Pathways to greater government accountability for breaches of their obligations in relation to doping in sport: A legal analysis
Bibliographic record
Abstract
The State doping scandal in Russia has highlighted a major discrepancy in the fight against doping in sport: on the one hand, the signatories of the Word Anti-Doping Code (federations, NADO's, etc.) are subject to a very strict regime and incur serious sanctions, while on the other hand, States, when they massively violate the rules, do not risk very important consequences in international law. For example, high ranking officials as well as the Russian state apparatus have not been affected with a few exceptions such as the Moscow antidoping laboratory. The aim of this opinion paper is to present a reflection on the different avenues that could be envisaged to make governments more accountable, especially as work is underway on the topic. The development of a true government accountability regime would allow the system to be more balanced.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".