Author, as appears in the article.: Font-Pomarol, Lluc; Piga, Angelo; Nasarre-Aznar, Sergio; Sales-Pardo, Marta; Guimera, Roger
Department: Enginyeria Química
URV's Author/s: Guimera Manrique, Roger / Nasarre Aznar, Sergio / Piga, Angelo / Sales Pardo, Marta
Keywords: Gender differences Judicial decision Judicial decisions Topic model
Abstract: There are examples of how unconscious bias can influence actions of people. In the judiciary, however, despite some examples there is no general theory on whether different demographic attributes such as gender, seniority or ethnicity affect case sentencing. We aim to gain insight into this issue by analyzing over 100k decisions of three different areas of law with the goal of understanding whether judge identity or judge attributes such as gender and seniority can be inferred from decision documents. We find that stylistic features of decisions are predictive of judge identities, their gender and their seniority, a finding that is aligned with results from analysis of written texts outside the judiciary. Surprisingly, we find that features based on legislation cited are also predictive of judge identities and attributes. While own content reuse by judges can explain our ability to predict judge identities, no specific reduced set of features can explain the differences we find in the legislation cited of decisions when we group judges by gender or seniority. Our findings open the door for further research on how these differences translate into how judges apply the law and, ultimately, to promote a more transparent and fair judiciary system.
Thematic Areas: Ciência da computação Ciencias sociales Computational mathematics Computer science applications Engenharias i Engenharias iv Mathematics, interdisciplinary applications Modeling and simulation Social sciences, mathematical methods
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: marta.sales@urv.cat sergio.nasarre@urv.cat roger.guimera@urv.cat
Author identifier: 0000-0002-8140-6525 0000-0001-9086-2533 0000-0002-3597-4310
Record's date: 2024-10-19
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-024-00494-x
Papper original source: Epj Data Science. 13 (1): 57-
APA: Font-Pomarol, Lluc; Piga, Angelo; Nasarre-Aznar, Sergio; Sales-Pardo, Marta; Guimera, Roger (2024). Language and the use of law are predictive of judge gender and seniority. Epj Data Science, 13(1), 57-. DOI: 10.1140/epjds/s13688-024-00494-x
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Article's DOI: 10.1140/epjds/s13688-024-00494-x
Entity: Universitat Rovira i Virgili
Journal publication year: 2024
Publication Type: Journal Publications