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Record W4367672610 · doi:10.7202/1098911ar

Le traitement de la violence conjugale comme un enjeu de SST au Canada : une étude empirique

2023· article· fr· W4367672610 on OpenAlexaffabout
Rachel Cox, Mélanie Ederer

Bibliographic record

VenueCommunitas · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsLegislationPolitical scienceOccupational safety and healthHumanitiesLawArt

Abstract

fetched live from OpenAlex

La violence conjugale (VC) est un enjeu important pour les milieux de travail, et ce, tant du point de vue de la productivité que de la sécurité au travail. Pourtant, au Québec et au Canada, la conception de la VC en tant que dimension de la santé et de la sécurité du travail (SST) est relativement récente. Peu d’études sur la VC et le travail portent sur des interventions, et encore moins sur celles de nature préventive. Cette étude contribue à combler cette lacune. Elle présente les résultats d’une série d’entretiens avec des informatrices-clés dans différentes juridictions canadiennes où la législation en SST vise la VC. L’étude suggère que, pour que la législation puisse atteindre son but, la sensibilisation à la VC dans les milieux de travailreprésente un élément incontournable. De plus, les ressources communautaires spécialisées en VC ont un rôle crucial à jouer dans la mise en œuvre de la législation.

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)0.014
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.741

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.007
Science and technology studies0.0120.007
Scholarly communication0.0060.002
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.044
GPT teacher head0.336
Teacher spread0.292 · 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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