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Record W2373320077 · doi:10.3917/nrp.021.0085

Travail et consommation de substances psychoactives : contributions des syndicats québécois à la prévention

2016· article· fr· W2373320077 on OpenAlexaboutno aff
Jean-Simon Deslauriers, Marie-France Maranda

Bibliographic record

VenueNouvelle revue de psychosociologie · 2016
Typearticle
Languagefr
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Les transformations du marché du travail associées à l’organisation flexible mettent en place une norme de performance et d’excellence à laquelle il peut devenir difficile de résister. Dans ce contexte, les pratiques de consommation de substances psychoactives en lien avec le travail se transforment, notamment comme moyen pour les travailleurs de maintenir une performance exceptionnelle ou de faire face à la souffrance de ne pas y arriver. Ce texte, qui s’appuie principalement sur une thèse de doctorat qui a étudié des initiatives syndicales québécoises en prévention des problèmes de santé mentale au travail, a un double objectif. D’abord, il vise à montrer les liens entre l’organisation du travail et l’apparition ou le développement d’une consommation problématique de substances psychoactives chez les travailleurs, consommation qui peut être comprise notamment comme une stratégie défensive au sens de la psychodynamique du travail déployée pour faire face aux exigences d’une organisation du travail hyperflexible. Ensuite, le texte décrit une initiative syndicale québécoise des réseaux d’entraide en milieu de travail en vue de discuter du rôle des pairs entraidants dans la prévention des problèmes de santé mentale au travail, y compris la consommation de substances psychoactives.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.243

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0140.005
Scholarly communication0.0070.003
Open science0.0010.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.080
GPT teacher head0.458
Teacher spread0.378 · 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 designQualitative
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
Published2016
Admission routes1
Has abstractyes

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Same venueNouvelle revue de psychosociologieSame topicOccupational Health and Safety ResearchFrench-language works237,207