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Record W1766137510 · doi:10.4000/pistes.3022

Les effets conjoints du travail et des horaires alternants sur la santé des agents de surveillance des établissements pénitentiaires

2006· article· fr· W1766137510 on OpenAlexvenueno aff
Pierre Pavageau

Bibliographic record

VenuePerspectives interdisciplinaires sur le travail et la santé · 2006
Typearticle
Languagefr
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Les préoccupations en santé publique révèlent le peu Notre étude vise à comparer les effets sur la santé de trois formes d’organisation temporelle (horaires traditionnels, factions de 6 heures et de 12 heures) au sein d’établissements pénitentiaires français, et plus particulièrement auprès des personnels de surveillance. Des moyens d’investigation complémentaires (questionnaire, observations du travail, traitement statistique) ont été mis en œuvre pour tenter de faire la part entre le poids des horaires et le poids du travail sur l’état de santé des agents. Si les personnels en factions de 12 heures présentent des résultats meilleurs que les personnels en 6 heures, c’est en particulier dû à des avantages dans la vie extra-professionnelle, bien que des signes certains de fatigue ne permettent pas de conclure significativement en faveur de telles modalités. Au-delà de l’alternance des horaires, le contenu du travail pèse de manière importante sur la santé des agents.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.019
GPT teacher head0.348
Teacher spread0.330 · 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

Citations2
Published2006
Admission routes1
Has abstractyes

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