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Quand l’accident survient… Le sauvetage-secourisme du travail, un instrument de gestion des risques au travail ? (1947-1969)

2018· article· fr· W3022555052 on OpenAlexaff
Charles-Antoine Wanecq

Bibliographic record

VenueHistoire Politique · 2018
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsASTER
Fundersnot available
KeywordsAccident (philosophy)Risk managementBusinessOperations managementPsychologyForensic engineeringEngineeringFinancePhilosophyEpistemology

Abstract

fetched live from OpenAlex

Cet article se consacre au développement du secourisme au sein des dispositifs de gestion des risques au travail de la fin des années 1940 au tournant des années 1970. Alors que la prévention donne lieu à une réflexion dense, portée notamment en France par l’Institut national de sécurité, l’enseignement des gestes de premiers secours, relativement marginal, demeure aux mains des associations de secourisme. La Sécurité sociale comme les employeurs ont pourtant un intérêt financier et humain à réduire les risques engendrés par l’accident lui-même. L’article cherche donc à analyser le rôle du monde associatif dans l’élaboration de l’État social à travers l’exemple peu connu du sauvetage-secourisme du travail.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.998
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.028
GPT teacher head0.210
Teacher spread0.182 · 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.

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
Published2018
Admission routes1
Has abstractyes

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