Skip navigation

The worldwide impact of identifying super-recognisers in police and business

The worldwide impact of identifying super-recognisers in police and business

Davis, Josh P. ORCID: 0000-0003-0017-7159 (2019) The worldwide impact of identifying super-recognisers in police and business. The Cognitive Psychology Bulletin, 4. pp. 17-22. ISSN 2397-2653

[img]
Preview
PDF (Author Accepted Manuscript)
24017 DAVIS_The_Worldwide_Impact_of_Identifying_Super-Recognisers_2019.pdf - Accepted Version

Download (351kB) | Preview

Abstract

Super-recognisers occupy the extreme top end of a wide spectrum of human face recognition ability. Although test scores provide evidence of super-recognisers’ quantitative superiority, their abilities may be driven by qualitatively different cognitive or neurological mechanisms. Some super-recognisers scoring exceptionally highly on multiple short-term face memory tests do not achieve superior performances on measures of simultaneous face matching, long-term face memory and/or spotting faces in a crowd. Heterogeneous performance patterns have implications for police, security or business aiming to utilise super-recognisers’ superior skills. Drawing on a global participant base (N ≈ 6,000,000), as well as theory and empirical research, this paper describes the background, development, and employment of tests designed to measure four components of superior face processing to assist in recruitment and deployment decisions.

Item Type: Article
Uncontrolled Keywords: Face recognition, super-recognisers, memory, police
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Faculty / School / Research Centre / Research Group: Faculty of Education, Health & Human Sciences
Faculty of Education, Health & Human Sciences > Applied Psychology Research Group
Faculty of Education, Health & Human Sciences > School of Human Sciences (HUM)
Related URLs:
Last Modified: 06 Jul 2019 23:57
URI: http://gala.gre.ac.uk/id/eprint/24017

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics