Explaining the Judges’ Decisions Criteria

Aerty Santos, Gabriel Silveira de Queirós Campos, Cristine Griffo, Eliana Zandonade, Elias de Oliveira, Elias de Oliveira

2025

Abstract

The identification of named entities in free text is a foundational research area for building intelligent systems in text and document mining. These textual elements allow us to evaluate the reasoning expressed by document authors. In a judicial decision, for example, by identifying time-related entities, an intelligent system can assess and verify whether a sentence issued by a justice agent falls within socially agreed-upon statistical parameters. In this study, 769 judicial decisions from the São Paulo court were evaluated. Our experiments compared the extreme time-value sentences against those with the lowest sentence, for instance, to infer the expressions that justified and have explained their values. The results revealed differences in sentence severity among robbery, drug trafficking, and theft, as well as in how judges cluster based on their sentencing behavior. The study also highlights anomalies in sentencing and links them to specific textual justifications, demonstrating how judges’ decisions can reflect both legal criteria and subjective biases. [...] In a lawsuit the first to speak seems right, until someone comes forward and cross-examines.(Proverbs 18:17)

Paper Citation

in Harvard Style

Santos A., Campos G., Griffo C., Zandonade E. and de Oliveira E. (2025). Explaining the Judges’ Decisions Criteria. In Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR; ISBN , SciTePress, pages 266-274. DOI: 10.5220/0013707500004000

in Bibtex Style

@conference{kdir25,
author={Aerty Santos and Gabriel Campos and Cristine Griffo and Eliana Zandonade and Elias de Oliveira},
title={Explaining the Judges’ Decisions Criteria},
booktitle={Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR},
year={2025},
pages={266-274},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013707500004000},
isbn={},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR
TI - Explaining the Judges’ Decisions Criteria
SN -
AU - Santos A.
AU - Campos G.
AU - Griffo C.
AU - Zandonade E.
AU - de Oliveira E.
PY - 2025
SP - 266
EP - 274
DO - 10.5220/0013707500004000
PB - SciTePress