An Exploratory Analysis of Precedent Relevance in the Brazilian Supreme Court Rulings

• Autor(a) principal: Correia, Fernando Alves
• Data de Publicação: 2019
• Outros Autores: Nunes, José Luiz, Almeida, Guilherme da Franca Couto Fernandes de, Almeida, Alexandre A. A., Lopes, Hélio
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
• Texto Completo: https://hdl.handle.net/10438/31153
• topic: Legal rulings; Legal documents; Precedents; Network analysis; Legal arguments; Brazilian law; Direito; Brasil. Supremo Tribunal Federal

The new Brazilian Code of Civil Procedure (CPC) has elevated the importance of precedents in the legal decision-making process. This increased the need to find relevant precedents for a given issue or dispute. Precedents play a central role in judicial thinking by providing information to judges about the legal relevance of particular facts and by establishing legal rules. Precedents are also an important argumentative tool, enabling lawyers to present arguments based on previous decisions. The automated search for relevant precedents is an unattended issue in the Brazilian scenario, partly due to the court’s massive production of decisions — only in 2018 the Brazilian Supreme Court (STF) produced more than 121.000 new rulings — and partly due to the technical challenges arising from the unstructured nature of the court’s practices. In this paper, we present a study of precedent relevance, taking into account the uniqueness of the Brazilian legal system and of STF. To do so, we conducted an exploratory investigation over the precedent network extracted from 1.152.963 decisions published by the STF between 2008 and 2018. This exploratory analysis, although interesting in itself, reveals important challenges that need to be overcome by future research in order for the technology to have the kind of impact it can have on legal practice and academia. In our conclusion, we set out possible paths forward, briefly considering some of the most promising ways to sort out the signal from the noise.