Les dynamiques de construction des règles de transferts de technologies université – industrie
Bibliographic record
Abstract
Les transferts de technologies font l’objet d’une évolution normative récente qui incite fortement les chercheurs universitaires et leurs équipes à s’inscrire dans des processus de commercialisation de leurs découvertes et développements. À partir de l’analyse d’une entreprise spin-off qui s’est développée au milieu des années 1980 dans le plus ancien parc scientifique européen, nous formulons l’hypothèse que cette norme, aujourd’hui dominante dans les universités, ne s’est imposée localement que dans le cadre de relations conflictuelles entre des chercheurs pionniers, qui ont agi aux frontières de leur institution, et leurs directions. L’institutionnalisation de cette norme, tant dans la sphère universitaire, qu’industrielle et publique, ne peut être comprise qu’à travers l’action transformatrice de ces chercheurs et de leurs capacités d’innovation.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".