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Record W3125318338 · doi:10.7202/1074195ar

Perceptions des pratiques en matière d’audition de suspects

2020· article· fr· W3125318338 on OpenAlexvenueno aff
Mathilde Noc, Magali Ginet

Bibliographic record

VenueCriminologie · 2020
Typearticle
Languagefr
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical sciencePsychology

Abstract

fetched live from OpenAlex

Le principal objectif de cette étude était d’évaluer les perceptions d’agents des douanes françaises en matière d’audition de suspects. Étant donné le peu de formation théorique existant en France, il était attendu que ces agents déclarent utiliser des méthodes considérées comme néfastes, dans la littérature scientifique, pour le déroulement et l’efficacité de la conduite d’auditions. Soixante-quatorze agents des douanes ont répondu à un questionnaire les invitant à évaluer l’usage, dans leur pratique, de méthodes d’audition de suspects, certaines étant considérées comme bénéfiques et d’autres, néfastes. Conformément à nos attentes, les résultats ont indiqué que les agents des douanes déclaraient utiliser certaines méthodes bénéfiques pour le déroulement de l’audition, mais aussi néfastes, telles que l’usage privilégié d’un questionnement fermé, la maximisation, la pression, etc. Les niveaux d’expérience et de présomption de culpabilité avaient également un impact sur les méthodes utilisées. L’analyse du questionnement a permis de montrer que les questions dirigées étaient largement utilisées. Des préconisations en termes de formation professionnelle sont formulées.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0670.024

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 head0.310
GPT teacher head0.432
Teacher spread0.122 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2020
Admission routes1
Has abstractyes

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