The lineup construction process and eyewitness identifications

该奖项是NSF社会、行为和经济科学(SBE)博士后研究奖学金(SPRF)计划和SBE法律和科学计划的一部分。SPRF计划的目标是为学术界、工业界或私营部门和政府的科学职业生涯培养有前途的、早期职业博士水平的科学家。SPRF奖项包括在知名科学家的赞助下进行两年的培训，并鼓励博士后研究员进行独立研究。国家科学基金会致力于促进科学界所有阶层的科学家参与其研究方案和活动，包括那些来自代表性不足的群体的科学家；博士后阶段被认为是实现这一目标的专业发展的一个重要水平。每个博士后研究员都必须解决推动各自学科领域向前发展的重要科学问题。在马萨诸塞大学阿默斯特分校杰弗里·斯塔恩斯博士的赞助下，这一博士后奖学金奖项支持一位研究阵容构建过程的早期职业科学家。列队经常被用来从目击者那里收集证据。名单通常由嫌疑人的照片组成，嫌疑人可能有罪，也可能没有罪，与无辜个人的照片一起展示，称为填充物。填充者通常由警察选择，通常是根据与嫌疑人的相似性。在刑事调查中，目击证人身份是重要的证据来源，在许多情况下，目击证人是唯一可用的证据。不幸的是，目击者对无辜嫌疑人的误认是导致错误定罪的重要因素，而且众所周知，存在差异，对个人和社区可能造成毁灭性的后果。该项目将调查列队的构建过程以及列队的组成结构对目击证人辨认准确性的影响，重点是特别容易出错的辨认情况。通过采用一种新的方法来分析阵容组成，该项目将阐明有助于阵容构建的因素，并确定支持更准确识别的阵容的特征。该项目将通过使用多维比例尺(MDS)解决一项研究不足的任务(阵容构建)来解决该领域的一个重大差距，MDS是一种在外地使用有限的先进统计工具。该分析方法和结果将为有关阵容建设的政策提供参考，并有助于理论的发展。该项目有三个主要组成部分：(1)相似性判断；(2)由感知者构建阵容；(3)使用(2)中的阵容识别目击者。多维尺度(MDS)分析将应用于(1)中的相似性判断，生成两个多维人脸空间，它们描绘出感知器如何表示人脸。心理面孔空间将被用来揭示感知者构建的阵容的相似结构。然后，这些阵容将在目击者识别研究中进行测试，使用单独的大样本参与者。这项研究工作将为阵容记忆和决策过程的理论发展和计算建模提供基础。这些对阵容属性的精确测量将加深我们对相关问题的理解，并阐明文献中不一致的发现。这些数据以及刺激集和分析代码将通过公共存储库提供给其他研究人员，这将支持研究基础设施并推动进一步的研究。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award was provided as part of NSF's Social, Behavioral and Economic Sciences (SBE) Postdoctoral Research Fellowships (SPRF) program and SBE's Law and Science program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Jeffrey Starns at the University of Massachusetts Amherst, this postdoctoral fellowship award supports an early career scientist investigating the lineup construction process. Lineups are frequently used to gather evidence from eyewitnesses. A lineup typically consists of a photo of the suspect, who may or may not be guilty, presented alongside photos of innocent individuals, referred to as fillers. The fillers are usually selected by police officers, often based on similarity to the suspect. Eyewitness identifications from lineups constitute an important source of evidence in criminal investigations, and in many cases, eyewitnesses provide the only available evidence. Unfortunately, eyewitness misidentifications of innocent suspects are significant contributors to wrongful convictions, and are known to be plagued with disparities, with potentially devastating consequences for individuals and communities. This project will investigate the process of lineup construction and the effects of the compositional structure of lineups on the accuracy of eyewitness identifications, with a focus on a particularly error-prone identification scenario. By taking a novel approach to the analysis of lineup composition, this project will elucidate factors contributing to lineup construction and identify the characteristics of a lineup that support more accurate identifications. The project will address a significant gap in the field by addressing an under-researched task (lineup construction) using multidimensional scaling (MDS), an advanced statistical tool that has had limited use in the field. The analytical approach and findings will inform policy on lineup construction and contribute to theory development.The project has three main components: (1) similarity judgments; (2) construction of lineups by perceivers; and (3) eyewitness identification using the lineups from (2). Multidimensional scaling (MDS) analyses will be applied to the similarity judgments from (1), generating two multidimensional face spaces that map out how faces are represented by perceivers. The psychological face spaces will be used to reveal the similarity structure of lineups constructed by perceivers. These lineups will then be tested in an eyewitness identification study, using a separate, large sample of participants. This research effort will provide the grounds for theory development and computational modeling of lineup memory and decision-making processes. These precise measurements of lineup properties will deepen our understanding of the relevant issues and shed light on inconsistent findings in the literature. The data, as well as the stimuli set and the analysis code, will be made available for other researchers via public repositories, which will support research infrastructure and spur further research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.