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

协作研究：理解和预测目击者识别错误：使用实际阵容中的一组独特材料的研究

• 批准号: 1420181
• 负责人: Gary Wells
• 金额: $ 26.34万
• 依托单位: Iowa State 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=1420181&HistoricalAwards=false
• 关键词: Collaborative; Research; Understanding; Predicting; Eyewitness

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.

法医 DNA 检测已在美国解救了数百名无辜者，其中约 75% 的定罪涉及错误的目击证人识别。显而易见，需要找到可靠的方法来区分准确的识别和错误的识别。实验室模拟实验的理论和数据表明，准确的识别和错误的识别在可测量的方面存在差异（例如识别速度、置信度、证人言语）。实验室研究还表明，阵容偏差（例如，无辜嫌疑人脱颖而出或管理员无意中引导证人）可能会加剧错误的识别。然而，实验室模拟参与者知道犯罪不是真实的，并且无法捕捉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）。研究人员从涉及 855 个照片排列的实际案例中获得了独特的材料，其中每个排列中只有一个人是嫌疑人。其他阵容成员都是众所周知的无辜填充者。填充物识别构成错误识别，占所有识别的 34%。研究人员提供的软件对证人的言语、辨认速度以及每个阵容的其他相关信息进行了录音。大多数阵容都是双盲进行的。因此，排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 测试阵容偏差是否预示着错误的识别。研究 2 测试证人的言语是否可以预测错误。研究 3 测试了错误是否比可疑识别更慢且确定性更低。研究 4 测试了双盲阵容程序是否证明阵容管理员的指导较少。数据分析涉及分层、混合模型对数线性分析或方差分析。这项工作可以帮助将实验室模拟结果转化为实际案例，从而帮助司法系统对错误的识别和准确的识别进行分类。结果将与科学家、警察和检察官广泛分享。本科生，包括小型本科学院的第一代学生和有色人种学生，将在该项目中接受研究培训。