THE MAIN APPROACHES TO THE LEGAL REGULATION OF GENDER VERIFICATION IN SPORT: A COMPARATIVE ANALYSIS
Bibliographic record
Abstract
Genetically determined differences in height, musculature and a number of other physiological parameters lead to a significant advantage for men over female in kind of sports where the key indicators depend on strength, speed and endurance. All above suggest the need to maintain the practice of holding separate competitions for different genders. However, the practical solution to this issue seems not that obvious, taking into consideration persons with an indeterminate gender identity and transgender person. Analysis of the current legislation of a significant number of States has allowed to identify some approaches:1) ignoring not only the problem of participation in sports activities of persons with an indeterminate gender identity and transgender person, but also the issue of their special legal status in general (Greece, Israel, Ireland, Cyprus, Latvia, etc.); 2) recognizing gender diversity and solving the problems of persons with an indeterminate gender identity and transgender personfrom the position of general provisions of non-discrimination legislation without defining the specifics of sports activities (Belgium, France, Germany, Hungary); 3) recognition of gender diversity but with strive to limit the opportunities for transgender personfor participation in sports in order to ensure fair competition (Brazil); 4) recognition of gender diversity with consequent regulation of sports participation of persons with an indeterminate gender identity and transgender person(Australia, great Britain, Canada, USA). Demonstrating the last example two patterns can be revealed: a possibility of developing different, sometimes diametrically opposite approaches to solving this problem due to the Federal structure of States, and the active involvement of national sports federations in this process
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".