Applied Ethics as Implemented by Ethics Committees in Europe and Canada (the Case of Transgenic Crops)
Bibliographic record
Abstract
Nous examinons comment certains comités d'éthique en Europe et au Canada élaborent leurs avis sur la question très controversée des cultures transgéniques. Nous nous interrogeons sur la pertinence de diverses critiques formulées envers ces comités, mais aussi sur la manière dont ils fonctionnent et dont l'on y pratique l'éthique appliquée. Les critiques se trouvent confirmées au moins en partie et pour quelques uns d'entre eux. Néanmoins, certains fournissent aussi des apports originaux, susceptibles d'éclairer le débat public concernant les plantes transgéniques. L'analyse des insuffisances des uns et des propositions originales des autres nous conduit à élaborer une typologie critique des arguments mobilisés. De là, nous dégageons des éléments de méthodologie pour l'évaluation éthique des plantes transgéniques. Notre analyse tend finalement à remettre en cause l'unique recours à de tels comités et à se demander si un autre type de fonctionnement complémentaire serait envisageable.
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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 | 0.014 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".