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Record W2807713067 · doi:10.1522/revueot.v26i1-2.212

La violence au travail subie par les gestionnaires en sécurité incendie au Québec

2017· article· fr· W2807713067 on OpenAlexaffvenueabout
Laetitia Larouche, Jacinthe Douesnard

Bibliographic record

VenueRevue Organisations & territoires · 2017
Typearticle
Languagefr
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsUniversité du Québec à ChicoutimiUniversité de Sherbrooke
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

De nombreuses manifestations de violence au travail, tel que le harcèlement, sont aujourd’hui sanctionnées dans plusieurs pays. Considérer cette problématique comme résolue serait toutefois une erreur puisqu’elle affecte encore plusieurs travailleurs, dont certains gestionnaires en sécurité incendie. Devant l’absence de littérature scientifique québécoise portant précisément sur la violence dans ce milieu de travail, il devient nécessaire de décrire les conduites hostiles qui y sont présentes afin de mieux comprendre le phénomène. Cet article expose les résultats d’une étude effectuée selon un devis corrélationnel transversal, dressant un portrait quantitatif de la violence au travail subie par 158 gestionnaires des services incendie du Québec. Les prévalences de violence au travail, les types de comportements hostiles les plus fréquents dans le milieu et certaines caractéristiques des agresseurs seront présentés pour finalement proposer une réflexion sur la violence présente dans les services incendie.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.051
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.375
Teacher spread0.331 · 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

Citations1
Published2017
Admission routes3
Has abstractyes

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