Joindre un réseau pour devenir un meilleur intrapreneur : les enseignements du Club de Montréal
Bibliographic record
Abstract
Résumé Le réseau professionnel peut constituer un outil efficace de développement personnel et de gestion des compétences des intrapreneurs, lesquels sont souvent des héros dissidents dans l’organisation. C’est ce que nous montre l’histoire du Club de Montréal, une communauté informelle créée dans les années 1990 et réunissant quelques directeurs de grands projets de différents secteurs d’activité de l’industrie française. Ce réseau a non seulement conforté ses membres dans leurs comportements autonomes au moment de la mise en place des projets, mais les a aussi encouragés à adopter des conduites déviantes ou peu conformistes. Cet article examine comment l’appartenance à un réseau professionnel ou d’affaires, qui peut parfois devenir une communauté de pratique, est en mesure de favoriser le déploiement de pratiques intrapreneuriales au sein des organisations.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".