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Record W2416019682 · doi:10.3917/spub.083.0121

La prévention des problèmes de santé psychologique liés au travail : nouveau défi pour la santé publique

2008· article· fr· W2416019682 on OpenAlexaff
Michel Vézina

Bibliographic record

VenueSanté Publique · 2008
Typearticle
Languagefr
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsCentre de Santé et de Services Sociaux de la Vieille-Capitale
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Over the last few decades, the workplace environment has undergone profound changes that have been shown to be related to the development of mental health problems. Theoretical models have been developed and validated in order to identify specific psychosocial dimensions of the work environment which represent an occupational health risk. They are the "demand-autonomy-support" model and the "effort-reward imbalance" model. In addition to reducing the complexity of the psychosocial reality of work to a set of significant elements in terms of health risks, these models facilitate the development and implementation of effective organisational interventions in the workplace setting. Four theory-grounded and empirically supported adverse psychosocial occupational risk factors have been identified: high psychological demands, low scope for decision-making, low social support, and low reward. From a public health perspective, the implementation of preventive measures and reduction of psychosocial risk factors at work have been shown to be feasible and effective interventions.

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)0.015
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.384
Teacher spread0.362 · 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 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

Citations3
Published2008
Admission routes1
Has abstractyes

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