LES MAUX DU DROIT ET LES MOTS DE LA MÉDECINE : ENTRELACS SÉMANTIQUES ET TERMINOLOGIQUES, REFLETS DES DIALOGUES ÉPISTÉMIQUES
Bibliographic record
Abstract
Les termes anciens de la common law tels que remedy et case, les termes modernes de la formation des juristes comme Juris Doctor et « clinique juridique », et certains mouvements de la philosophie du droit tels que la therapeutic jurisprudence suggèrent des convergences entre droit et médecine quand d’autres termes évoquent plutôt des divergences, par exemple la différence entre « patient » et « client ». Cet essai s’appuie sur ces convergences et divergences terminologiques pour ouvrir des pistes d’exploration concernant les dialogues épistémiques entre droit et médecine à diverses époques. En examinant l’histoire des usages des termes, mais aussi les connotations et aspirations qu’ils véhiculent, l’auteur montre comment les mots apparemment innocents du quotidien révèlent des échanges foisonnant d’une discipline à l’autre.
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 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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.037 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 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".