Mieux comprendre la gestion de l’innovation : le cas d’un centre de liaison et de transfert en sciences sociales au Québec
Bibliographic record
Abstract
Les recherches sur les partenariats entreprise-université reposent souvent sur l’étude de cas exemplaires aux États-Unis en haute technologie. Il apparaît intéressant d’investiguer ces relations de coopération dans des contextes différents de celui des Etats-Unis. Dans les petits pays, l’innovation implique souvent que la coopération entre des acteurs multiples est nécessaire pour que soient appropriées et mobilisées les connaissances scientifiques dans le champ économique. Dans cet article, nous examinerons comment a été organisée et géré, par un centre de liaison et de transfert québécois, un projet de recherche impliquant des acteurs de plusieurs milieux. L’examen des leçons tirées de l’expérience d’un centre de liaison et de transfert montre que les partenariats peuvent appuyer le changement social, mais que la recherche en collaboration nécessite l’instauration de nouveaux outils et dispositifs institutionnels.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".