版权诉讼中的合理使用抗辩:合理使用抗辩策略的成功可预测吗?

Michael D'Rosario
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引用次数: 4

摘要

对法律结果和其他法律领域相关变量的预测已成为最近一些研究的基础。虽然最近的研究估计了标准化变量和二分结果,例如司法判决过程的结果,但很少有研究使用二分数据和分类数据来预测法律辩护策略的基础或审判成功的可能性。司法科学中的实证研究继续采用有限的实证方法子集。本文重申了几种基于人工智能的非参数技术的好处,这些技术比文献中使用的许多常见方法更适合该学科。本文考虑了美国在版权侵权诉讼中合理使用辩护的可预测性,以及审判成功的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fair Use Defences During Copyright Litigation: Is the Success of a Fair Use Defence Strategy Predictable?
The prediction of legal outcomes and other legal domain related variables has served as the basis of a number of recent studies. While recent studies have estimated standardised variables and dichotomous outcomes such as the outcome of a judicial decision process, few studies have employed dichotomous data and categorical data to predict the basis of a legal defense strategy or the likelihood of trial success. Empirical research within the judicial sciences continues to employ a limited subset of empirical methods. This article reasserts the benefits of several artificial intelligence based non-parametric techniques that are better suited to the discipline than many of the common methods employed within the literature. The article considers the predictability of fair use defense within the U.S. during copyright infringement proceedings, and the likelihood of trial success.
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