Replication Data for: Ascriptive Characteristics and Perceptions of Impropriety in the Rule of Law: Race, Gender, and Public Assessments of Whether Judges Can Be Impartial
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
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Title |
Replication Data for: Ascriptive Characteristics and Perceptions of Impropriety in the Rule of Law: Race, Gender, and Public Assessments of Whether Judges Can Be Impartial
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Identifier |
https://doi.org/10.7910/DVN/ZHOL6Y
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Creator |
Ono, Yoshikuni
Zilis, Michael A. |
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Publisher |
Harvard Dataverse
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Description |
Perceptions of procedural fairness influence the legitimacy of the law, and because procedures are mutable, reforming them can buttress support for the rule of law. Yet legal authorities have recently faced a distinct challenge: accusations of impropriety based on their ascriptive characteristics (e.g., gender, ethnicity). We study the effect of these traits in the context of the U.S. legal system, focusing on the conditions under which citizens perceive female and minority judges as exhibiting impropriety, and how this compares with perceptions of their white and male counterparts. We find that Americans use a judge’s race and gender to make inferences about which groups the judge favors, whether she is inherently biased, and whether she should recuse. Notably, we find drastically different evaluations of female and Hispanic judges among the political right and left.
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Subject |
Social Sciences
Courts Judges Race Gender Bias Public opinion |
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Contributor |
Zilis, Michael A.
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