Le géant aux pieds d’argile : de la fragilité des arguments éthiques de la réglementation antidopage
Bibliographic record
Abstract
Le dopage sportif est l’objet d’un combat sans merci de la part des organismes sportifs de tous genres. Le Comité international olympique, par exemple, l’interdit sur la base de trois arguments qui ont pour objectif de « protéger la santé des athlètes, défendre l’éthique médicale et sportive, maintenir l’égalité des chances pour tous dans toutes les compétitions ». Mais ces arguments éthiques, sur lesquels se fonde la réglementation antidopage, résistent-ils à une analyse poussée et sont-ils à la fois nécessaires et suffisants ? Cet article montre que c’est loin d’être le cas et que la réglementation antidopage n’est en fait, sur le plan éthique, qu’un colosse aux pieds d’argile.
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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".