Ringhand & Collins on An Empirical Analysis of the Senate Judiciary Committee Hearings of Supreme Court Nominees, 1939-2009

Professor Lori A. Ringhand of the University of Georgia School of Law and Professor Paul M. Collins, Jr. of the University of North Texas Department of Political Science have posted May it Please the Senate: An Empirical Analysis of the Senate Judiciary Committee Hearings of Supreme Court Nominees, 1939-2009 (2010). Here is the abstract:

This paper examines the questions asked and answers given by every Supreme Court nominee who has appeared to testify before the Senate Judiciary Committee since 1939. In doing so, it uses a new dataset developed by the authors. This database, which provides a much-needed empirical foundation for scholarship in emerging areas of constitutional law and political science, captures all of the statements made at the hearings and codes these comments by issue area, subissue area, party of the appointing president, and party of the questioning senator. The dataset allows us to quantify for the first time such things as which issues are most frequently discussed at the hearings, whether those issues have changed over time, and whether they vary depending on the party of the appointing president and the party of the questioning senator. We also investigate if questioning patterns differ depending on the race or gender of the nominee. Some of our results are unsurprising: for example, the hearings have become longer. Others, however, challenge conventional wisdom: the Bork hearing is less of an outlier in several ways than is frequently assumed, and abortion has not dominated the hearings. We also discover that there is issue area variation over time, and that there are notable disparities in the issues addressed by Democratic versus Republican senators. Finally, we find that female and minority nominees face a significantly different hearing environment than do white male nominees.

Click here for an infographic — created by GOOD and MGMT. design — based on some of the data in this paper.

HT @cmccool.

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