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Record W1766135313 · doi:10.7202/1030389ar

Pratiques coopétitives dans l’Open Innovation : Les enseignements des patent pools

2015· article· fr· W1766135313 on OpenAlexvenueno aff
Cécile Ayerbe, Jamal Eddine Azzam

Bibliographic record

VenueManagement international · 2015
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesBusinessPhilosophy

Abstract

fetched live from OpenAlex

Cette recherche propose une relecture de l’Open Innovation sous l’angle de la coopétition. Une telle approche est encore très peu appréhendée dans la littérature existante. Ces logiques de coopétition sont analysées dans le cadre des ‘‘patent pools’’ qui constituent une forme organisée d’innovation ouverte que nous qualifions ‘‘d’ouverture à grande échelle’’, très peu étudiée par la littérature managériale. Nous montrons que les patent pools reposent sur le développement simultané de pratiques collaboratives et compétitives, que ce soit lors de leur constitution ou ensuite de leur fonctionnement et en tirons des enseignements quant à la coopétition dans l’Open 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)0.017
metaresearch head score (Gemma)0.044
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: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0060.012
Scholarly communication0.0160.026
Open science0.0020.009
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0120.002

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 head0.109
GPT teacher head0.291
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.

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

Citations12
Published2015
Admission routes1
Has abstractyes

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