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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Akan, Melisa |
| Country | United States |
| Start Date | Aug 01, 2022 |
| End Date | Jul 31, 2024 |
| Duration | 730 days |
| Number of Grantees | 4 |
| Roles | Co-Principal Investigator; Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2203796 |
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.
Akan, Melisa
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