Les grappes industrielles en régions périphériques: le cas des biotechnologies marines à Rimouski (Québec)
Bibliographic record
Abstract
Figurant comme un élément important des politiques de développement économique, les grappes régionales ont été souvent présentées, à tort ou à raison, comme étant l'environnement le mieux adapté pour stimuler l'innovation et la compétitivité des entreprises et des régions. L'objectif de cet article est d'étudier le phénomène des grappes industrielles en région périphérique à partir du cas des biotechnologies marines à Rimouski. Pour ce faire, nous décrivons la structure et le fonctionnement de la grappe et nous analysons comment les dynamiques d'innovation résultent de processus et d'interactions qui se déroulent à différentes échelles spatiales. De plus, nous discutons en quoi le cas des biotechnologies marines à Rimouski illustre la difficulté de faire émerger une grappe dans un contexte périphérique.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".