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Legislative text, court decisions, regulatory filings, patents, government contracts, election data
9,649 datasets
Serving as the replication package for an empirical analysis of occupational licensing efficiency during the Gilded and Progressive Eras. It contains three data files and a descriptive appendix detailing data collection and variable calculations. The author is Mark Kanazawa.
This replication package supports the paper 'Private Benefits, Public Vices: Railways and Logrolling in the Nineteenth-Century British Parliament'. It contains the data and code required to reproduce the paper's figures and tables, as well as an online appendix with additional results and variable descriptions. The specific dataset dimensions, such as row and column counts, are not provided in the input.
This dataset replicates results from a study on the motivations for the Great Reform Act of 1832, focusing on the roll call vote from March 22, 1831. It was created by Toke S. Aidt to investigate the origins of democracy and the specific factors behind this key UK parliamentary reform. The dataset is associated with computer code for replicating the paper's findings.
Patent Agent List 2026 is a dataset published on Kaggle. The title suggests it contains a directory of registered patent agents or attorneys for the year 2026. The specific source, size, and structure of the data are not detailed in the provided metadata.
This dataset replicates results from a study on the motivations for the Great Reform Act of 1832. It contains roll call vote data from the March 22, 1831 parliamentary vote, authored by Toke S Aidt.
This dataset replicates results from a study on the motivations behind the Great Reform Act of 1832. It contains roll call vote data from the parliamentary vote on March 22, 1831, used to analyze the origins of democracy. The author is Toke S Aidt.
Presenting a replication package for a Journal of Economic History article analyzing legal capacity, regulatory activity, and market integration in Poland from 1505 to 1772. It was authored by Mikołaj Malinowski and last updated in February 2026.
Indexes derived from People's Daily articles using neural topic modeling. The dataset is hosted on Kaggle, but the author, organization, and temporal coverage are unknown. The specific methodology involves analyzing news text to quantify policy-related economic uncertainty.
This dataset relates to the discovery that stress granule formation, seeded by the meiosis-specific RNA binding protein Rim4, halts meiosis at high temperatures in Saccharomyces cerevisiae. It explores the temperature range for meiotic stress granule appearance (33–42 °C) and the role of proteins like 14-3-3 and Hsp104 in assembly and disassembly. The data connects granule persistence to recovery, suggesting a role in cellular repair.
A dataset concerning regulatory changes enacted during the Trump administration. The data likely contains records of executive actions, policy memos, or rule modifications affecting state-level governance. It was published on Kaggle, but the specific source, time range, and data volume are unknown.
Qwen2b-with-legal-domain is a dataset published on Kaggle. The title suggests it relates to a version of the Qwen language model that has been adapted for the legal domain. The dataset's specific content, size, and provenance are not detailed in the available metadata.
LLM Physics Law-Breaker Benchmark Results evaluate how 21 large language models perform against 34 adversarial physics-based reasoning traps. The dataset contains benchmark scores assessing model robustness to logical inconsistencies and physical fallacies. The original author and creation date are unknown.
Vietnamese Legal Corpus (UTS_VLC) is a dataset of Vietnamese legal documents maintained by Underthesea NLP. It contains the Constitution, Codes, and Laws from 1945 to 2025, with splits from 2021, 2023, and 2026 containing 110, 208, and 318 documents respectively. The dataset was last updated on 2026-01-24.
Qwen3B-without-legal-domain is a version of the Qwen language model with a specific domain exclusion. The dataset likely contains model weights or training data from which legal-domain content has been filtered. It was published on Kaggle, but the author, organization, and specific data characteristics are not provided.
This social science dataset contains replication materials for research on public policies and victim stigma related to violence against women. Created by Helen Rabello Kras and hosted on Harvard Dataverse, the data explores the influence of source cues within contexts of impunity. The collection was last updated in March 2026.
This dataset combines data on roll-call voting, parliamentary speeches, and questions in the German Bundestag with novel data on candidate renominations and failures. It covers the period from 1990 to 2017, investigating how selectorates punish dissent and reward activity in the mixed-member electoral system.
Survey results regarding Taiwanese public opinion on the defense of outlying islands, authored by Andrew Chubb for a forthcoming article in Pacific Review. The data captures specific attitudes toward the security of Kinmen, Matsu, and the lesser-known Wuchiu islands.
Sebastian Jäckle's dataset contains follow-up survey data from users of the Voteswiper Voting Advice Application during the 2025 German federal election campaign. It analyzes the alignment between VAA results and users' prior voting intentions, as well as correlations with subsequent short-term voting intentions. The data reveals differences in VAA effects across social groups and party preferences.
Dylan Balla Elliott produced this social science replication dataset for a forthcoming study in the Review of Economics and Statistics regarding causal effects in information provision experiments. The data, updated in March 2026, facilitates the verification of econometric findings related to how information treatments influence subject behavior. It serves as the primary empirical basis for the author's causal identification methodology.
Building plans for the municipality of Berzhausen, delimiting indoor and outdoor areas. The data is provided by the German Federal Agency for Cartography and Geodesy (Bundesamt für Kartographie und Geodäsie) and was last updated on January 23, 2026. It is served via a Web Map Service (WMS) format.