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Record W2062047329 · doi:10.1037/0021-9010.86.6.1280

Mug shot exposure prior to lineup identification: Interference, transference, and commitment effects.

2001· article· en· W2062047329 on OpenAlex
Jennifer E. Dysart, R. C. L. Lindsay, Robin Hammond, Paul Dupuis

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Applied Psychology · 2001
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsQueen's University
Fundersnot available
KeywordsPsychologyEyewitness identificationShot (pellet)Identification (biology)Social psychologyInterference (communication)Data miningComputer science

Abstract

fetched live from OpenAlex

The effects of viewing mug shots on subsequent identification performance are as yet unclear. Two experiments used a live staged-crime paradigm to determine if interpolated eyewitness exposure to mug shots caused interference, unconscious transference, or commitment effects influencing subsequent lineup accuracy. Experiment 1 (N = 104) tested interference effects. Similar correct decision rates were obtained for the mug shot and no mug shot groups from both perpetrator-present and absent lineups. Experiment 2 (N = 132) tested for commitment and transference effects. Results showed that the commitment group made significantly more incorrect identifications than either the control or the transference group, which had similar false-identification rates. Commitment effects present a serious threat to identification accuracy from lineups following mug shot searches.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.814
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.352
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it