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Record W4403208060 · doi:10.26034/la.cfs.2024.4694

Article court : Le comportement non verbal lors de procès devrait-il être ignoré?

2024· article· fr· W4403208060 on OpenAlexaffabout
Vincent Denault, Victoria Talwar

Bibliographic record

VenueCriminologie Forensique et Sécurité · 2024
Typearticle
Languagefr
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsMcGill UniversityUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Au Canada, la Cour suprême du Canada reconnait l’importance de la communication non verbale lors de procès, tant pour l’évaluation de la crédibilité que pour le contre-interrogatoire. Toutefois, en pratique, la popularité de croyances non fondées et démontrées fausses soulève des questions quant à l’usage de du comportement non verbal lors de procès. Devant un tel constat, le comportement non verbal lors de procès devrait-il être ignorée? Pour répondre à cette question, dans un premier temps, un retour sur les fonctions du comportement non verbal sera effectué et, dans un deuxième temps, les arguments contre l’usage du comportement non verbal seront résumés. Cet article court se termine par un appel à apprécier à sa juste valeur le comportement non verbal des témoins lors de procès.

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)0.003
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.161
Threshold uncertainty score0.319

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.009
Scholarly communication0.0100.004
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0130.002

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 head0.087
GPT teacher head0.387
Teacher spread0.300 · 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 designNot applicable
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

Citations0
Published2024
Admission routes2
Has abstractyes

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