ПЕРВЫЕ ЗАКОНОДАТЕЛЬНЫЕ АКТЫ О СПОРТЕ В ЗАРУБЕЖНЫХ ГОСУДАРСТВАХ
Bibliographic record
Abstract
This article provides an overview of the world's first Acts in the sports sphere. The authors studied the experience of Argentina, Brazil, UK, Spain, Italy, Canada, Colombia, Cuba, United States, France, Czech Republic and Chile. Concluded that we have several thousand years of history of self-regulation in sport and several hundred years of history of sports law, while the history of field-specific laws on sports numbers only less than 150 years. It was not until recently that the state has introduced its public policy into the sports sphere, which for thousands of years operated independently of the system of public authority according to its own statutes. Extralegal regulatory control in the sports sphere has its own history, considerably longer-term and increasingly diversified, than the history of sports legislation, adopted by the system of public authority, which began to be adopted relatively recently. We think that a considerable scientific interest lies in the issue of when first Acts on sport were adopted in various countries of the world. Probably, the very first Acts, which could be conventionally mentioned in this context, should be sought for in ancient Greece. Subsequently, there were legislative instruments, issued by Emperor Justinian, who closed the major part of sports organizations. Acts, passed in ancient China and ancient Japan, determined the rules of military training and contests, related therewith.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".