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Record W2010306295 · doi:10.4000/pistes.3086

Gestion par projets et risques pour la santé psychologique au travail dans la nouvelle économie

2006· article· fr· W2010306295 on OpenAlexvenueno aff
Marie‐Josée Legault, Hind Belarbi-Basbous

Bibliographic record

VenuePerspectives interdisciplinaires sur le travail et la santé · 2006
Typearticle
Languagefr
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Y a-t-il des problèmes de santé mentale propres au travail dans la nouvelle économie ? Quoiqu’on puisse constater que le modèle de demande psychologique - autonomie décisionnelle de Karasek et Theorell- trouve aussi son application dans les milieux de travail qui empruntent cette forme, on observe, en fait, des formes particulières de ces facteurs dans la forme d’organisation du travail propre à la gestion par projets. Assimilables à « l’hypersollicitation par le client » comme il a été repéré par Christophe Dejours, ces formes ont été observées lors d’une enquête menée récemment sur la conciliation entre la vie privée et la vie professionnelle dans sept organisations montréalaises. La recherche qualitative a recueilli en tout le discours de 88 répondants distribués également selon le sexe et exerçant des fonctions liées au génie informatique. Ces observations permettent d’envisager une nuance au modèle théorique de la santé mentale ci-haut mentionné, visant à tenir compte des effets délétères d’une très grande latitude décisionnelle assortie de très grandes responsabilités chez des travailleurs hautement qualifiés.

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)0.007
metaresearch head score (Gemma)0.027
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 score0.082
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.004
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0210.002

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 head0.025
GPT teacher head0.416
Teacher spread0.390 · 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

Citations9
Published2006
Admission routes1
Has abstractyes

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