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Record W2112694465 · doi:10.4000/pistes.3045

Quand les ergonomes sont sortis du laboratoire.... à propos du travail des femmes dans l’industrie électronique (1963 – 1973)

2006· article· fr· W2112694465 on OpenAlexvenueno aff
Catherine Teiger, Liliane Barbaroux, Maryvonne David, Jacques Duraffourg, Marie-Thérèse Galisson, Antoine Laville, Louis Thareaut

Bibliographic record

VenuePerspectives interdisciplinaires sur le travail et la santé · 2006
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical sciencePhilosophyHumanities

Abstract

fetched live from OpenAlex

Cette réflexion collective sur la première recherche « de terrain » (il y a 40 ans !) des ergonomes du Conservatoire National des Arts et Métiers (Paris), associe des syndicalistes (« demandeurs ») et des ergonomes (« réalisateurs »). Elle vise à reconstituer le déroulement de cette expérience commune et à tirer des enseignements concernant action syndicale, production des connaissances ergonomiques et transformation du travail. Par le mode d’entrée des chercheurs dans l’entreprise, l’élaboration progressive de la démarche, la production de connaissances inattendues sur le travail réel et ses effets sur la santé, cette recherche sur le travail des femmes ouvrières de la production de masse marque un tournant épistémologique en ergonomie. Obligeant à inventer de nouvelles méthodes, de nouvelles postures de recherche en reconnaissant « l’expertise ouvrière », de nouveaux modèles de l’activité de travail, elle jette les bases d’une dynamique « tourbillonnaire » prolongée jusqu’aujourd’hui fondée sur la coopération entre acteurs et articulant recherche, formation et action. Développements et limites sont aussi soulignés.

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)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.008
Scholarly communication0.0040.004
Open science0.0000.002
Research integrity0.0010.002
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 head0.069
GPT teacher head0.378
Teacher spread0.309 · 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

Citations48
Published2006
Admission routes1
Has abstractyes

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