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Record W1628092717 · doi:10.4000/pistes.1721

La formation visant la prise en charge globale des troubles musculo-squelettiques par l’entreprise : une étude exploratoire

2011· article· fr· W1628092717 on OpenAlexaffvenue
Valérie Tremblay-Boudreault, Nicole Vézina, Denys Denis, Yannick Tousignant‐Laflamme

Bibliographic record

VenuePerspectives interdisciplinaires sur le travail et la santé · 2011
Typearticle
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Un plan de formation a été développé et implanté selon une approche d’ergonomie participative, afin de favoriser la prévention des troubles musculo-squelettiques et la gestion du maintien et du retour au travail par une entreprise de caoutchouc. Les impacts du plan de formation ont été observés sous l’angle des changements de représentation, de la philosophie d’intégration des travailleurs et du développement des compétences à l’interne. Le principal apport de notre intervention réside dans le fait d’avoir combiné la prévention et le retour au travail au plan de formation. Compte tenu du peu de ressources spécialisées en santé et sécurité du travail et aucune en ergonomie, une collaboration entre les acteurs internes et des ressources externes apparait essentielle pour optimiser la prise en charge globale de la prévention des TMS par l’entreprise, en particulier dans un contexte alliant des ressources financières limitées, une population vieillissante de travailleurs et un niveau de contraintes élevé.

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)0.010
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.004
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.035
GPT teacher head0.370
Teacher spread0.335 · 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 designQualitative
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

Citations7
Published2011
Admission routes2
Has abstractyes

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