingly pointed to fears of arrest and deportation as well as abuse by\npolice", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:000479:8:0:0", "start": 1020, "end": 1050, "surface": "returnee monitoring interviews", "probe_tag": "confusion", "probe_score": 0.2901, "luna_label": 0, "luna_reason": "Interviews are described as conducted, indicating data production rather than existing-data use."}]}, {"key": "paddy2-235", "text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "source": "refugee_pads", "subset": "annotate_paddy_part2", "spans": [{"key": "sample:refugee_pads:000049:38:1:0", "start": 565, "end": 598, "surface": "household expenditure survey data", "probe_tag": "confusion", "probe_score": 0.7323, "luna_label": 1, "luna_reason": null}, {"key": "sample:refugee_pads:000049:38:1:1", "start": 870, "end": 881, "surface": "survey data", "probe_tag": "confusion", "probe_score": 0.1461, "luna_label": 1, "luna_reason": null}, {"key": "sample:refugee_pads:000049:38:1:2", "start": 1978, "end": 2008, "surface": "data from the Household Survey", "probe_tag": "confusion", "probe_score": 0.1121, "luna_label": 1, "luna_reason": "Household Survey data supports the finding that parents withdraw girls from school."}]}, {"key": "paddy2-236", "text": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\nwill also be ascertained through community scorecards to understand implementation effectiveness and\naccrued benefits to targeted households.\n\n\n75. In terms of Social Safeguards policies, **_OP 4.10 on Indigenous Peoples_** is triggered as analysis by the\nWorld Bank and other experts confirms that the overwhelming majority of people in the proposed project\nareas are expected to meet the requirements of OP 4.10. The project will comply with the requirements\nof OP 4.10 by ensuring that implementation arrangements at the field level embed its basic principles of\na free, prior, and informed consultation leading to broad community support for the proposed Project.\nThe use of pre‐determined criteria for targeting which will be universally applied through community‐\nbased approach would prevent exclusion. In this vein, no separate Indigenous Peoples Plan (IPP) is to be\nprepared.\n\n\n76. Although the project might fund small construction activities under the proposed support to WASH\n(Component 1.2) and postharvest management (Component 2.1), **_OP 4.12 on Involuntary Resettlement_**\nis not triggered. While land is still in abundance in South Sudan, sections of available land that are\naccessible have shrunk due to conflict and insecurity. Potential small infrastructure like water points,\ncommunal grain storage facilities would not require land acquisition and any land will be obtained through\nvoluntary donations following due process and proper documentation. However, a Resettlement Policy\nFramework (RPF), in accordance with OP 4.12 was prepared, finalized and disclosed under the Emergency\nFood Crisis Response Project (EFCRP) by the PIU in MAFS which will also implement the proposed project.\nIn the event that there is any unexpected involuntary resettlement, the RPF will be updated, as necessary,\nre‐consulted on and re‐disclosed.\n\n\n**F. Environment (including Safeguards)**\n\n\n77. No", "source": "jdc_operational", "subset": "annotate_paddy_part2", "spans": [{"key": "jdc_operational:000038:33:0:0", "start": 122, "end": 142, "surface": "community scorecards", "probe_tag": "confusion", "probe_score": 0.1035, "luna_label": 0, "luna_reason": "Future scorecards are planned to ascertain implementation effectiveness."}]}, {"key": "paddy2-237", "text": "#### **IV. Access to Affordable Land and Housing**\n\n##### **Land and Housing Market Assessment**\n\n**Housing markets play a very important role for cities, both in terms of access to affordable**\n**shelter, and as a revenue potential through land value capture.** This chapter drills into\nsecondary and primary data to analyze, for the first time, the land and housing market of the GMA.\nThe objective is to better understand an important real estate market segment not formally\nrecognized by legal nor institutional frameworks. Since land is legally considered as a public asset,\nit cannot be commercialized nor taxed based on market value. Ultimately, this analysis may set\nforth policy and institutional reforms which can enhance municipalities’ ability to capture urban\nland value to finance much needed urban infrastructure. Additionally, overlapping housing price\ndata with poverty map may bring light to unofficial housing market and its affordability aspects.\nThese aspects may affect particularly shelter options for the urban poor.\n\n**The study collected data on housing market by location and type of construction material in**\n**the GMA.** Following Dowall’s land value assessment methodology (Dowall 1991), the team\nconducted interviews with local formal and informal real estate brokers knowledge of real estate\ntransactions in the different neighborhood. Through this interviews, it was possible to classified\nhousing prices by different categories: (i) small, medium, or large, (ii) durable and non-durable\nmaterial homes, and (iii) location. These were the five steps taken to collect and analyze GMA\nhousing data. For each data point, Dowall recommends to gather three interviews. But he also\nexplains that this would create an unnecessary repetition burden turning the whole exercise\ninviable. Hence the solution is to extrapolate the original sample. One interviewed expert with\nexperience beyond his original area provided information about other areas. That reduced the\nnumber of interviews needed for the survey. Another", "source": "fcv_pads_east_africa", "subset": "annotate_paddy_part2", "spans": [{"key": "fcv_pads_east_africa:017825:25:0:0", "start": 855, "end": 873, "surface": "housing price\ndata", "probe_tag": "confusion", "probe_score": 0.799, "luna_label": 0, "luna_reason": "Generic data named for proposed analysis without an attributed finding or concrete claim."}]}, {"key": "paddy2-238", "text": " (e.g.,\n\nmobile phone traces, social media, and other types of big data) and other traditional data sources\n\n(e.g., census data, administrative records and registries, labor mobility data).\n\nc. Broadening the perspective for some key research questions to make better use of existing\n\nhousehold survey data and provide complementary solutions to the ‘rare event’ problem (e.g., look\n\nat climate-induced immobility other than mobility).\n\n\nIn an ideal scenario all these tools and integrations would be operationalized and the longitudinal and multi\ntopic nature of household surveys would: i) allow investigating the prevailing outcomes of slow-onset\n\nchanges, namely migration _vs._ immobility, and their interactions with contextual factors; ii) shed light on\n\nthe leading mediating channels at play; iii) facilitate assessing the potential existence of relevant migration\n\nchains and the role of climate change as an indirect push factor for cross-border mobility; and iv) gauge\n\nfinal impacts on welfare and how these are distributed across different types of households and individuals.\n\n\n16", "source": "general_prwp", "subset": "annotate_paddy_part2", "spans": [{"key": "prwp:001103:17:1:4", "start": 564, "end": 581, "surface": "household surveys", "probe_tag": "confusion", "probe_score": 0.7006, "luna_label": 0, "luna_reason": "Future envisioned use of household surveys, not an already executed analysis."}]}, {"key": "paddy2-239", "text": " 2007**<br>Covering 26 European Union countries which provided monthly data to UNHCR (no data for Italy).<br><br><br>|**Table 4. Origin of asylum applications lodged in the European Union (26), 2006 and 2007**<br>Covering 26 European Union countries which provided monthly data to UNHCR (no data for Italy).<br><br><br>|**Table 4. Origin of asylum applications lodged in the European Union (26), 2006 and 2007**<br>Covering 26 European Union countries which provided monthly data to UNHCR (no data for Italy).<br><br><br>|**Table 4. Origin of asylum applications lodged in the European Union (26), 2006 and 2007**<br>Covering 26 European Union countries which provided monthly data to UNHCR (no data for Italy).<br><br><br>|**Table 4. Origin of asylum applications lodged in the European Union (26), 2006 and 2007**<br>Covering 26 European Union countries which provided monthly data to UNHCR (no data for Italy).<br><br><br>|\n|Origin<br>|2006<br>|2007<br>|Total<br>|Annual<br>change<br>|Share<br><br>|Share<br><br>|Rank<br><br>|Rank<br><br>|\n|Origin<br>|2006<br>|2007<br>|Total<br>|Annual<br>change<br>|2006<br><br>|2007<br><br>|2006<br>|2007<br>|\n|Iraq<br>|19,375<br", "source": "reliefweb", "subset": "annotate_paddy_part2", "spans": [{"key": "reliefweb:001058:15:1:0", "start": 63, "end": 75, "surface": "monthly data", "probe_tag": "confusion", "probe_score": 0.6106, "luna_label": 1, "luna_reason": "Monthly country data underlies the presented asylum-application table."}]}]