Detecting Ideology in Judicial Language

Dumas, Michel

doi:10.37911/9781947864085.14

Cited by 3 publications

(2 citation statements)

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“…To do so, political scientists have developed models in which ideology is a latent variable that influences speech and can be inferred statistically from text (Lauderdale and Herzog 2016; Schwarz, Traber, and Benoit 2017). These methods provide exciting opportunities for researchers to measure political disagreement on environmental policy among various public actors, as reflected by Dumas (2020), who analyzes the role of variation in judges' ideologies in environmental court case decisions.…”

Section: Measuring Attitudes and Communication From Governments And Ngosmentioning

confidence: 99%

Text as Data in Environmental Economics and Policy

Dugoua

Dumas

Noailly³

2022

Review of Environmental Economics and Policy

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Section: Measuring Attitudes and Communication From Governments And Ngosmentioning

confidence: 99%

Text as Data in Environmental Economics and Policy

Dugoua

Dumas

Noailly³

2022

Review of Environmental Economics and Policy

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“…Later work sought to assign documents to subject matter categories (Gonçalves & Quaresma 2005, Thompson 2001), to predict the authoring judge from the vocabulary used in an opinion (Li et al 2013, Rosenthal & Yoon 2011, and to generate classifications of legal texts along an ideological dimension (Evans et al 2007). 3 Dumas (2019) tests whether it is possible to predict the political affiliation of judges based on the language in judicial opinions, and Hausladen et al (2020) train a machine-learning algorithm to predict the ideological direction of case outcomes from the text of US appellate court opinions. Recent work has used these methods to apply labels to contracts (Lippi et al 2017) and privacy policies (Contissa et al 2018).…”

Section: Prediction and Classificationmentioning

confidence: 99%

Computational Methods in Legal Analysis

Frankenreiter

Livermore

2020

Annu. Rev. Law. Soc. Sci.

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The digitization of legal texts and advances in artificial intelligence, natural language processing, text mining, network analysis, and machine learning have led to new forms of legal analysis by lawyers and law scholars. This article provides an overview of how computational methods are affecting research across the varied landscape of legal scholarship, from the interpretation of legal texts to the quantitative estimation of causal factors that shape the law. As computational tools continue to penetrate legal scholarship, they allow scholars to gain traction on traditional research questions and may engender entirely new research programs. Already, computational methods have facilitated important contributions in a diverse array of law-related research areas. As these tools continue to advance, and law scholars become more familiar with their potential applications, the impact of computational methods is likely to continue to grow. Expected final online publication date for the Annual Review of Law and Social Science, Volume 16 is October 13, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Judge Language Choices

Ash

2024

The Oxford Handbook of Comparative Judicial Behaviour

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This chapter provides an overview of scientific research into the language choices made by judges. First, it introduces a foundational model to frame the judge’s linguistic decisions, considering both the institutional inputs and downstream impacts. Second, it explores the use of natural language processing tools for measuring judicial language choices, highlighting the challenges faced due to the multifaceted and intricate nature of language. Then the focus shifts to the determinants of these choices, evaluating existing empirical studies with an acknowledgment of the inherent challenges in establishing broad causal evidence given the scarcity of natural or field experiments. Fourth, the chapter examines the consequences of judicial language choices, an even harder problem given the challenge of disentangling other aspects of a judge’s choices besides language. In both respects, a number of important findings have been developed, yet many fundamental questions in judge language choice remain unanswered. The chapter concludes with a discussion of some promising paths for future work.

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Detecting Ideology in Judicial Language

Cited by 3 publications

References 0 publications

Text as Data in Environmental Economics and Policy

Text as Data in Environmental Economics and Policy

Computational Methods in Legal Analysis

Judge Language Choices

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