The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Who can recognize unfamiliar faces? Individual differences and observer consistency in person identification.
Abstract
It can be remarkably difficult to determine whether two photographs of unfamiliar faces depict the same person or two different people. This fallibility is well established in the face perception and eyewitness domain, but most of this research has focused on the "average" observer by measuring mean performance across groups of participants. This study deviated from this convention to provide a detailed description of individual differences and observer consistency in unfamiliar face identification by assessing performance repeatedly, across a 3-day (Experiment 1) and a 5-day period (Experiment 2). Both experiments reveal considerable variation between but also within observers. This variation is such that the same observers frequently made different identification decisions to the same faces on different days (Experiment 1). And when new faces were shown on each day, observers that produced perfect accuracy on one day made many misidentifications on another (Experiment 2). However, a few individuals also performed with consistent high accuracy in these tests. These findings suggest that accuracy and consistency are separable indices of face-matching ability, and both measures are necessary to provide a precise index of a person's face processing skill. We discuss whether these measures could provide the basis for a selection tool for occupations that depend on accurate person identification.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
People have very little insight into their own face identification ability.
“In general, people have very little insight into their own face identification ability [31–34]”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [34]
Citations
Cites
Henrich, J., Heine, S. J., & Norenzayan, A. (2010) · Nature · doi:10.1038/466029a · Cited by 3,441
Flagged first, then by citations
Cited by
Sorted by citations
Do professional facial image comparison training courses work?
Towler, A., Kemp, R. I., Burton, A. M., Dunn, J. D., Wayne, T., Moreton, R., & White, D. (2019) · PLOS ONE · doi:10.1371/journal.pone.0211037 · Cited by 111
Developmental Improvement and Age-Related Decline in Unfamiliar Face Matching
Megreya, A. M., & Bindemann, M. (2015) · Perception · doi:10.1068/p7825 · Cited by 53
Self-citation
Metadata
- Authors
- Bindemann, M., Avetisyan, M., & Rakow, T.
- Venue
- Journal of Experimental Psychology: Applied
- Published
- 2012
- Volume
- 18
- Issue
- 3
- Pages
- 277-291
- ISSN
- 1939-2192
- 1076-898X
- Cited by
- 57
- References
- 1
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review