The forthcoming article “Ascriptive Characteristics and Perceptions of Impropriety in the Rule of Law: Race, Gender, and Public Assessments of Whether Judges Can Be Impartial” by Yoshikuni Ono and Michael A. Zilis is summarized by the author(s) below.
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). That is, Americans may question the impartiality of the judiciary based on attributes of judges that cannot be changed. It is worth remembering that, in 2016, Republican presidential nominee Donald Trump criticized a Hispanic judge, claiming that the judge would not be able to give a fair ruling on a suit involving Trump University due to his ethnic background. What is the public’s view of whether judges are impartial in light of ascriptive characteristics such as a judge’s gender and ethnicity?
In order to understand how the attributes of judges affect perceptions of judicial impartiality in the context of the U.S. legal system, we conducted two survey experiments with around 3,000 U.S. adults each. We first conducted an experiment in which we manipulated the names of the judges appearing in a news article and asked them to evaluate the fairness of the judge. Our results revealed that assessments of a judge’s fairness depended on their perceived race/ethnicity and gender. Figure 1 below shows how respondents assess the fairness of female (black square dots) and Hispanic judges (grey triangle dots). It demonstrates that Democrats, compared with Republicans, tend to perceive less bias among Hispanics and women.
Figure 1 Perceptions of Impropriety Based on Innate Traits
The squares and triangles in the figure represent estimates of the extent to which respondents believe there is bias in the judgments of women and Hispanic judges, respectively, and the straight lines represent confidence intervals at the 95% level.
Next, we conducted a conjoint experiment in which respondents read an article about a pending court case and then asked to rate the fairness of judges who might be assigned to the case. Crucially, we randomized multiple aspects of judges’ profiles, including race/ethnicity and gender. As the results shown in Figure 2 below demonstrate, Democrats believe that female (compared to males) judges and Hispanic (compared to white) judges exhibit less bias. The exact opposite is true among Republicans. Republicans perceive more bias on the part of female and Hispanic judges.
Figure 2. Pooled Conjoint Results Predicting Judge Bias
The dots in the figure indicate the extent to which each attribute influences respondents’ judgments about whether a judge is impartial, with positive values indicating a strong degree of unfairness.
Overall, our findings show that despite the progress they have achieved, female and Hispanic judges face remaining hurdles. Equally notable is the fact that ascriptive traits contribute further to partisan polarization in support for U.S. judges. This pattern is concerning because it goes beyond mere ideology, demonstrating that citizens believe that judges may be biased as a result of their race/ethnicity and gender alone. As women and minorities make up a larger share of the bench, our results imply that partisans diverge in whether these judges can rule with impartiality.
About the Author(s): Yoshikuni Ono is Professor, Faculty of Political Science and Economics at Waseda University and Michael A. Zilis is Associate Professor, Department of Political Science at University of Kentucky. Their research “Ascriptive Characteristics and Perceptions of Impropriety in the Rule of Law: Race, Gender, and Public Assessments of Whether Judges Can Be Impartial” is now available in Early View and will appear in a forthcoming issue of the American Journal of Political Science.
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