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Simon Rjosk

Bio: Simon Rjosk is an academic researcher. The author has contributed to research in topics: Law enforcement. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.

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Journal ArticleDOI
TL;DR: In this paper , the authors benchmark the three most challenging face identity processing (FIP) tests available against two work-samples and find that performance on either work-sample was better predicted by performance on the other than by lab-based test scores.

3 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated whether police officers' performance in searching for unfamiliar faces in a video-based real-world task is predicted by laboratory-based face processing tests that are typically used to assess individual differences in face processing abilities.
Abstract: In the present study, we investigated whether police officers’ performance in searching for unfamiliar faces in a video-based real-world task is predicted by laboratory-based face processing tests that are typically used to assess individual differences in face processing abilities. Specifically, perceptual performance in the field was operationalized via the identification of target individuals in self-made close-circuit television (CCTV) video tapes. Police officers’ abilities in the laboratory were measured by the Cambridge Face Memory Test long form (CFMT+). We hypothesized that the CFMT+ predicts individual differences in the CCTV task performance. A total of N = 186 police officers of the Rhineland-Palatinate State Police participated in the study (i.e., N = 139 novice and advanced cadets with either 3 months, 15 months or 24 months of pre-service experience; N = 47 experienced police officers with three years of pre-service experience and at least two years of full-service experience, who participated in the assessment center of the special police forces, specifically the surveillance and technical unit). Results revealed that the CFMT+ explained variance in the CCTV task. In sample 1, CFMT+ scores predicted hits, but not false alarms. In contrast, in sample 2, CFMT+ scores were correlated with both hits and false alarms. From a theoretical perspective, we discuss factors that might explain CCTV task performance. From a practical perspective, we recommend that personnel selection processes investigating individual differences of police officers’ face processing abilities should comprise of two steps. At first, laboratory-based tests of face processing abilities should be applied. Subsequently, to validate laboratory-based individual differences in face processing abilities, we recommend that work samples such as CCTV tasks from the field should be added.

3 citations

Journal ArticleDOI
17 May 2023-PLOS ONE
TL;DR: In this article , an end-to-end selection process was used to establish an SR unit in a large police force and 38 super-recognisers were recruited from this cohort to complete 10 follow-up tests.
Abstract: People vary in their ability to recognise faces. These individual differences are consistent over time, heritable and associated with brain anatomy. This implies that face identity processing can be improved in applied settings by selecting high performers–‘super-recognisers’ (SRs)–but these selection processes are rarely available for scientific scrutiny. Here we report an ‘end-to-end’ selection process used to establish an SR ‘unit’ in a large police force. Australian police officers (n = 1600) completed 3 standardised face identification tests and we recruited 38 SRs from this cohort to complete 10 follow-up tests. As a group, SRs were 20% better than controls in lab-based tests of face memory and matching, and equalled or surpassed accuracy of forensic specialists that currently perform face identification tasks for police. Individually, SR accuracy was variable but this problem was mitigated by adopting strict selection criteria. SRs’ superior abilities transferred only partially to body identity decisions where the face was not visible, and they were no better than controls at deciding which visual scene that faces had initially been encountered in. Notwithstanding these important qualifications, we conclude that super-recognisers are an effective solution to improving face identity processing in applied settings.

1 citations