The lineup construction process and eyewitness identifications

该奖项是美国国家科学基金会（NSF）社会、行为和经济科学（SBE）博士后研究奖学金（SPRF）计划和SBE法律与科学计划的一部分。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事业准备有前途的早期职业博士级科学家。SPRF奖励包括在知名科学家的赞助下进行为期两年的培训，并鼓励博士后进行独立研究。美国国家科学基金会寻求促进科学界各阶层的科学家，包括那些未被充分代表的群体的科学家，参与其研究项目和活动；博士后阶段被认为是实现这一目标的一个重要的专业发展阶段。每个博士后必须解决各自学科领域的重要科学问题。在马萨诸塞大学阿默斯特分校杰弗里·斯特恩斯博士的赞助下，这项博士后奖学金奖励支持一位早期职业科学家调查阵容构建过程。指认经常被用来从目击者那里收集证据。一个典型的指认包括一张可能有罪也可能无罪的嫌疑人的照片，以及被称为“填充者”的无辜者的照片。填充物通常是由警察根据与嫌疑人的相似度来选择的。在刑事调查中，证人的指认是重要的证据来源，在许多情况下，证人是唯一可用的证据。不幸的是，目击者对无辜嫌疑人的错误指认是造成错误定罪的重要原因，而且众所周知，这种情况存在差异，给个人和社区带来潜在的毁灭性后果。该项目将调查阵容构建过程以及阵容组成结构对目击者识别准确性的影响，重点关注一个特别容易出错的识别场景。通过采用一种新颖的方法来分析阵容组成，本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特征。该项目将通过使用多维尺度（MDS）解决研究不足的任务（阵容构建）来解决该领域的重大空白，MDS是一种先进的统计工具，在该领域的应用有限。分析方法和结果将为阵容建设政策提供信息，并有助于理论发展。该项目有三个主要组成部分：(1)相似性判断；(2)感知者对队列的建构；(3)利用(2)的指认指认目击者。多维尺度（MDS）分析将应用于(1)的相似性判断，生成两个多维人脸空间，绘制出感知者如何表示人脸。心理面空间将被用来揭示由感知者构建的队列的相似性结构。然后，这些人将在一项目击者识别研究中进行测试，使用一个单独的、大样本的参与者。本研究将为阵容记忆与决策过程的理论发展和计算建模提供依据。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促进进一步的研究。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.