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# Datasets  To address this question we used two datasets.  First, we used the US General Social Survey (GSS), which is a long running (1972-) survey on social attitudes and behavior behaviors  of US American citizens. In addition to social attitudes, the GSS provides demographic and life-course data data about respondents. Each row represents one respondent. Second, we used a database of federal appeals court cases that were decided at the level of circuit courts. The cases were separated by issue (e.g. affirmative action, gender discrimination, racial discrimination). A circuit court case is decided by a randomly assigned panel of three judges. The dataset provides information about the outcome of each case, which is coded as the number of judges that voted in favor the outcome that can be considered to be more "progressive" (that is, pro-affirmative action, and against racial or gender discrimination for example). The dataset also contains information about judge characteristics, such as sex, religion, race, and the party of their appointing president. For our analyses reported below, we focused of the issue of gender discrimination, and restricted ourselves to court case data pertaining to that issue. In total, we used 100 cases (one case per row) that were decided between 1995 and 2004.