Décider la mort et prélever les organes : la question de l’extension des conditions du prélèvement d’organes
Bibliographic record
Abstract
La référence à la pénurie d’organes est un lieu commun du discours politique et social associé au don. Dans ce contexte se pose la question d’une extension possible des conditions d’inclusion des patients dans le prélèvement d’organes. Nous analyserons ici, au sujet particulier des patients pour lesquels un arrêt des thérapeutiques est décidé, les conséquences morales et sociales ainsi que les dilemmes moraux suscités par une telle extension. Nous montrerons notamment que l’indétermination des normes de référence autorise des pratiques divergentes et moralement contestées au sein des pays occidentaux. Il s’agira également de souligner les formes d’aménagement normatif induites par cette évolution de la pratique médicale.
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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 | 0.037 | 0.063 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.048 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".