Collaborative Research: RUI: Understanding and Predicting Eyewitness Identification Errors: Studies Using a Unique Set of Materials from Actual Lineups

合作研究：RUI：理解和预测目击者识别错误：使用来自实际阵容的一组独特材料的研究

• 批准号: 1420135
• 负责人: Nancy Steblay
• 金额: $ 13.42万
• 依托单位: Augsburg University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1420135&HistoricalAwards=false
• 关键词: Collaborative; Research; RUI; Understanding; Predicting

Forensic DNA testing has freed hundreds of innocent people in the U.S. and approximately 75% of these convictions involved mistaken eyewitness identification. The need to identify reliable ways to sort between accurate and mistaken identifications is readily apparent. Theory and data from laboratory-simulation experiments indicate that accurate and mistaken identifications differ in measurable ways (e.g., identification speed, confidence, witness verbalizations). Lab research also shows that lineup biases (e.g., innocent suspect stands out or administrator unintentionally steers the witness) can inflate mistaken identifications. Lab simulation participants, however, know that the crime is not real and fail to capture potentially important dynamics of actual witnesses (e.g., fear, justice motivations, concern for consequences). The researchers have unique materials from actual cases involving 855 photo-lineups where only one person in each lineup was a suspect. The other lineup members were known-innocent fillers. Filler identifications, which constitute mistaken identifications, comprise 34% of all identifications. Software provided by the researchers made audio recordings of witnesses' verbalizations, speed of identifications, and other relevant information for each lineup. A majority of the lineups were administered double-blind; thus, lineup administrators were unaware of which was the suspect's photo and hence could not steer the witness. Four studies were conducted. Study 1 tests whether lineup bias predicts mistaken identifications. Study 2 tests whether witness verbalizations predict mistakes. Study 3 tests whether mistakes are slower and made with less certainty than suspect identifications. Study 4 tests whether double-blind lineup procedures evidence less steering by the lineup administrators. Data analyses involve hierarchical, mixed model log-linear analyses or ANOVAs. This work can help translate lab simulation findings to actual cases and thereby help the justice system sort between mistaken and accurate identifications. Results will be shared broadly with scientists, police and prosecutors. Undergraduate students, including first-generation and those of color at a small undergraduate college, will receive research training in this project.

在美国，法医DNA测试已经释放了数百名无辜的人，其中大约75%的定罪涉及错误的目击者身份识别。很明显，需要找到可靠的方法来区分准确和错误的识别。来自实验室模拟实验的理论和数据表明，准确和错误的识别在可测量的方式上是不同的（例如，识别速度、置信度、证人语言表达）。实验室研究还表明，阵容偏见（例如，无辜的嫌疑人站出来或管理员无意中引导证人）可以夸大错误的识别。然而，实验室模拟参与者知道犯罪不是真实的，并且未能捕捉到实际证人的潜在重要动态（例如，恐惧、正义动机、对后果的关注）。研究人员从855张照片中获得了独特的材料，每个照片中只有一个人是嫌疑人。其他的嫌疑人都是众所周知的无辜的填充者。在所有鉴定中，构成错误鉴定的填充鉴定占34%。研究人员提供的软件对证人的口头陈述、指认速度和每个列队的其他相关信息进行了录音。大部分的列队都是双盲的;因此，列队管理员不知道哪张是嫌疑人的照片，因此无法引导证人。进行了四项研究。研究1测试是否阵容偏见预测错误的识别。研究2测试证人言语是否预测错误。研究3测试错误是否比可疑识别更慢，更不确定。研究4测试了双盲队列程序是否证明队列管理员的指导较少。数据分析涉及分层、混合模型对数线性分析或ANOVA。这项工作可以帮助将实验室模拟结果转化为实际案件，从而帮助司法系统在错误和准确的识别之间进行分类。研究结果将与科学家、警察和检察官广泛分享。本科生，包括第一代和那些在一个小的本科学院的颜色，将在这个项目中接受研究培训。