‘Making the pros pay’ for amateur sports: the Ontario Athletic Commission, 1920–1947<sup>†</sup>
Bibliographic record
Abstract
The capitalist sports-media complex is heavily subsidized in many countries. Teams, leagues and their corporate partners enjoy state-donated land and stadia, favourable tax rates, legislative and judicial relief from antitrust requirements, the player and fan development systems of state-supported playgrounds, schools, colleges and universities, and the legitimation of public ceremonies. They claim these benefits on the basis of the economic spin-offs they generate and the ‘branding’ of cities and regions they headline. But in an earlier political tradition these expectations were reversed. Both sports entrepreneurs and professional athletes were expected to contribute financially to the development of amateur and community sport, on the grounds that it is these programmes that train the players and educate the fans on which capitalist sport depends. One such example was the tax on professional sport levied during the interwar years by the Ontario Athletic Commission (OAC), the subject of this paper. The OAC was the very first state sports body in Canada, and in many ways it set the mould for the state-directed and state-financed programmes of the federal and provincial governments today, although the tax on professional sports no longer exists. The paper was written in 1994, while I was still a member of the board of the publicly owned Stadium Corporation of Ontario, which operated Toronto's SkyDome.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".