Éthique et risques dans la réglementation des biotechnologies : La prise en compte des questions normatives dans les processus d’homologation contemporains
Bibliographic record
Abstract
Résumé Les régimes qui réglementent l’introduction des biotechnologies sur un territoire donné reposent sur le processus d’homologation—un processus décisionnel qui vise à identifier, évaluer, et minimiser les risques associés à l’introduction d’un produit ou d’une substance. Les processus d’homologation comprennent un examen des risques qui est présenté comme étant neutre, empirique et strictement scientifique. Malgré cela, plusieurs jugements de valeur surviendront au moment de cet examen en raison des « questions normatives » qui y surgissent immanquablement. En revanche, une analyse des dispositions provenant de divers régimes canadiens, américains, et européens démontre que ceux-ci abordent et même résolvent certaines questions normatives. Ce faisant, ils mettent en valeur le rôle actuel et potentiel des règles législatives, réglementaires, et administratives pour arbitrer le contenu scientifique et éthique des processus d’homologation.
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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 | 0.021 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.041 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".