Attributes Beyond Attitudes: Measuring Personality Traits on the U.S. Supreme Court

Abstract

Models of behavior on the U.S. Supreme Court almost universally assume that the justices' behavior depends on the characteristics of the individual justices. However, few prior studies have attempted to measure the justices' individual characteristics beyond their ideological preferences. In contrast, we apply recent advances in machine learning to measure the Big Five personality traits of U.S. Supreme Court justices serving during the 1946 through 2015 terms based on the language in their written opinions. We then conduct an empirical application to demonstrate the importance of these Supreme Court Individual Personality Estimates (SCIPEs) in predicting the justices' behaviors.