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Record W4200529804 · doi:10.1002/acp.3910

Effects of stress on eyewitness identification in the laboratory

2021· article· en· W4200529804 on OpenAlexafffund
Heather L. Price, Laurie Sykes Tottenham, Bianca Hatin, Ryan J. Fitzgerald, Eva Rubínová

Bibliographic record

VenueApplied Cognitive Psychology · 2021
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsSimon Fraser UniversityUniversity of ReginaThompson Rivers University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsPsychologyTrier social stress testSurpriseEyewitness identificationStress (linguistics)Identification (biology)Social psychologyHeart rateDevelopmental psychologyCognitive psychologyFight-or-flight responseBlood pressure

Abstract

fetched live from OpenAlex

Abstract Witnesses to crime often experience stress during the witnessed event. However, most laboratory studies examining eyewitness memory do not include a stressful encoding event. Participants (N = 129) completed an experimental stress induction procedure—a modified version of the Trier Social Stress Test. We designed three conditions to manipulate the amount of stress experienced and included three types of measures to assess the effectiveness of the manipulation: cortisol levels (hormonal), blood pressure and heart rate (autonomic), and self‐report (subjective). Participants watched a video that had a surprise viewing of a staged theft and completed two lineup identification tasks. We observed no effects of stress on the accuracy or willingness to choose from a lineup. Importantly, there was variability in the correspondence between measured indicators of stress, which should be considered in future designs.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.338
Teacher spread0.311 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2021
Admission routes2
Has abstractyes

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