Detecting the influence of the Chinese guiding cases: a text reuse approach

IF 3.1 2区 社会学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence and Law Pub Date : 2023-05-06 DOI:10.1007/s10506-023-09358-7
Benjamin M. Chen, Zhiyu Li, David Cai, Elliott Ash
{"title":"Detecting the influence of the Chinese guiding cases: a text reuse approach","authors":"Benjamin M. Chen, Zhiyu Li, David Cai, Elliott Ash","doi":"10.1007/s10506-023-09358-7","DOIUrl":null,"url":null,"abstract":"Abstract Socialist courts are supposed to apply the law, not make it, and socialist legality denies judicial decisions any precedential status. In 2011, the Chinese Supreme People’s Court designated selected decisions as Guiding Cases to be referred to by all judges when adjudicating similar disputes. One decade on, the paucity of citations to Guiding Cases has been taken as demonstrating the incongruity of case-based adjudication and the socialist legal tradition. Citations are, however, an imperfect measure of influence. Reproduction of language uniquely traceable to Guiding Cases can also be evidence of their impact on judicial decision-making. We employ a local alignment tool to detect unattributed text reuse of Guiding Cases in local court decisions. Our findings suggest that Guiding Cases are more consequential than commonly assumed, thereby complicating prevailing narratives about the antagonism of socialist legality to case law.","PeriodicalId":51336,"journal":{"name":"Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2023-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence and Law","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s10506-023-09358-7","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

Abstract Socialist courts are supposed to apply the law, not make it, and socialist legality denies judicial decisions any precedential status. In 2011, the Chinese Supreme People’s Court designated selected decisions as Guiding Cases to be referred to by all judges when adjudicating similar disputes. One decade on, the paucity of citations to Guiding Cases has been taken as demonstrating the incongruity of case-based adjudication and the socialist legal tradition. Citations are, however, an imperfect measure of influence. Reproduction of language uniquely traceable to Guiding Cases can also be evidence of their impact on judicial decision-making. We employ a local alignment tool to detect unattributed text reuse of Guiding Cases in local court decisions. Our findings suggest that Guiding Cases are more consequential than commonly assumed, thereby complicating prevailing narratives about the antagonism of socialist legality to case law.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
中文指导案例的影响检测:一种文本重用方法
社会主义法院应该适用法律,而不是制定法律,社会主义法制否定了司法判决的先例地位。2011年,中国最高人民法院将部分判决确定为指导案例,供全体法官在审理同类纠纷时参考。十年过去了,指导性案例被引用的不足被认为是案例审判与社会主义法律传统不协调的体现。然而,引用次数并不是衡量影响力的完美标准。对指导性案例独特语言的复制也可以作为其对司法决策影响的证据。我们使用一个局部对齐工具来检测地方法院判决中指导性案例的未归属文本重用。我们的研究结果表明,指导性案例比通常假设的更为重要,从而使关于社会主义合法性与判例法对立的主流叙述复杂化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
9.50
自引率
26.80%
发文量
33
期刊介绍: Artificial Intelligence and Law is an international forum for the dissemination of original interdisciplinary research in the following areas: Theoretical or empirical studies in artificial intelligence (AI), cognitive psychology, jurisprudence, linguistics, or philosophy which address the development of formal or computational models of legal knowledge, reasoning, and decision making. In-depth studies of innovative artificial intelligence systems that are being used in the legal domain. Studies which address the legal, ethical and social implications of the field of Artificial Intelligence and Law. Topics of interest include, but are not limited to, the following: Computational models of legal reasoning and decision making; judgmental reasoning, adversarial reasoning, case-based reasoning, deontic reasoning, and normative reasoning. Formal representation of legal knowledge: deontic notions, normative modalities, rights, factors, values, rules. Jurisprudential theories of legal reasoning. Specialized logics for law. Psychological and linguistic studies concerning legal reasoning. Legal expert systems; statutory systems, legal practice systems, predictive systems, and normative systems. AI and law support for legislative drafting, judicial decision-making, and public administration. Intelligent processing of legal documents; conceptual retrieval of cases and statutes, automatic text understanding, intelligent document assembly systems, hypertext, and semantic markup of legal documents. Intelligent processing of legal information on the World Wide Web, legal ontologies, automated intelligent legal agents, electronic legal institutions, computational models of legal texts. Ramifications for AI and Law in e-Commerce, automatic contracting and negotiation, digital rights management, and automated dispute resolution. Ramifications for AI and Law in e-governance, e-government, e-Democracy, and knowledge-based systems supporting public services, public dialogue and mediation. Intelligent computer-assisted instructional systems in law or ethics. Evaluation and auditing techniques for legal AI systems. Systemic problems in the construction and delivery of legal AI systems. Impact of AI on the law and legal institutions. Ethical issues concerning legal AI systems. In addition to original research contributions, the Journal will include a Book Review section, a series of Technology Reports describing existing and emerging products, applications and technologies, and a Research Notes section of occasional essays posing interesting and timely research challenges for the field of Artificial Intelligence and Law. Financial support for the Journal of Artificial Intelligence and Law is provided by the University of Pittsburgh School of Law.
期刊最新文献
SIM-GCN: similarity graph convolutional networks for charges prediction The digital transformation of jurisprudence: an evaluation of ChatGPT-4’s applicability to solve cases in business law Graph contrastive learning networks with augmentation for legal judgment prediction Intermediate factors and precedential constraint Self-training improves few-shot learning in legal artificial intelligence tasks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1