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Record W2758012110 · doi:10.7202/1053576ar

Quel est le rôle du substrat technique dans l’appropriation d’une innovation managériale ? Une analyse longitudinale d’une méthode innovante

2018· article· fr· W2758012110 on OpenAlexvenueno aff
Émilie Canet, Sébastien Tran

Bibliographic record

VenueManagement international · 2018
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

Cette recherche propose une réflexion sur l’appropriation d’une innovation managériale par les acteurs de l’organisation qui la conçoivent. Parce que le substrat technique est l’élément concret qui matérialise l’innovation, nous analysons son rôle dans ce processus. Notre recherche est basée sur l’étude longitudinale du cas d’une innovation managériale au sein d’un grand groupe industriel. Cette recherche permet de montrer que la construction de l’innovation managériale repose sur une interaction forte entre substrat technique et philosophie gestionnaire. L’appropriation est également assurée par la légitimité émergente de nouveaux acteurs promue par les nouvelles relations favorisées par l’innovation.

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)0.028
metaresearch head score (Gemma)0.055
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: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.003
Scholarly communication0.0070.006
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.029
GPT teacher head0.257
Teacher spread0.228 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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