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Record W1978483367 · doi:10.3917/riges.322.0031

Promouvoir la santé mentale au travail : donner un sens au travail

2007· article· fr· W1978483367 on OpenAlexvenueno aff
Estelle M. Morin, Jacques Forest

Bibliographic record

VenueGestion · 2007
Typearticle
Languagefr
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPsychologySociologyPhilosophy

Abstract

fetched live from OpenAlex

Résumé Le travail peut stimuler le bien-être psychologique des personnes. Les recherches que nous avons menées auprès de cadres et d’employés ont permis de déterminer plusieurs facteurs qui contribuent à préserver la santé mentale : l’utilité sociale du travail, la rectitude morale du travail, l’exercice de l’autonomie, les occasions d’apprentissage et de développement ainsi que la qualité des relations professionnelles. Observation étonnante, les facteurs qui expliquent le mieux les scores de bien-être psychologique ne sont pas les mêmes que ceux qui expliquent les scores de détresse psychologique. Serait-il possible que la promotion du bien-être psychologique au travail requière des interventions différentes de celles visant la prévention des troubles de santé mentale? D’autres recherches sont nécessaires avant de conclure. Cependant, si cette observation s’avérait exacte, cela aurait des implications importantes pour la recherche future et son application à la gestion du travail.

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)0.011
metaresearch head score (Gemma)0.016
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 score0.024
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0060.016
Scholarly communication0.0080.005
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.017
GPT teacher head0.344
Teacher spread0.327 · 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

Citations50
Published2007
Admission routes1
Has abstractyes

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