Kukucka, J;
Dror, IE;
Yu, M;
Hall, L;
Morgan, RM;
(2020)
The impact of evidence lineups on fingerprint expert decisions.
Applied Cognitive Psychology
, 34
(5)
pp. 1143-1153.
10.1002/acp.3703.
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Abstract
Forensic examiners routinely compare a crime‐relevant mark of unknown origin against a single suspect's sample, which may create an expectation that the two will match. We tested how embedding the suspect's sample among known‐innocent fillers (i.e., an evidence lineup ) affects expert decision‐making. Experienced fingerprint examiners (N = 43) compared crime‐relevant marks against either individual suspect fingerprints (i.e., the standard procedure) or arrays of fingerprints (i.e., evidence lineups), with a matching fingerprint either present or absent. Evidence lineups promoted conservative decision‐making, as evidenced by fewer correct IDs and a higher rate of inconclusive judgments. Though errors were rare, evidence lineups also occasionally revealed errors that would have otherwise gone undetected. Our findings thus support arguments that evidence lineups can expose fraud, identify flawed methodologies, and curb overconfidence. The potential benefits and challenges of implementing evidence lineups in forensic laboratories are discussed.
Type: | Article |
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Title: | The impact of evidence lineups on fingerprint expert decisions |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1002/acp.3703 |
Publisher version: | https://doi.org/10.1002/acp.3703 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | forensic science; cognitive bias; expert decision-making; fingerprints; evidence lineups |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Security and Crime Science |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10107154 |
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