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| Funder | Economic and Social Research Council |
|---|---|
| Recipient Organization | University of Kent |
| Country | United Kingdom |
| Start Date | Sep 30, 2024 |
| End Date | Dec 31, 2027 |
| Duration | 1,187 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2925047 |
Forensic facial examiners in the police are skilled in the identity comparison of faces, even under conditions where automatic recognition systems fail. It is unclear why forensic examiners perform at such a high level. Their superiority might stem from complex procedures wherein they first examine faces on their own but must then also work in pairs to come to a final identification decision.
In my PhD, I seek to examine the basis of facial examiner expertise by focusing on these collaborative decision-making processes. I will employ a series of novel paradigms to explore potential mechanisms underlying differences between these forensic experts and laypeople. I will assess what information facial examiners deem relevant when making identification decisions, how selective individuals are about the evidence they accept, and whether differences emerge based on expertise when compared to laypeople.
Across a systematic research programme, I will combine conversational data with behavioural measures such as eye fixations, touch capture, decision accuracy, and choice blindness (e.g., accepting a choice that one has not made as if it were their own). These data-rich experiments will allow me to explore the underlying mechanisms of examiner expertise as well as the evidence that experts consider in reaching collaborative identification decisions.
This coherent body of work will lead to a new cognitive theory of forensic expertise that, for the first time, seeks to understand the complex social interactions underpinning decision-making processes in this task. In turn, these insights will improve training protocols for occupations that rely on facial identification.
University of Kent
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