La Géographie des comportements d'innovation au Québec : des territoires « européens » aux accessibilités « canadiennes » ?
Bibliographic record
Abstract
La géographie de l’innovation est souvent abordée par le biais du rapport au territoire. Or, des recherches portant sur le Québec montrent que la propension à innover varie selon la distance aux centres urbains. Cet article propose une discussion, puis une analyse empirique, de la variation géographique des comportements d’innovation des entreprises manufacturières québécoises. Un questionnement sous-jacent à cette analyse concerne la possibilité que certaines idées, concepts ou approches en sciences régionales diffèrent entre le Canada et l’Europe. Les résultats montrent que les comportements d’innovation varient à la fois spatialement (selon l’accessibilité aux interlocuteurs), mais aussi selon le territoire. Seules les collaborations avec des partenaires privés ne reflètent aucun patron géographique. Il en ressort que les concepts utilisés – territoires finis ou distances continues - seraient communs au Canada et à l’Europe, mais que l’orientation des recherches empiriques – et donc les questions posées – seraient influencées par les particularités locales.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".