Sur les conséquences du brevet d’invention dans la science : résultats d’une enquête auprès des inventeurs académiques français
Bibliographic record
Abstract
Cet article s’intéresse aux conséquences du brevet d’invention dans la science. Une enquête par questionnaire menée auprès de 280 inventeurs académiques français conduit à de nouveaux résultats concernant l’impact du brevet sur la diffusion des connaissances académiques et le transfert de technologie universités-entreprises. En particulier, notre travail suggère que si, dans certains secteurs, breveter les inventions académiques favorise leur transfert vers l’industrie (surtout dans la pharmacie et les sciences de la vie), cela engendre aussi un retard quasiment systématique de la publication des recherches académiques et est susceptible d’affecter l’agenda de la recherche scientifique (en incitant les chercheurs à s’orienter vers des domaines où les recherches sont brevetables).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.009 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".