作为批量数据的判断

IF 6.5 1区社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY

Big Data & Society Pub Date : 2023-01-01 DOI:10.1177/20539517231160527

V. Janeček

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引用次数: 0

摘要

为了文本和数据挖掘的目的，法院的判决是否应该公开?这篇文章表明，支持和反对获得判决的论点混淆了对什么是判决的不同理解。一种观点认为，判决被视为“法理学”范畴，而另一种观点则认为它们是“事实”的东西。一旦了解到这些意见和根据这些意见提出的要求不是在同一领土上进行斗争，就应该更容易使判决更广泛地获得，包括将判决作为大量数据进行计算分析。本文的目的是帮助澄清关于将判决作为批量数据访问的争论，并强调有关判决的首选许可制度的一些相关考虑因素。

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Judgments as bulk data

Should court judgments be publicly available for text and data mining purposes? This article shows that the arguments for and against access to judgments conflate different understandings of what judgments are. On one view, judgments are seen as a ‘jurisprudential’ category, whereas the other view regards them as something ‘factual’. Once it is understood that these views and the claims based on them do not fight over the same territory, it should be easier to make judgments more widely available, including for the purposes of computational analysis of judgments as bulk data. The purpose of this article is to help to clear the ground for the debate around access to judgments as bulk data and highlight some relevant considerations for the preferred licencing regime concerning judgments.

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来源期刊

Big Data & Society SOCIAL SCIENCES, INTERDISCIPLINARY-

CiteScore

10.90

自引率

10.60%

发文量

审稿时长

11 weeks

期刊介绍： Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government. BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices. BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.