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Record W4366496396 · doi:10.1080/13218719.2023.2175074

Remaining silent during interrogation

2023· article· en· W4366496396 on OpenAlexafffund
Mark Snow, Quintan Crough, Cassandre Dion Larivière, Funmilola Ogunseye, Joseph Eastwood

Bibliographic record

VenuePsychiatry Psychology and Law · 2023
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsOntario Tech University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSuspectInterrogationDenialPsychologySilenceConfession (law)Social psychologyCriminologyLawPolitical sciencePsychoanalysis

Abstract

fetched live from OpenAlex

In many Western jurisdictions, criminal suspects undergoing police interrogations have the right to remain silent. In this experiment, we examined the effects of remaining silent during police questioning on laypersons’ perceptions of a suspect. Participants (N = 126) read one of three mock-interview transcripts (i.e. admission, denial or silence) and indicated the extent to which they agreed or disagreed that a male suspect in a missing person case was guilty, cooperative, trustworthy and rational. Participants expressed stronger agreement that the suspect was guilty when he admitted guilt than when he denied involvement or remained silent. When the suspect remained silent, participants viewed the suspect as less cooperative than when the suspect denied or admitted guilt and as less rational than when the suspect denied committing the crime. Our findings provide some support for the notion that remaining silent during police questioning may be viewed unfavourably by external observers.

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)0.006
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.064
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.348
Teacher spread0.322 · 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 designObservational
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

Citations2
Published2023
Admission routes2
Has abstractyes

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