Measuring Fairness of the US Supreme Court

• In Event: New Measures in Judicial Politics (Virtual Session)

Abstract

The decision of Chief Justice John Roberts to split from his ideological colleagues in the National Federation of Independent Business v. Sebelius showcased how median Justices can shift the outcome of a Supreme Court case. Building off of extant literature on the swing Justice and judicial behavior, this paper seeks to add additional context to the decision-making of median Justices by conceptualizing and measuring the “fairness” of their decisions. Analyzing a corpus of nearly 5000 dissenting opinions between 1940 and 2011, we use a machine learning model to detect the number of disagreements and concessions made by individual Justices. We then determine fairness scores using a ratio of concessions to disagreements and compare Justices to their colleagues based on Martin-Quinn scores of their relative ideological positioning. We hypothesized that median Justices would display higher levels of fairness when compared to their more ideological colleagues and that during times of increased polarization the differences between the “median” and “ideological” Justices would widen. This paper adds valuable information to the study of median Justices and their impact on case outcomes. Additionally, it provides a novel explanation for disparities in the results of landmark Supreme Court decisions - past, present, and future.

Authors

• Donald Snyder, University of Massachusetts, Amherst

• Caitlyn Pierce, University of Massachusetts, Amherst