When Precedents Clash

• URL: http://arxiv.org/abs/2410.10567v1
• Date: Mon, 14 Oct 2024 14:45:47 GMT
• Title: When Precedents Clash
• Authors: Cecilia Di Florio, Huimin Dong, Antonino Rotolo,
• Abstract summary: In legal practice the consistency requirements for case bases may not be satisfied. A model of precedential constraint should take into account the hierarchical structure of the legal system under consideration. We show that condition principles based on the hierarchical structure and on the temporal dimension can provide an unambiguous decision-making process for new cases.
• Score: 0.4915744683251149
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Consistency of case bases is a way to avoid the problem of retrieving conflicting constraining precedents for new cases to be decided. However, in legal practice the consistency requirements for case bases may not be satisfied. As pointed out in (Broughton 2019), a model of precedential constraint should take into account the hierarchical structure of the specific legal system under consideration and the temporal dimension of cases. This article continues the research initiated in (Liu et al. 2022; Di Florio et al. 2023), which established a connection between Boolean classifiers and legal case-based reasoning. On this basis, we enrich the classifier models with an organisational structure that takes into account both the hierarchy of courts and which courts issue decisions that are binding/constraining on subsequent cases. We focus on common law systems. We also introduce a temporal relation between cases. Within this enriched framework, we can formalise the notions of overruled cases and cases decided per incuriam: such cases are not to be considered binding on later cases. Finally, we show under which condition principles based on the hierarchical structure and on the temporal dimension can provide an unambiguous decision-making process for new cases in the presence of conflicting binding precedents.

Related papers

• Empirical analysis of Binding Precedent efficiency in the Brazilian Supreme Court via Similar Case Retrieval [3.317447070657057]
  We empirically assess the legal impact of five binding precedents, 11, 14, 17, 26 and 37, at the highest court level. We compare the uses of different methods of Natural Language Processing for Similar Case Retrieval. We observe that the deep learning models performed significantly worse in the specific Similar Case Retrieval task.
  arXiv  Detail & Related papers  (2024-07-09T16:17:16Z)
• DELTA: Pre-train a Discriminative Encoder for Legal Case Retrieval via Structural Word Alignment [55.91429725404988]
  We introduce DELTA, a discriminative model designed for legal case retrieval. We leverage shallow decoders to create information bottlenecks, aiming to enhance the representation ability. Our approach can outperform existing state-of-the-art methods in legal case retrieval.
  arXiv  Detail & Related papers  (2024-03-27T10:40:14Z)
• PILOT: Legal Case Outcome Prediction with Case Law [43.680862577060765]
  We identify two unique challenges in making legal case outcome predictions with case law. First, it is crucial to identify relevant precedent cases that serve as fundamental evidence for judges during decision-making. Second, it is necessary to consider the evolution of legal principles over time, as early cases may adhere to different legal contexts.
  arXiv  Detail & Related papers  (2024-01-28T21:18:05Z)
• Technical Report on the Learning of Case Relevance in Case-Based Reasoning with Abstract Argumentation [14.755026411356315]
  We show how relevance can be learnt automatically in practice with the help of decision trees. We also show that AA-CBR with decision-tree-based learning of case relevance results in a more compact representation than their decision tree counterparts.
  arXiv  Detail & Related papers  (2023-10-30T15:01:41Z)
• SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval [75.05173891207214]
  Legal case retrieval plays a core role in the intelligent legal system. Most existing language models have difficulty understanding the long-distance dependencies between different structures. We propose a new Structure-Aware pre-traIned language model for LEgal case Retrieval.
  arXiv  Detail & Related papers  (2023-04-22T10:47:01Z)
• An interpretability framework for Similar case matching [8.747801053040256]
  This study proposes an integrated pipeline framework for interpretable SCM. The framework comprises four modules: judicial feature sentence identification, case matching, feature sentence alignment, and conflict resolution. The experimental results show the effectiveness of our proposed framework, establishing a new benchmark for interpretable SCM.
  arXiv  Detail & Related papers  (2023-04-04T08:25:12Z)
• Legal Element-oriented Modeling with Multi-view Contrastive Learning for Legal Case Retrieval [3.909749182759558]
  We propose an interaction-focused network for legal case retrieval with a multi-view contrastive learning objective. Case-view contrastive learning minimizes the hidden space distance between relevant legal case representations. We employ a legal element knowledge-aware indicator to detect legal elements of cases.
  arXiv  Detail & Related papers  (2022-10-11T06:47:23Z)
• Transparency, Compliance, And Contestability When Code Is(n't) Law [91.85674537754346]
  Both technical security mechanisms and legal processes serve as mechanisms to deal with misbehaviour according to a set of norms. While they share general similarities, there are also clear differences in how they are defined, act, and the effect they have on subjects. This paper considers the similarities and differences between both types of mechanisms as ways of dealing with misbehaviour.
  arXiv  Detail & Related papers  (2022-05-08T18:03:07Z)
• What About the Precedent: An Information-Theoretic Analysis of Common Law [64.49276556192073]
  In common law, the outcome of a new case is determined mostly by precedent cases, rather than existing statutes. We are the first to approach this question by comparing two longstanding jurisprudential views. We find that the precedent's arguments share 0.38 nats of information with the case's outcome, whereas precedent's facts only share 0.18 nats of information.
  arXiv  Detail & Related papers  (2021-04-25T11:20:09Z)
• When Hearst Is not Enough: Improving Hypernymy Detection from Corpus with Distributional Models [59.46552488974247]
  This paper addresses whether an is-a relationship exists between words (x, y) with the help of large textual corpora. Recent studies suggest that pattern-based ones are superior, if large-scale Hearst pairs are extracted and fed, with the sparsity of unseen (x, y) pairs relieved. For the first time, this paper quantifies the non-negligible existence of those specific cases. We also demonstrate that distributional methods are ideal to make up for pattern-based ones in such cases.
  arXiv  Detail & Related papers  (2020-10-10T08:34:19Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.