Impacting attitudes towards gambling: A prison gambling awareness and prevention program
Bibliographic record
Abstract
Research indicates that approximately one third of prison inmates meet the criteria for problem or pathological gambling (Williams, Royston, & Hagen, 2005). However, despite this rate being among the highest of all gambling populations (Walters, 1997; Shaffer & Hall, 2001), there appears to be a lack of prison gambling awareness and prevention programs. This study sought to develop, implement, and evaluate one such program at the Lethbridge Correctional Facility in Alberta, Canada. Forty-nine inmates completed a six-session program over 18 months. Gambling screen results revealed a significant increase in cognitive error recognition, and attitudes towards gambling became significantly more negative. The program did not render any significant differences in math skill score, Canadian Problem Gambling Index (CPGI) score, or past-year South Oaks Gambling Screen (SOGS) score. Changes in the past-year frequency score approached significance. This study suggests that programs of this kind can be effective for inmate populations, particularly in changing attitudes towards gambling.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".