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Lawyer, Interrupted: Gender Bias in Oral Arguments at the US Supreme Court

Published online by Cambridge University Press:  21 October 2022

Dana Patton*
Affiliation:
University of Alabama
Joseph L. Smith
Affiliation:
University of Alabama
*
Contact the corresponding author at dana.patton@ua.edu.
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Abstract

We examine gender bias in political institutions through a novel lens: oral arguments at the US Supreme Court. We ask whether female lawyers are afforded less speaking time during oral arguments compared to male lawyers. We posit that justices, while highly educated and more aware than most of laws requiring equal treatment, may be influenced by gender schemas that result in unconscious biased treatment of male and female lawyers. Applying automated content analysis to the transcripts of 3,583 oral arguments, we find that female lawyers are interrupted earlier, allowed to speak for less time between interruptions, and subjected to more and longer speeches by the justices compared to their male counterparts. However, this pattern is reversed during oral arguments involving gender-related cases. Our most novel and significant theoretical finding is that gender negates the well-documented positive effect of being on the winning side of a case.

Information

Type
Research Article
Copyright
© 2017 by Law and Courts Organized Section of the American Political Science Association. All rights reserved.
Figure 0

Table 1. Difference of Means Tests by Lawyer Gender (Unequal Variances)

Figure 1

Figure 1. In each graph, the point estimates and standard errors show the change in the predicted value of the relevant dependent variable due to a one-unit change in the relevant independent variable. The estimates were produced using Stata’s truncated Poisson regression with errors clustered on the case. The vertical line in each column reflects zero effect. Error bars show 90% confidence intervals. The table of estimates and standard errors is table A2 in the appendix.

Figure 2

Figure 2. In each graph, the point estimates and standard errors show the predicted values of the relevant dependent variable under the combinations listed on the left side. The estimates were produced using Stata’s truncated Poisson regression and standard errors clustered on the case. Error bars show 90% confidence intervals. The table of estimates and standard errors is table A3 in the appendix.

Figure 3

Figure 3. In each graph, the point estimates and standard errors show the change in the predicted value of the relevant dependent variable when the lawyer presenting the argument is female rather than male, as the number of female justices ranges from zero to three. The estimates were produced using Stata’s truncated Poisson regression and standard errors clustered on the case. Error bars show 90% confidence intervals.

Figure 4

Table A1. Summary Statistics

Figure 5

Table A2. Truncated Poisson Regression Results Presented in Figure 1

Figure 6

Table A3. Truncated Poisson Regression Results Presented in Figure 2