MétaCan
Menu
Back to cohort
Record W1997763964 · doi:10.1037/lhb0000077

Language style matching and police interrogation outcomes.

2014· article· en· W1997763964 on OpenAlex
Beth H. Richardson, Paul Taylor, Brent Snook, Stacey M. Conchie, Craig Bennell

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

VenueLaw and Human Behavior · 2014
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsCarleton UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsConfession (law)InterrogationMatching (statistics)PsychologySuspectStyle (visual arts)UtteranceSocial psychologyLinguisticsCriminologyLawPolitical science

Abstract

fetched live from OpenAlex

This research examined the coordination of interrogator and suspects' verbal behavior in interrogations. Sixty-four police interrogations were examined at the aggregate and utterance level using a measure of verbal mimicry known as Language Style Matching. Analyses revealed an interaction between confession and the direction of language matching. Interrogations containing a confession were characterized by higher rates of the suspect matching the interrogators' language style than interrogations without a confession. A sequence analysis of utterance-level Language Style Matching revealed a divergence in the type of matching that occurred across outcome. There was a linear increase in interrogator-led matching for interrogations containing a confession and an increase in suspect-led matching for nonconfession interrogations. These findings suggest that police interrogations play out, in part, at the basic level of language coordination.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.351
Teacher spread0.330 · 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