Search
Browse By Day
Browse By Time
Browse By Person
Browse By Mini-Conference
Browse By Division
Browse By Session or Event Type
Browse Sessions by Fields of Interest
Browse Papers by Fields of Interest
Search Tips
Virtual Exhibit Hall
Change Preferences / Time Zone
Sign In
X (Twitter)
This project examines the role of gender in judicial rulings. It explains aspects of gender differences (between judges), gender bias (favoring defendants of the judge’s own gender or dealing with issues relevant to the judge’s own gender), and court differences. To do so, it extends the literature to understudied settings, such as administrative courts, and tests whether the gender bias that has been found in certain types of courts reflects a fundamental behavior that can be found across courts.
Many theories propose gender differences in judging as a result of identification with women or women’s issues, but these would imply universal same-gender bias, and empirical findings have been mixed. I propose the Fairer Sex Theory, which posits that differences in male and female judges’ decisions are mediated by their perceptions of stakes to the individual who has suffered adverse consequences. Judges will differ in their appraisal of the effect of a ruling on a litigant’s well-being, particularly when the ruling involves non-monetary penalties. The theory predicts that female judges may be more punitive in cases with calculable stakes yet more lenient in cases in which injury is uncertain.
This work leverages the fact that administrative courts rule on specific issues and therefore require specific legal expertise that should be more similar between genders than that in the federal courts previously studied. Research in judicial politics has focused on the Supreme Court and lower federal courts, rarely providing insight into the operation of dozens of administrative courts created by congressional and executive authority, such as immigration, social security, and tax courts. This paper utilizes an original data set of web-scraped administrative court data to isolate the linkages between actors’ identity and their decisions. Multi-level modeling is used to analyze gender patterns at the judge, case type, and court levels.