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Record W1545834643 · doi:10.4000/pistes.1664

Pénibilité au travail : reclasser ou prévenir ?

2010· article· fr· W1545834643 on OpenAlexvenueno aff
Franck Héas

Bibliographic record

VenuePerspectives interdisciplinaires sur le travail et la santé · 2010
Typearticle
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La santé de travailleurs peut se trouver irrémédiablement et directement compromise en raison de la pénibilité de certains métiers et/ou fonctions. La réglementation de la pénibilité au travail emprunte à cet égard plusieurs voies. Un retrait du marché du travail de manière progressive ou anticipée peut tout d’abord être envisagé. L’attribution de compensations financières au salarié ayant exercé ou continuant d’être employé dans un milieu pénible est également envisageable. L’obligation légale de reclassement existant en matière d’inaptitude est par ailleurs un autre dispositif pouvant permettre l’aménagement de la relation contractuelle de travail et ce faisant, compenser les conséquences de la pénibilité. Néanmoins, au-delà de ces différentes possibilités, l’amélioration des conditions de travail fondée sur une logique de prévention apparaît comme la seule alternative permettant de prendre en compte la pénibilité et donc de limiter l’impact de certains environnements de travail sur la santé des personnes.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0160.002

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 head0.021
GPT teacher head0.380
Teacher spread0.360 · 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 designNot applicable
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

Citations4
Published2010
Admission routes1
Has abstractyes

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