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Record W2935769522 · doi:10.3166/rfg.2019.00293

La recherche-action dans le domaine du <i>supply chain management</i>

2018· article· fr· W2935769522 on OpenAlexaff
Martin Beaulieu, Claudia Rebolledo, Jacques Roy, Sylvain Landry

Bibliographic record

VenueRevue française de gestion · 2018
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophySociology

Abstract

fetched live from OpenAlex

La recherche-action (RA) est une méthodologie centrée sur une proximité avec le milieu professionnel afin de développer des connaissances qui permettront de résoudre des problèmes pratiques pour les gestionnaires. Cette stratégie de recherche est une réponse aux critiques de certains voulant que la recherche en supply chain management s’éloigne des besoins de connaissances des entreprises. À partir de trois expériences en supply chain du secteur de la santé, cet article formule des observations à l’attention des chercheurs afin de mieux comprendre les conditions facilitant la recherche-action en supply chain management.

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)0.070
metaresearch head score (Gemma)0.065
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 score0.070
Threshold uncertainty score0.370

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0700.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.006
Science and technology studies0.0060.040
Scholarly communication0.0230.018
Open science0.0040.010
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0080.002

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 head0.076
GPT teacher head0.276
Teacher spread0.200 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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