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Record W7056432898

Exposition aux risques psychosociaux et détresse psychologique des travailleurs québécois selon la taille d'entreprise

2014· other· fr· W7056432898 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languagefr
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsnot available
Fundersnot available
KeywordsWorkplace safetyJob insecurityPerceived organizational support
DOInot available

Abstract

fetched live from OpenAlex

Les milieux de travail ont un impact significatif sur la santé psychologique des employés. Même si la contribution des petites et moyennes entreprises (PME) comme employeurs s’avère cruciale au Québec, les problématiques de santé psychologique et d’environnement psychosocial de travail y demeurent méconnues. Cette étude vise à décrire la situation actuelle en matière de santé psychologique au travail dans les PME et les grandes entreprises en utilisant un échantillon représentatif de 4608 travailleurs québécois. De plus, trois gestionnaires travaillant à temps plein dans des PME québécoises sont interrogés en entrevues. Les résultats suggèrent que les travailleurs des très petites entreprises sont moins susceptibles d’être exposés à un déséquilibre efforts-récompenses et à de la tension au travail que ceux des petites, des moyennes et des grandes organisations. Les interventions sur la santé psychologique au travail devraient être adaptées en fonction de la taille de l’entreprise et de ses besoins particuliers. Mots-clés : petites et moyennes entreprises, santé psychologique au travail, risques psychosociaux, détresse psychologique, taille d’entreprise, tension au travail, déséquilibre efforts-récompenses.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, 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: Other · Consensus signal: Other
Teacher disagreement score0.612
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.1890.024

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 head0.024
GPT teacher head0.290
Teacher spread0.267 · 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
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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Same topicThermal properties of materialsFrench-language works237,207