The Proportion of Gaming Revenue Derived from Problem Gamblers: Examining the Issues in a Canadian Context
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
The legitimacy of government‐sponsored gambling and its continued expansion depends in part on the impact that gambling has on society and the extent to which gambling revenue is derived from vulnerable individuals. The purpose of the present article is to try to establish a valid estimate of the proportion of gaming revenue derived from problem gamblers in Canada. Using recent secondary data collected in eight Canadian provinces, we estimate this proportion to be 23.1%, compared to a problem gambling prevalence rate of 4.2%. This estimate must be seen as tentative, however, as self‐reported expenditures are 2.1 times higher than actual provincial gaming revenues.
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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) | 0.000 | 0.000 |
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