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21 to 30 of 243 Results
Feb 19, 2026
Lockwood, Lee, 2026, "Replication Data for: Health Insurance and Consumption Risk", https://doi.org/10.7910/DVN/GNDABS
Review of Economics and Statistics: Forthcoming
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
Feb 19, 2026
Wyckoff, James, 2026, "Replication Data for Puzzling Over Declining Academic Achievement", https://doi.org/10.7910/DVN/9TWA6T
These data support the figures and tables in the paper.
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
Feb 19, 2026
Kruks-Wisner, Gabrielle; Mangla, Akshay; Sukhtankar, Sandip, 2026, "Replication Data for: Institutional Recognition: Activating Representation to Build Police Responsiveness to Women", https://doi.org/10.7910/DVN/AVXHJI, Harvard Dataverse
This package contains replication data for: "Institutional Recognition: Activating Representation to Build Police Responsiveness to Women." It contains analysis data from an RCT evaluating the impacts of a police reform, Women’s Help Desks (WHDs), in Madhya Pradesh, India. Also included in the package are the survey instruments used to obtain data...
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
Feb 19, 2026
Rivero, Albert, 2026, "Replication Data for: Partisan Hacks? How Election Cases Divide the Supreme Court", https://doi.org/10.7910/DVN/LU95AU
This is the replication package for "Partisan Hacks? How Election Cases Divide the Supreme Court"
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
Feb 19, 2026
Littlewood, Keith, 2026, "Replication Data for AI as Simulation Scenario Raters", https://doi.org/10.7910/DVN/49FBTR
4 LLMs were prompted to rate 10 simulation scenarios that had already been rated with the Simulation Scenario Evaluation Tool (SSET) by 5 blinded human experts for another study. This data set contains the results for human and AI raters.
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
Feb 19, 2026
jorge, jorge cano febles, 2026, "Replication Data for: happy regression", https://doi.org/10.7910/DVN/EJZOKT
Data on subjective well-being, health, and regime type of a selection of countries. Gallup World Bank And Boix-Miller-Rosato Dichotomous Coding of Democracy
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
Feb 19, 2026
Derecki, Noel, 2026, "Replication Data for: TestHelloWorld", https://doi.org/10.7910/DVN/UV2VA1
This is a test of the application
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
Feb 19, 2026
Rivero, Albert, 2026, "Replication Data for: Difference-Splitting Voting: Middle-Ground Votes at the U.S. Supreme Court", https://doi.org/10.7910/DVN/Y2VP7F
Replication data for Difference-Splitting Voting: Middle-Ground Votes at the U.S. Supreme Court (Journal of Law and Empirical Analysis)
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
Feb 19, 2026
E Littlewood, Keith, 2026, "Paired Simulation Scenario Ratings for AI vs Human Authors", https://doi.org/10.7910/DVN/LZLQEP
5 expert raters used the SSET tool to evaluate 5 paired (AI vs Human created) scenarios, reported perceived authorship, and rated suitability for deployment
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
Feb 19, 2026
Volden, Craig, 2026, "Replication Data for: Issue Specialization and Effective Lawmaking in the U.S. Congress", https://doi.org/10.7910/DVN/STPJZA
Replication datasets and code for JOP article, separately for House and Senate.
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
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