User-Generated Content Shapes Judicial Reasoning: Evidence from a Randomized Control Trial on Wikipedia

计算机科学 控制(管理) 用户生成的内容 随机对照试验 内容(测量理论) 情报检索 万维网 社会化媒体 人工智能 医学 数学 数学分析 外科
作者
Neil Thompson,Xueyun Luo,Brian McKenzie,Edana Richardson,Brian Flanagan
出处
期刊:Information Systems Research [Institute for Operations Research and the Management Sciences]
标识
DOI:10.1287/isre.2023.0034
摘要

User-generated content, for example, on Wikipedia, is easily accessed but has uncertain reliability. This makes it attractive to use but also creates risk, so there should be limits to who uses Wikipedia and for what purposes. In this paper, we use a randomized control trial to show that Wikipedia’s influence extends to judicial decision making, a field that is highly professional and supposed to follow strict procedures. This causal evidence further emphasizes the widespread influence of Wikipedia and other frequently accessed user-generated content on important social outcomes. Our findings also reveal boundaries to user-generated content’s influence. Although Wikipedia’s influence does extend to courts of “first instance” (where the case is first decided), it does not extend to higher courts (Court of Appeals, Supreme Court). These results suggest that normative prohibitions do seem to be sufficient to keep Wikipedia from influencing the most-important, well-resourced parts of law but that these prohibitions are insufficient in areas where time and resource pressures are greater. By showing that Wikipedia is influencing such an important and formal domain, our paper reinforces the importance of improving the accuracy and reliability of user-generated content, especially in domains with far-reaching societal consequences. Because there is no obvious way to prevent individuals from taking advantage of user-generated content professionally or nonprofessionally, our findings also contribute to the ongoing discussion of how to build public repositories of knowledge into more reliable storehouses.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
俱乐部完成签到,获得积分10
1秒前
Cc完成签到 ,获得积分10
1秒前
1秒前
上官若男应助无语的安卉采纳,获得10
1秒前
平平无奇种花小天才完成签到,获得积分10
1秒前
冯骏发布了新的文献求助30
1秒前
Skyrin完成签到,获得积分0
2秒前
Miya完成签到 ,获得积分10
2秒前
蛇從革发布了新的文献求助50
3秒前
肯德鸭完成签到,获得积分10
4秒前
6秒前
lgy完成签到,获得积分10
6秒前
federish完成签到 ,获得积分10
7秒前
妙奇完成签到,获得积分10
7秒前
子车谷波完成签到,获得积分10
7秒前
浮游应助LLY采纳,获得10
8秒前
欧阳小枫完成签到 ,获得积分10
8秒前
ruby30完成签到,获得积分10
8秒前
无知的小能手完成签到,获得积分10
9秒前
RRR完成签到,获得积分10
9秒前
loveananya完成签到,获得积分10
9秒前
张豪杰完成签到 ,获得积分10
11秒前
这小猪真帅完成签到,获得积分10
12秒前
任性柜子完成签到 ,获得积分10
13秒前
13秒前
耳东完成签到 ,获得积分10
14秒前
开朗煎饼完成签到 ,获得积分10
14秒前
核桃发布了新的文献求助10
14秒前
bella完成签到,获得积分10
15秒前
漫溢阳光完成签到 ,获得积分0
15秒前
15秒前
16秒前
George Will完成签到,获得积分10
16秒前
Yuuki完成签到,获得积分10
16秒前
人不犯二枉少年完成签到,获得积分10
17秒前
薛小飞发布了新的文献求助10
18秒前
xinL应助方正采纳,获得10
18秒前
吴美思完成签到,获得积分10
18秒前
18秒前
18秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Handbook of Milkfat Fractionation Technology and Application, by Kerry E. Kaylegian and Robert C. Lindsay, AOCS Press, 1995 1000
A novel angiographic index for predicting the efficacy of drug-coated balloons in small vessels 500
Textbook of Neonatal Resuscitation ® 500
The Affinity Designer Manual - Version 2: A Step-by-Step Beginner's Guide 500
Affinity Designer Essentials: A Complete Guide to Vector Art: Your Ultimate Handbook for High-Quality Vector Graphics 500
Optimisation de cristallisation en solution de deux composés organiques en vue de leur purification 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5079983
求助须知:如何正确求助?哪些是违规求助? 4298027
关于积分的说明 13389776
捐赠科研通 4121516
什么是DOI,文献DOI怎么找? 2257145
邀请新用户注册赠送积分活动 1261455
关于科研通互助平台的介绍 1195563