An official website of the United States government
Justices on the United States Supreme Court use rhetorical strategies to maintain institutional legitimacy. In the court opinion, a strategy called the monologic voice presents a flattering depiction of the Court. The monologic voice occurs through two tones, the individualistic and collective, which respectively maintain the Justices’ legitimacy through critique and the Court’s legitimacy through unification. We train large language models to identify these rhetorical features in 15,291 modern Supreme Court opinions, issued between 1946 and 2022. While the fraction of collective and individualistic tones has been relatively consistent between 1946 and 2022, the Rehnquist Court used the collective tone at a higher rate than any other Court. In recent terms, 2021 and 2022, we find suggestions of another rhetorical shift, as all Associate Justices of the Roberts Court, excluding Chief Justice Roberts, used the individualistic tone at a historically high rate.
more »
« less
This content will become publicly available on April 1, 2025
Lower Court Influence on High Courts: Evidence from the Supreme Court of the United Kingdom
Abstract Do lower court judges influence the content of Supreme Court opinions in the United Kingdom? Leveraging original data, we analyze opinion language adoption practices of the UK Supreme Court. We advance a theory where the justices’ choices to adopt language from lower court opinions are influenced by Supreme Court-level attributes and Court of Appeal case characteristics. We uncover compelling evidence that UK Supreme Court justices incorporate language extensively from the written opinions of the Court of Appeal of England and Wales. Our findings have significant implications for opinion formulation, doctrinal development, and higher and lower court interactions within comparative courts.
more »
« less
- PAR ID:
- 10521514
- Editor(s):
- Clark, Tom
- Publisher / Repository:
- Cambridge University Press
- Date Published:
- Journal Name:
- Journal of Law and Courts
- Volume:
- 12
- Issue:
- 1
- ISSN:
- 2164-6570
- Page Range / eLocation ID:
- 217 to 238
- Subject(s) / Keyword(s):
- opinion writing opinion content judicial hierarchy comparative courts
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Latent factor models are widely used in the social and behavioural sciences as scaling tools to map discrete multivariate outcomes into low-dimensional, continuous scales. In political science, dynamic versions of classical factor models have been widely used to study the evolution of justices’ preferences in multi-judge courts. In this paper, we discuss a new dynamic factor model that relies on a latent circular space that can accommodate voting behaviours in which justices commonly understood to be on opposite ends of the ideological spectrum vote together on a substantial number of otherwise closely divided opinions. We apply this model to data on nonunanimous decisions made by the US Supreme Court between 1937 and 2021, and show that for most of this period, voting patterns can be better described by a circular latent space.more » « less
-
Guimerà, Roger (Ed.)We study the U.S. Supreme Court dynamics by analyzing the temporal evolution of the underlying policy positions of the Supreme Court Justices as reflected by their actual voting data, using functional data analysis methods. The proposed fully flexible nonparametric method makes it possible to dissect the time-dynamics of policy positions at the level of individual Justices, as well as providing a comprehensive view of the ideology evolution over the history of Supreme Court since its establishment. In addition to quantifying individual Justice’s policy positions, we uncover average changes over time and also the major patterns of change over time. Additionally, our approach allows for representing highly complex dynamic trajectories by a few principal components which complements other models of analyzing and predicting court behavior.more » « less
-
Abstract The significance and influence of U.S. Supreme Court majority opinions derive in large part from opinions’ roles as precedents for future opinions. A growing body of literature seeks to understand what drives the use of opinions as precedents through the study of Supreme Court case citation patterns. We raise two limitations of existing work on Supreme Court citations. First, dyadic citations are typically aggregated to the case level before they are analyzed. Second, citations are treated as if they arise independently. We present a methodology for studying citations between Supreme Court opinions at the dyadic level, as a network, that overcomes these limitations. This methodology—the citation exponential random graph model, for which we provide user-friendly software—enables researchers to account for the effects of case characteristics and complex forms of network dependence in citation formation. We then analyze a network that includes all Supreme Court cases decided between 1950 and 2015. We find evidence for dependence processes, including reciprocity, transitivity, and popularity. The dependence effects are as substantively and statistically significant as the effects of exogenous covariates, indicating that models of Supreme Court citations should incorporate both the effects of case characteristics and the structure of past citations.more » « less
-
null (Ed.)The voting patterns of the nine justices on the United States Supreme Court continue to fascinate and perplex observers of the Court. While it is commonly understood that the division of the justices into a liberal branch and a conservative branch inevitably drives many case outcomes, there are finer, less transparent divisions within these two main branches that have proven difficult to extract empirically. This study imports methods from evolutionary biology to help illuminate the intricate and often overlooked branching structure of the justices’ voting behavior. Specifically, phylogenetic tree estimation based on voting disagreement rates is used to extend ideal point estimation to the non-Euclidean setting of hyperbolic metrics. After introducing this framework, comparing it to one- and two-dimensional multidimensional scaling, and arguing that it flexibly captures important higher-dimensional voting behavior, a handful of potential ways to apply this tool are presented. The emphasis throughout is on interpreting these judicial trees and extracting qualitative insights from them.more » « less
