Whose interests? Which solidarity? Challenges of developing a European Super League
Bibliographic record
Abstract
Since the 1990s, rumours of a European Super League (ESL), comprised of the major clubs from England, France, Germany, Italy, and Spain, have mounted. According to these rumours, this new league would break away from the Union of European Football Associations (UEFA). Many clubs would operate outside the current European federative system, abandoning their national leagues and football federations. An ESL thus conceived would present a menacing alternative to the UEFA Champions League (UCL) and, depending on the format of the ESL, national competitions such as leagues and cups. In this article, we draw on literature in the fields of philosophy and sport law to identify legal and ethical challenges that would result from creating an ESL. Our goal is not to provide exhaustive analyses of the identified challenges. Rather, we aim to examine the challenges to uncover intersections among sport law, sport ethics, and European football.
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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 | 0.070 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.033 |
| Scholarly communication | 0.025 | 0.015 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".