Pardon the Interruption: An Analysis of Gender and Turn-Taking in U.S. Supreme Court Oral Arguments

TL;DR

This paper introduces a labeled corpus of turn changes in U.S. Supreme Court oral arguments, analyzing how speech features relate to gender and legal roles, and demonstrating predictive modeling of exchange nature.

Contribution

It provides a novel annotated dataset and explores the relationship between speech features, gender, and legal roles in Supreme Court oral arguments.

Findings

Models can predict exchange labels with moderate accuracy.

Speech features correlate with gender and legal roles.

The corpus enables future large-scale analysis of turn-taking.

Abstract

This study presents a corpus of turn changes between speakers in U.S. Supreme Court oral arguments. Each turn change is labeled on a spectrum of "cooperative" to "competitive" by a human annotator with legal experience in the United States. We analyze the relationship between speech features, the nature of exchanges, and the gender and legal role of the speakers. Finally, we demonstrate that the models can be used to predict the label of an exchange with moderate success. The automatic classification of the nature of exchanges indicates that future studies of turn-taking in oral arguments can rely on larger, unlabeled corpora.