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Record W1712242069 · doi:10.4000/pistes.2311

Réflexions critiques sur le maintien en emploi de travailleurs vieillissants faiblement qualifiés : responsabilité sociale ou individuelle ?

2009· article· fr· W1712242069 on OpenAlexvenueno aff
Thibauld Moulaert, Florence Laigle, Achille N’Guessi, Claude Mahau

Bibliographic record

VenuePerspectives interdisciplinaires sur le travail et la santé · 2009
Typearticle
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Cet article propose une réflexion pluridisciplinaire (médecins du travail et sociologue) sur la nécessité de prolonger les carrières à partir du cas limite de travailleurs faiblement qualifiés de deux entreprises : une entreprise de ramassage de déchets (Cleanbel) et une entreprise de distribution alimentaire (Distribel). Croisant réalité pratique et ergonomie d’un côté et enjeu de responsabilité et réflexion sociologique de l’autre, il montre les limites d’un questionnement sur l’emploi des salariés vieillissants quand est occulté le travail analysé au départ de l’activité réelle. En explorant le cas de travailleurs faiblement qualifiés, il montre aussi les marges de manœuvre étroites d’une action sociale possible ou voulue qui pose in fine la question de la responsabilité de cette action : est-elle collective (portée par l’Etat et l’entreprise) ou individuelle (portée par le travailleur) ?

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)0.018
metaresearch head score (Gemma)0.020
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: none
Teacher disagreement score0.020
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0090.047
Scholarly communication0.0130.012
Open science0.0030.010
Research integrity0.0070.008
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 head0.032
GPT teacher head0.410
Teacher spread0.378 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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