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Record W2146098866 · doi:10.7202/1007976ar

Mise en concurrence des fournisseurs ou partenariat ?

2012· article· fr· W2146098866 on OpenAlexvenueno aff
Hervé Fenneteau

Bibliographic record

VenueRevue internationale P M E Économie et gestion de la petite et moyenne entreprise · 2012
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesConcurrencePolitical scienceGeographyPhilosophyPhysics

Abstract

fetched live from OpenAlex

Les entreprises qui désirent exercer une influence sur leurs sources d’approvisionnement peuvent adopter deux politiques distinctes : mettre continuellement les fournisseurs en concurrence ou bien proposer une coopération durable à certains d’entre eux. Cet article s’attache à définir les termes de ce choix. La logique de chacun de ces deux comportements y est d’abord analysée. Nous montrons ensuite comment l’étude des besoins qui sous-tendent l’achat et l’examen du marché amont permettent d’opter en faveur de l’une de ces deux politiques. La situation propre aux entreprises de petite taille est prise en compte à chacune des étapes de l’analyse.

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)0.020
metaresearch head score (Gemma)0.050
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 score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.050
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0090.011
Scholarly communication0.0160.011
Open science0.0020.009
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0180.003

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 head0.034
GPT teacher head0.267
Teacher spread0.233 · 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

Citations13
Published2012
Admission routes1
Has abstractyes

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Same venueRevue internationale P M E Économie et gestion de la petite et moyenne entrepriseSame topicBusiness Strategy and InnovationFrench-language works237,207