Revenue Sharing in Professional Sports Leagues
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This entry provides a review of economic models of professional sports leagues with and without revenue sharing. These include models that assume profit-maximizing and win-maximizing (sportsmen) club owners. Both approaches predict that revenue sharing will reduce the demand for player talent, depress player salaries, and transfer revenue from large-market to small-market clubs, but they differ on league parity effects. Empirical work has been sparse due to financial data limitations and has not yielded definitive results on the parity issue. Despite the growing awareness of sports economics in the sports industry, the lack of consensus from theoretical models has resulted in sports leagues searching for an optimal revenue sharing policy. The difficulty in providing consistent policy prescriptions in models that incorporate revenue sharing, salary caps, and other league policies has made economic modeling of sports leagues very difficult and complex. While revenue sharing remains an interesting theoretical modeling issue, it has not bridged the gap to real-world league policies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it