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Record W4406106803 · doi:10.4000/130lc

Le modèle de double régulation de l’activité : un modèle-guide pour la formation en ergonomie à l’Université

2024· article· fr· W4406106803 on OpenAlexvenueno aff
Muriel Prévot-Carpentier, Cathy Toupin

Bibliographic record

VenuePerspectives interdisciplinaires sur le travail et la santé · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicInformation Technology and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Le modèle de la double régulation ou modèle aux cinq carrés proposé par Leplat et Cuny en 1977 est aujourd’hui encore central dans l'analyse de l'activité en ergonomie, en ce qu'il constitue un modèle ouvert, matrice de compréhension de l'activité en situation réelle. Ce modèle définit, dans une approche systémique, les grandes classes de variables et de relations à partir desquelles une activité peut être caractérisée. Plus spécifiquement, il s’agit d’identifier les déterminants qui conditionnent et influencent cette activité, ainsi que ses effets sur l’individu observé et le système qui l’entoure. Cet article vise à définir l'émergence de cette modélisation de l’activité dans les travaux de Jacques Leplat, à expliquer les grands principes du modèle, ainsi qu’à donner à voir et discuter, à partir de l’illustration d’une étude menée dans le secteur hospitalier, son rôle essentiel de guidage pour la formation en ergonomie à l’Université.

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)0.003
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.004
Scholarly communication0.0050.004
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.019
GPT teacher head0.297
Teacher spread0.278 · 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 designTheoretical or conceptual
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

Citations0
Published2024
Admission routes1
Has abstractyes

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