Precedent-based legal reasoning and knowledge acquisition in contract law: A process model
Precedent-based legal reasoning and knowledge acquisition in contract law: A process model
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合同法中基于先例的法律推理和知识获取：过程模型
DOI：
10.1145/41735.41759
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发表时间：
1987
期刊：
影响因子：
--
通讯作者：
M. Flowers
中科院分区：
文献类型：
--
作者：
Seth R. Goldman;M. Dyer;M. Flowers
在法律中，先前案件的判决对于新案件的陈述、理解和结果发挥着重要作用。在几乎没有法规（明确的法律规则）的合同法领域尤其如此。当接到新案件时，律师必须能够识别重要问题并对案件如何判决做出一些预测。律师常常会回忆过去与当前案件有相似之处的案例，并进行类比推理来做出这些预测。为了完成这些任务，律师必须能够记住过去的案件，在记忆中组织它们，以便将概念上相似的案件存储在一起（律师通常不会想起不相关的案件），并在案件之间进行类比。因此，记忆中知识的组织和表征对于建立律师认知过程模型至关重要。本文描述了一个在名为 STARE 的计算机程序中实现的过程模型，该模型在一年级法律学生学习合同法的背景下解决了这些问题。
In the law, decisions in previous cases play a significant role in the presentation, understanding, and outcome of new cases. This is particularly true in the area of contract law where few statutes (explicit legal rules) exist. When presented with a new case, a lawyer must be able to identify important issues and make some predictions about how the case might be decided. The lawyer will often recall past cases which bear similarities to the current case and reason analogically to make these predictions. In order to perform these tasks, a lawyer must be able to remember past cases, organize them in memory so that cases that are conceptually similar are stored together (a lawyer normally won't be reminded of an irrelevant case), and make analogies between cases. Thus the organization and representation of knowledge in memory is crucial in building a model of lawyer's cognitive processes. This paper describes a process model, implemented in a computer program called STARE, which addresses these issues in the context of first-year law students learning contract law.