Bibliographic record
Abstract
With the ongoing growth of state-sponsored gambling throughout Canada and much of the western world, this study by Vaillancourt and Roy is of more than a passing interest. Following a brief history of gambling, the authors present a comprehensive overview of the level, composition and importance of government gambling revenues in Canada. The compendium of statistical tables drawn from a variety of domestic and international sources is a useful general reference for researchers in the field. http://www.camh.net/egambling/issue4/review/index.html (1 of 5) [6/24/2002 12:17:03 AM] EJGI:Issue 4: Reviews: Gambling & Government in Canada Three themes emerge from the statistical presentation that invite comment. First, the authors focus on government revenue from gambling and do not include non-government gambling activities in their analysis. While this was no doubt in the interest of simplicity, it may understate the true importance of gambling as a funding mechanism for traditional government responsibilities. For example, hospital lotteries have become a staple in many Canadian cities, while community service agencies have often come to depend on the
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| 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".