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Record W2098635219 · doi:10.1348/135532507x186653

Halfe the world knowes not how the other halfe lies: Investigation of verbal and non‐verbal signs of deception exhibited by criminal offenders and non‐offenders

2007· article· en· W2098635219 on OpenAlexaff
Stephen Porter, Naomi L. Doucette, Michael Woodworth, Jeff Earle, Bonnie M. MacNeil

Bibliographic record

VenueLegal and Criminological Psychology · 2007
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsMinistry of Community Safety and Correctional ServicesQueen's UniversityUniversity of British ColumbiaUniversity of New BrunswickDalhousie University
Fundersnot available
KeywordsLyingDeceptionPsychologyLie detectionCredibilitySocial psychologyNonverbal communicationDevelopmental psychology

Abstract

fetched live from OpenAlex

Purpose. This study examined the verbal and non‐verbal behaviours exhibited by criminal offender and non‐offender participants while they related planned truthful and deceptive accounts about emotional autobiographical events. Methods. In a 2 × 2 (participant group × veracity) quasi‐experimental design, offenders ( N = 27) and university students ( N = 38) provided videotaped accounts of four autobiographical emotional events: two honest and two fabricated (counterbalanced). Patterns of behaviour exhibited during the truthful and the deceptive accounts were then compared. Results. In general, offenders and non‐offenders showed similar patterns of deceptive behaviour. Deceptive accounts by both groups contained fewer details than honest accounts. Deception was associated with an increase in illustrator usage and self‐manipulations; however, univariate analyses indicated only that offenders exhibited significantly more self‐manipulations when lying. A significant interaction emerged in which offenders showed a reduction in smiles when lying about the emotional events, while students showed no difference. Conclusions. Offenders and students showed similar patterns of lying on most cues. However, unlike non‐offenders, offenders smiled less and showed an increase in self‐manipulations when lying. We theorize that offenders may have been aware that smiling and laughing are negatively related to perceived credibility in the speaker and used self‐manipulations to distract listeners from the content of their lies.

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 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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.841
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.077
GPT teacher head0.328
Teacher spread0.251 · 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 teacher head, not a consensus.

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

Citations39
Published2007
Admission routes1
Has abstractyes

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