Prevention of problem gambling: Lessons learned from two Alberta programs
Bibliographic record
Abstract
The development of effective problem gambling prevention programs is in its infancy. The present paper discusses results of randomized control trials of two programs that have been implemented in Alberta, Canada. The first is a 10 session program delivered to several classes of university students taking Introductory Statistics. This program focused primarily on teaching the probabilities associated with gambling and included several hands-on demonstrations of typical casino table games. The second is a 5 session program delivered to high school students at several sites in southern Alberta. This program was more comprehensive, containing information and exercises on the nature of gambling and problem gambling, gambling fallacies, gambling odds, decisionmaking, coping skills, and social problem-solving skills. Data concerning gambling attitudes, gambling fallacies and gambling behaviour at 3 and 6-months postintervention are presented. The findings of these studies are somewhat counter-intuitive and have important implications for the design of effective prevention programs.
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How this classification was reachedexpand
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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".