A Historical Overview of Legalized Sports Gambling in Canada
Bibliographic record
Abstract
Although gambling on sporting events has been a practice since ancient times, government-regulated single-event sports betting is a relatively new phenomenon in Canada. While strictly prohibited and generally considered unthinkable in earlier times, gambling in professional sports is omnipresent today (e.g., sponsorships, broadcasts), and it generates vast sources of revenue for teams, their respective leagues and provincial and federal governments through taxation revenues. The authors of this paper do not advocate for legalized sport gambling in Canada, but more accurately endeavour to explore the seismic shift and historic growth of legalized sports gambling in the country. In addition to chronicling the economic benefits that the practice has brought to the sports industry, the gambling establishments, and the federal and provincial governments, the authors document the negative elements associated with legalized sports gambling (e.g., addictions, financial hardships, and mental and physical health impacts). Regardless of one’s opinion on the appropriateness of legalized sports gambling in Canada, the practice appears to be deeply embedded in society and is destined to continue. Keywords: sports gambling, Canada, history, legislation
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".