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Record W2887671802 · doi:10.4000/books.irhis.1968

Twenty years after': were the big French industrial enterprises still following American patterns in the mid-1970s?

2002· book-chapter· en· W2887671802 on OpenAlexaff
Pierre Lanthier

Bibliographic record

VenuePublications de l’Institut de recherches historiques du Septentrion eBooks · 2002
Typebook-chapter
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Qu’est devenue l’américanisation de l’industrie française vingt ans après l’épisode des missions de productivité dans les années 1950? La France des affaires connaissait bien les théories et les méthodes de gestion qui prévalaient aux ÉtatsUnis. Mais les appliquait-elle? L’étude des 20 premiers groupes français en 1976 permet de constater, outre l’amélioration considérable des conditions du marché, une importante vague de concentration industrielle, ainsi que l’adoption de la direction générale au sein du holding, avec des divisions opérationnelles et des divisions fonctionnelles. À travers cette formule, le management à l’américaine s’est introduit durablement dans la grande entreprise française.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.239
Threshold uncertainty score0.476

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.003
Scholarly communication0.0050.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.117
GPT teacher head0.292
Teacher spread0.175 · 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 designObservational
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
Published2002
Admission routes1
Has abstractyes

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