Replication Data for: Revolving Door Lobbyists and the Value of Congressional Staff Connections

This dataset contains the files necessary to replicate all of the main results in the final article. Included is the primary dataset, an R file with code to replicate the models, figures and tables, and a Stata .do file to recreate the predicted values used in the data visualization within the paper. The R file "replication.r" is the primary file for replication

Replication Data for: "Bounding Partisan Approval Rates Under Endogenous Partisanship: Why High Presidential Partisan Approval May Not Be What It Seems"

Data construction and analysis files for "Bounding Partisan Approval Rates Under Endogenous Partisanship: Why High Presidential Partisan Approval May Not Be What It Seems

Police Executive Attitudes Towards Civilian Review Boards

Survey experiment on police executives' attitudes towards civilian review boards

Institutional Factors Driving Citizen Perceptions of AI in Government: Evidence from a Survey Experiment on Policing

Law enforcement agencies are increasingly adopting AI-powered tools. While prior work emphasizes the technological features driving public opinion, we investigate how public trust and support for AI in government vary with the institutional context. We administer a pre-registered survey experiment to 4,200 respondents about AI use cases in policing to measure responsiveness to three key institutional factors: bureaucratic proximity (i.e., local sheriff versus national FBI), algorithmic targets (i.e., public targets via predictive policing versus detecting officer misconduct through automated case review), and agency capacity (i.e., necessary resources and expertise). We find that the public clearly prefers local over national law enforcement use of AI, while reactions to different algorithmic targets are more limited and politicized. However, we find no responsiveness to agency capacity or lack thereof. The findings suggest the need for greater scholarly, practitioner, and public attention to organizational, not only technical, prerequisites for successful government implementation of AI