Replication Data for: \"Supreme Prejudice: Examining the Supreme Court’s Racial & Criminal Biases\"

The U.S. Supreme Court is often regarded as an impartial arbiter of justice, yet various prejudices may influence its decisions. This article examines Supreme Court justices’ biases, focusing on how they invoke racialized stereotypes of criminality. We argue that justices are more likely to vote in favor of white, nonviolent litigants, reinforcing stereotypes that depict nonwhite defendants as inherently more criminal and violent. Drawing on the U.S. Supreme Court Database’s criminal procedure case outcomes from 2005–2017, combined with an original dataset of litigants’ racial identities, we estimate a series of multilevel logistic regressions. Our findings show that litigant race, crime type, and justice ideology jointly shape judicial votes. We further investigate how bias appears in justices’ written opinions, revealing language that perpetuates racialized conceptions of criminality. Overall, our results underscore the Court’s role in constructing what it means to be both “criminal” and “nonwhite,” suggesting that the Court is not a neutral interpreter of law, but an institution shaped by broader social and political biases. This dataverse contains datasets and do files in Stata 17 format used for the article, \"Supreme Prejudice: Examining the Supreme Court’s Racial & Criminal Biases\" Published in the Journal of Race, Ethnicity, and Politics by Elizabeth A. Maltby and Abigail A. Matthews.