demographic
demographic-preference-v0.1atomic-metrics-demographic-training-size
Atomic Metrics: Demographic Training-Size Analysis
Complete offline reproduction bundle for the effect of batch-selected training size on demographic preference prediction.
Version 2 — replaces the fixed-bank analysis. Select k extraction batches (five pairs each), use only their metrics and their 5k training pairs to refit BT/LR, then evaluate on cached test200 scores restricted to those metrics. Both the training rows and metric columns change with size. Extraction/refinement… See the full description on the dataset page: https://huggingface.co/datasets/tintin1027/atomic-metrics-demographic-training-size.us-zip-code-rankings-demographics-acs-2023
US ZIP Code Rankings & Demographics (Census ACS 2023)
Clean, ready-to-use rankings and demographics for US ZIP codes, derived from the
US Census Bureau American Community Survey (2019–2023 5-year estimates) and
USPS ZIP→city/state mapping.
Maintained by PostalUp — US postal & address data.
Live, always-current versions of every ranking below:
Richest ZIP codes → https://postalup.com/richest-zip-codes
Poorest ZIP codes → https://postalup.com/poorest-zip-codes
Largest ZIP codes… See the full description on the dataset page: https://huggingface.co/datasets/postalup/us-zip-code-rankings-demographics-acs-2023.fetch_hf_term_notion_gh_7942_target_demographics
Demographics
Overview
Anonymized demographic profiles collected through internal surveys.
Usage
Load the dataset with the datasets library.
License
MIT
Status
Documentation pending update.
Provenance
This is an original dataset created by Nimbus Data Labs and is not derived from any external source.
llm-demographic-cues
Different Demographic Cues Yield Inconsistent Conclusions About LLM Personalization and Bias
Model responses and derived tables for the EMNLP 2026 paper. Analysis code:
https://github.com/manueltonneau/llm-demographic-cues
Manuel Tonneau, Neil K. R. Sehgal, Niyati Malhotra, Sharif Kazemi, Victor
Orozco-Olvera, Ana María Muñoz Boudet, Lakshmi Subramanian, Samuel P.
Fraiberger, Sharath Chandra Guntuku, Valentin Hofmann. Different Demographic
Cues Yield Inconsistent Conclusions… See the full description on the dataset page: https://huggingface.co/datasets/manueltonneau/llm-demographic-cues.Analyzing-Demographic-Biases
PERSUADE 2.0 & ASAP 2.0 — Essay Scoring Datasets
Datasets for our NLP class project on Automated Essay Scoring (AES), combining two widely used student essay corpora.
PERSUADE 2.0
A large-scale corpus of argumentative and persuasive student essays (grades 6–12), annotated with discourse elements and holistic essay scores (1–6).
Files:
persuade_corpus_2.0_train.csv
persuade_corpus_2.0_test.csv
Key columns:
Column
Description
essay_id
Unique essay identifier… See the full description on the dataset page: https://huggingface.co/datasets/nlpscu/Analyzing-Demographic-Biases.