1 to 10 of 69 Results
Aug 4, 2025
Keohane, Robert O.; King, Gary, 2021, "Replication Data for: Designing Social Inquiry: Scientific Inference for Qualitative Research", https://doi.org/10.7910/DVN/YHZG5M, Harvard Dataverse, V1, UNF:6:2HECL90TQQxdW2/NYMrkbg== [fileUNF]
Replication data for the preface of Gary King, Robert O. Keohane, and Sidney Verba. Designing Social Inquiry: Scientific Inference in Qualitative Research, 2nd Edition. Princeton University Press. Princeton, 2021. |
Burden, Barry C.; Kimball, David C.; King, Gary, 2004, "Archive of the Controversy Involving Wendy K. Tam Cho, Brian J. Gaines, and the American Political Science Review", https://doi.org/10.7910/DVN/NU8OZQ, Harvard Dataverse, V1
An article by Barry C. Burden and David C. Kimball entitled “A New Approach to the Study of Ticket Splitting” was published in the September 1998 issue of the American Political Science Review1. The empirical part of the article made use of an ecological inference technique developed by Gary King in his book, A Solution to the Ecological Inference... |
Dec 19, 2023 - American Journal of Political Science (AJPS) Dataverse
Evans, Georgina; King, Gary; Smith, Adam; Thakurta, Abhradeep, 2023, "Replication Data for: Differentially Private Survey Research", https://doi.org/10.7910/DVN/X4Y2FL, Harvard Dataverse, V1, UNF:6:1hQlAh8RGzLi+kKnI82oXw== [fileUNF]
Survey researchers have long protected the privacy of respondents via de-identification (removing names and other directly identifying information) before sharing data. Although these procedures help, recent research demonstrates that they fail to protect respondents from intentional re-identification attacks, a problem that threatens to undermine... |
Evans, Georgina; King, Gary, 2021, "Replication Data for: Statistically Valid Inferences from Differentially Private Data Releases, with Application to the Facebook URLs Dataset", https://doi.org/10.7910/DVN/UDFZJD, Harvard Dataverse, V1, UNF:6:qVAL2iA9dusDRaLhZ1X4xg== [fileUNF]
We offer methods to analyze the “differentially private” Facebook URLs Dataset which, at over 17 trillion cell values, is one of the largest social science research datasets ever constructed. The version of differential privacy used in the URLs dataset has specially calibrated random noise added, which provides mathematical guarantees for the priva... |
Jiang, Wenxin; King, Gary; Schmaltz, Allen; Tanner, Martin A., 2018, "Replication Data for: Ecological Regression with Partial Identification", https://doi.org/10.7910/DVN/8TB7GO, Harvard Dataverse, V3
NOTE: This is a pre-publication release. (Version 0.1.) This repository includes details for replicating the results in: Wenxin Jiang, Gary King, Allen Schmaltz, and Martin A. Tanner. 2018. "Ecological Regression with Partial Identification". (under review) |
Jul 11, 2021 - Political Analysis Dataverse
Jerzak, Connor; King, Gary; Strezhnev, Anton, 2021, "Replication Data for: An Improved Method of Automated Nonparametric Content Analysis for Social Science", https://doi.org/10.7910/DVN/AVNZR6, Harvard Dataverse, V1
Some scholars build models to classify documents into chosen categories. Others, especially social scientists who tend to focus on population characteristics, instead usually estimate the proportion of documents in each category -- using either parametric "classify-and-count" methods or "direct" nonparametric estimation of proportions without indiv... |
Kaufman, Aaron R.; King, Gary; Komisarchik, Mayya, 2021, "Replication Data for: How to Measure Legislative District Compactness If You Only Know It When You See It", https://doi.org/10.7910/DVN/FA8FVF, Harvard Dataverse, V1, UNF:6:35bRbD/BTBvdHB84G6SBmQ== [fileUNF]
To deter gerrymandering, many state constitutions require legislative districts to be “compact.” Yet, the law offers few precise definitions other than “you know it when you see it,” which effectively implies a common understanding of the concept. In contrast, academics have shown that compactness has multiple dimensions and have generated many con... |
Barari, Soubhik; Caria, Stefano; Davola, Antonio; Falco, Paolo; Fetzer, Thiemo; Fiorin, Stefano; Hensel, Lukas; Ivchenko, Andriy; Jachimowicz, Jon; King, Gary; Kraft-Todd, Gordon; Ledda, Alice; MacLennan, Mary; Mutoi, Lucian; Pagani, Claudio; Reutskaja, Elena; Roth, Christopher; Slepoi, Federico Raimondi, 2020, "Replication Data for: Evaluating COVID-19 Public Health Messaging in Italy: Self-Reported Compliance and Growing Mental Health Concerns", https://doi.org/10.7910/DVN/1SBQCX, Harvard Dataverse, V3, UNF:6:3t6Wk/r71T1+09TffFwqpw== [fileUNF]
Purpose: The COVID-19 death-rate in Italy continues to climb, surpassing that in every other country. We implement one of the first nationally representative surveys about this unprecedented public health crisis and use it to evaluate the Italian government’ public health efforts and citizen responses. Findings: (1) Public health messaging is being... |
Aug 26, 2019 - American Political Science Review Dataverse
Katz, Jonathan N.; Gary, King; Rosenblatt, Elizabeth, 2019, "Replication Data for: Theoretical Foundations and Empirical Evaluations of Partisan Fairness in District-Based Democracies", https://doi.org/10.7910/DVN/FTYHPJ, Harvard Dataverse, V1, UNF:6:eqlEaHuLdph00pTX/7yCrw== [fileUNF]
We clarify the theoretical foundations of partisan fairness standards for district-based democratic electoral systems, including essential assumptions and definitions that have not been formalized or in some cases even discussed. We also offer extensive empirical evidence for assumptions with observable implications. Throughout, we follow a fundame... |
Jul 20, 2019
King, Gary; Pan, Jennifer; Roberts, Margaret E., 2017, "Replication data for: How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, not Engaged Argument", https://doi.org/10.7910/DVN/QSZMPD, Harvard Dataverse, V2, UNF:6:/3IIELdmrcyZm+v5mx0OJg== [fileUNF]
The Chinese government has long been suspected of hiring as many as 2,000,000 people to surreptitiously insert huge numbers of pseudonymous and other deceptive writings into the stream of real social media posts, as if they were the genuine opinions of ordinary people. Many academics, and most journalists and activists, claim that these so-called "... |
