Assessing governance without government: A proposal for the International Council of Sport Governance
Bibliographic record
Abstract
Over the past half-century global sport governance has, in the face of hyper-commercialisation and globalisation, been found wanting. Key institutions have lurched between scandal and outright failure to address their remit and duty to employees, fans and, perhaps most importantly, participants the world over. Critical sport scholars have investigated and demanded better, yet by and large, these demands have not been met, in part, as we argue, because there has been no solution proffered, beyond principled frameworks. In the spirit of critical proactivism, and drawing from international relations praxis and Critical Theory, the following paper seeks to catalyse discussion around a potential solution. We seek to promote and further elucidate the philosophy of and justification for the establishment of an overarching, morally sustainable, and democratically accountable regulatory and enforcement apparatus for sports’ global governance: namely the ‘International Council for Sports Governance’ (ICSG) as a much-needed credibility inoculation for global sport.
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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 | 0.097 | 0.098 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.012 | 0.083 |
| Scholarly communication | 0.041 | 0.041 |
| Open science | 0.007 | 0.023 |
| Research integrity | 0.069 | 0.045 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".