datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Gender-Indicators-For-African-Countries
Gender Indicators For African Countries | Africa (World Health Organization)
Size category: 1K<n<10K - Formats: csv - Sector: demographics_social - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Public datasets help… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/Gender-Indicators-For-African-Countries.us_ssa_gender_neutral_first_namesThis is the official dataset for Beyond Binary Gender Labels: Revealing Gender Bias in LLMs through Gender-Neutral Name Predictions
Name-based gender prediction has traditionally categorized individuals as either female or male based on their names, using a binary classification system. That binary approach can be problematic in the cases of gender-neutral names that do not align with any one gender, among other reasons. Relying solely on binary gender categories without recognizing… See the full description on the dataset page: https://huggingface.co/datasets/uzw/us_ssa_gender_neutral_first_names.transactions-genderhttps://www.kaggle.com/c/python-and-analyze-data-final-project/
gender_predictionflores_plus_gender
FLORES+Gender
This dataset builds on the FLORES+ benchmark, developed by Meta to assess machine translation (MT) systems for low-resource languages. FLORES+Gender is designed to assess gender bias in MT. While the typical approach examines bias by translating from a genderless language into a gendered one, this dataset follows the methodology of Costa-jussà et al. (2023) and reverses the direction to analyse whether translation quality is affected by the predominant grammatical… See the full description on the dataset page: https://huggingface.co/datasets/HiTZ/flores_plus_gender.canada_ssa_gender_neutral_first_namesThis is the official dataset for Beyond Binary Gender Labels: Revealing Gender Bias in LLMs through Gender-Neutral Name Predictions
Name-based gender prediction has traditionally categorized individuals as either female or male based on their names, using a binary classification system. That binary approach can be problematic in the cases of gender-neutral names that do not align with any one gender, among other reasons. Relying solely on binary gender categories without recognizing… See the full description on the dataset page: https://huggingface.co/datasets/uzw/canada_ssa_gender_neutral_first_names.france_ssa_gender_neutral_first_namesThis is the official dataset for Beyond Binary Gender Labels: Revealing Gender Bias in LLMs through Gender-Neutral Name Predictions
Name-based gender prediction has traditionally categorized individuals as either female or male based on their names, using a binary classification system. That binary approach can be problematic in the cases of gender-neutral names that do not align with any one gender, among other reasons. Relying solely on binary gender categories without recognizing… See the full description on the dataset page: https://huggingface.co/datasets/uzw/france_ssa_gender_neutral_first_names.lemonde_genderThe full_data.csv file contains, for every article, the number of mentions of men/women, the number of citations of men/women, the author and its gender when it is clear. In the scripts folder, there is a code to make figures.
age-gender-datasetmuti-label-gender-test2iran_executive_agency_employees_by_gender_province_2022
Iran Executive Agency Employees Statistics by Gender and Province (2022)
Dataset_Overview
This dataset offers a comprehensive breakdown of the number of employees in Iranian executive agencies for the year 1401 (corresponding to 2022). It provides detailed statistics on the public sector workforce, categorized by province and gender. This information is vital for policymakers, researchers, and anyone interested in the geographic distribution and gender composition of… See the full description on the dataset page: https://huggingface.co/datasets/Farmaanaa/iran_executive_agency_employees_by_gender_province_2022.dynamic_gender_label_datasetThis is the official dataset for Beyond Binary Gender Labels: Revealing Gender Bias in LLMs through Gender-Neutral Name Predictions
Name-based gender prediction has traditionally categorized individuals as either female or male based on their names, using a binary classification system. That binary approach can be problematic in the cases of gender-neutral names that do not align with any one gender, among other reasons. Relying solely on binary gender categories without recognizing… See the full description on the dataset page: https://huggingface.co/datasets/uzw/dynamic_gender_label_dataset.gender-bias-PE
Dataset Card for gender-bias-PE data
Dataset Description
The gender-bias-PE dataset contains the post-edits and associated behavioural data of the human-centered experiments presented in the paper:
What the Harm? Quantifying the Tangible Impact of Gender Bias in Machine Translation with a Human-centered Study accepted at EMNLP 2024.
The dataset allows to study the impact of gender bias in Machine Translation (MT) via human-centered measures like post-editing effort (i.e.… See the full description on the dataset page: https://huggingface.co/datasets/FBK-MT/gender-bias-PE.detection-of-age-and-gendergender-based-violence-ipv
Gender-Based Violence & Intimate Partner Violence Dataset
Abstract
This dataset provides 30,000 simulated GBV/IPV records (10,000 per scenario) of women in sub-Saharan Africa. Each record contains 45+ variables including violence type (physical, sexual, emotional, economic), risk factors, injuries, mental health consequences, help-seeking behaviour, barriers, and clinical response. Three settings: urban one-stop centre (26% help-seeking), district facility (20%), and… See the full description on the dataset page: https://huggingface.co/datasets/Saksham-443paudel/gender-based-violence-ipv.muti-class-gender-bluesky-testage-gender-predictionmd_gender_biasage_gender_height_weight_building-bridges-gender-fair-german-mtface-age-genderface-age-gender-dataset
Face Age & Gender Dataset
Uploaded from Kaggle.
Women_Gender_violenceage-gender-pred