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Language and the use of law are predictive of judge gender and seniority

Authors :
Lluc Font-Pomarol
Angelo Piga
Sergio Nasarre-Aznar
Marta Sales-Pardo
Roger GuimerĂ 
Source :
EPJ Data Science, Vol 13, Iss 1, Pp 1-18 (2024)
Publication Year :
2024
Publisher :
SpringerOpen, 2024.

Abstract

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.

Details

Language :
English
ISSN :
21931127
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
EPJ Data Science
Publication Type :
Academic Journal
Accession number :
edsdoj.8c777f0f85ed44cda9b56138bb64a533
Document Type :
article
Full Text :
https://doi.org/10.1140/epjds/s13688-024-00494-x