• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

不公正的阵容使证人更有可能混淆无辜和有罪的嫌疑人。

Unfair Lineups Make Witnesses More Likely to Confuse Innocent and Guilty Suspects.

机构信息

Department of Psychology, University of Warwick.

Department of Psychology, University of Warwick

出版信息

Psychol Sci. 2016 Sep;27(9):1227-39. doi: 10.1177/0956797616655789. Epub 2016 Jul 24.

DOI:10.1177/0956797616655789
PMID:27458070
Abstract

Eyewitness-identification studies have focused on the idea that unfair lineups (i.e., ones in which the police suspect stands out) make witnesses more willing to identify the police suspect. We examined whether unfair lineups also influence subjects' ability to distinguish between innocent and guilty suspects and their ability to judge the accuracy of their identification. In a single experiment (N = 8,925), we compared three fair-lineup techniques used by the police with unfair lineups in which we did nothing to prevent distinctive suspects from standing out. Compared with the fair lineups, doing nothing not only increased subjects' willingness to identify the suspect but also markedly impaired subjects' ability to distinguish between innocent and guilty suspects. Accuracy was also reduced at every level of confidence. These results advance theory on witnesses' identification performance and have important practical implications for how police should construct lineups when suspects have distinctive features.

摘要

目击证人辨认研究一直关注这样一种观点,即不公正的列队(即警方怀疑某人站在其中)会使证人更愿意指认警方嫌疑人。我们研究了不公正的列队是否也会影响受试者区分无辜和有罪嫌疑人的能力,以及他们判断自己辨认准确性的能力。在一项单独的实验(N=8925)中,我们比较了警方使用的三种公正列队技术与我们不采取任何措施防止突出嫌疑人的不公正列队。与公正的列队相比,不采取任何措施不仅增加了受试者指认嫌疑人的意愿,而且明显损害了他们区分无辜和有罪嫌疑人的能力。在每个置信水平上,准确性也都降低了。这些结果推进了关于证人识别表现的理论,对于警方在嫌疑人具有明显特征时应该如何构建列队具有重要的实际意义。

相似文献

1
Unfair Lineups Make Witnesses More Likely to Confuse Innocent and Guilty Suspects.不公正的阵容使证人更有可能混淆无辜和有罪的嫌疑人。
Psychol Sci. 2016 Sep;27(9):1227-39. doi: 10.1177/0956797616655789. Epub 2016 Jul 24.
2
Estimating the proportion of guilty suspects and posterior probability of guilt in lineups using signal-detection models.使用信号检测模型估计列队辨认中有罪嫌疑人的比例和有罪的后验概率。
Cogn Res Princ Implic. 2020 May 13;5(1):21. doi: 10.1186/s41235-020-00219-4.
3
The single lineup paradigm: A new way to manipulate target presence in eyewitness identification experiments.单一列队范式:一种在目击者识别实验中操纵目标存在的新方法。
Law Hum Behav. 2018 Feb;42(1):1-12. doi: 10.1037/lhb0000272.
4
A signal-detection analysis of eyewitness identification across the adult lifespan.一项针对成年人整个生命周期内目击证人辨认的信号检测分析。
Psychol Aging. 2017 May;32(3):243-258. doi: 10.1037/pag0000168.
5
Why are lineups better than showups? A test of the filler siphoning and enhanced discriminability accounts.为什么列队辨认优于单纯辨认?对填充虹吸和增强可辨别性解释的检验。
J Exp Psychol Appl. 2020 Mar;26(1):124-143. doi: 10.1037/xap0000218. Epub 2019 Mar 18.
6
Police lineups of the future?未来的警察列队?
Am Psychol. 2020 Jan;75(1):76-91. doi: 10.1037/amp0000465. Epub 2019 Apr 18.
7
The Relationship Between Eyewitness Confidence and Identification Accuracy: A New Synthesis.目击证人信心与识别准确性之间的关系:新综合。
Psychol Sci Public Interest. 2017 May;18(1):10-65. doi: 10.1177/1529100616686966. Epub 2017 Mar 22.
8
Measuring lineup fairness from eyewitness identification data using a multinomial processing tree model.使用多项处理树模型从目击者识别数据衡量阵容公平性。
Sci Rep. 2023 Apr 18;13(1):6290. doi: 10.1038/s41598-023-33101-6.
9
Evaluating lineup fairness: Variations across methods and measures.评估列队辨认的公平性:方法与测量的差异
Law Hum Behav. 2017 Feb;41(1):103-115. doi: 10.1037/lhb0000203. Epub 2016 Sep 29.
10
Phenotypic mismatch between suspects and fillers but not phenotypic bias increases eyewitness identifications of Black suspects.嫌疑人与陪衬者之间的表型不匹配而非表型偏差会增加对黑人嫌疑人的目击证人指认。
Front Psychol. 2024 Apr 12;15:1233782. doi: 10.3389/fpsyg.2024.1233782. eCollection 2024.

引用本文的文献

1
Delays reduce culprit-presence detection but do not affect guessing-based selection in response to lineups.延迟会降低对犯罪嫌疑人在场的检测,但不影响对列队辨认的基于猜测的选择。
Sci Rep. 2025 Aug 4;15(1):28382. doi: 10.1038/s41598-025-13937-w.
2
On the advantages of using AI-generated images of filler faces for creating fair lineups.利用 AI 生成的填充物人脸图像创建公平的列队的优势。
Sci Rep. 2024 May 29;14(1):12304. doi: 10.1038/s41598-024-63004-z.
3
New Insights on Expert Opinion About Eyewitness Memory Research.关于目击证人记忆研究的专家意见新见解。
Perspect Psychol Sci. 2025 Sep;20(5):903-924. doi: 10.1177/17456916241234837. Epub 2024 Apr 18.
4
Enabling witnesses to actively explore faces and reinstate study-test pose during a lineup increases discriminability.使证人在列队辨认过程中积极探索面部特征并重新摆出研究-测试姿势,可提高辨别力。
Proc Natl Acad Sci U S A. 2023 Oct 10;120(41):e2301845120. doi: 10.1073/pnas.2301845120. Epub 2023 Oct 2.
5
A descriptive study on misidentifications of a person as a familiar person in an everyday situation.一项关于在日常情况下将某人错误识别为熟人的描述性研究。
Sci Rep. 2023 May 26;13(1):8530. doi: 10.1038/s41598-023-35094-8.
6
Evaluating the impact of first-yes-counts instructions on eyewitness performance using the two-high threshold eyewitness identification model.运用双高阈限目击者识别模型评估首肯计数指令对目击者表现的影响。
Sci Rep. 2023 Apr 21;13(1):6572. doi: 10.1038/s41598-023-33424-4.
7
Measuring lineup fairness from eyewitness identification data using a multinomial processing tree model.使用多项处理树模型从目击者识别数据衡量阵容公平性。
Sci Rep. 2023 Apr 18;13(1):6290. doi: 10.1038/s41598-023-33101-6.
8
The effect of pre-event instructions on eyewitness identification.事前指示对目击证人辨认的影响。
Cogn Res Princ Implic. 2023 Feb 28;8(1):16. doi: 10.1186/s41235-023-00471-4.
9
Identifying unfamiliar voices: Examining the system variables of sample duration and parade size.识别不熟悉的声音:考察样本时长和列队大小的系统变量。
Q J Exp Psychol (Hove). 2023 Dec;76(12):2804-2822. doi: 10.1177/17470218231155738. Epub 2023 Mar 7.
10
Experimental validation of a multinomial processing tree model for analyzing eyewitness identification decisions.多分类处理树模型分析目击证人辨认决策的实验验证。
Sci Rep. 2022 Sep 16;12(1):15571. doi: 10.1038/s41598-022-19513-w.