Lorsque les démarches d’exploration nécessitent de l’innovation collective
Bibliographic record
Abstract
L’objectif de cette contribution est d’analyser les rôles que peuvent jouer les communautés de pratique dans des démarches d’exploration nécessitant de l’innovation collective. L’analyse se fonde sur une étude longitudinale de 16 mois. Les résultats montrent que des communautés de pratique dédiées à des méthodes d’exploration peuvent jouer un rôle majeur dans l’ouverture des processus d’innovation d’une organisation. Dépassant les fonctions d’un intermédiaire d’innovation, ces collectifs autonomes accompagnent cette dynamique en sensibilisant et en légitimant l’importance d’explorer certains enjeux d’innovation avec des partenaires, en structurant et en animant des démarches d’innovation collective, tout en interprétant et documentant les apprentissages et les résultats liés à ces initiatives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".