Gambling and Related Mental Disorders: A Public Health Analysis
Bibliographic record
Abstract
This article reviews the prevalence of gambling and related mental disorders from a public health perspective. It traces the expansion of gambling in North America and the psychological, economic, and social consequences for the public's health, and then considers both the costs and benefits of gambling and the history of gambling prevalence research. A public health approach is applied to understanding the epidemiology of gambling-related problems. International prevalence rates are provided and the prevalence of mental disorders that often are comorbid with gambling problems is reviewed. Analysis includes an examination of groups vulnerable to gambling-related disorders and the methodological and conceptual matters that might influence epidemiological research and prevalence rates related to gambling. The major public health problems associated with gambling are considered and recommendations made for public health policy, practice, and research. The enduring value of a public health perspective is that it applies different 'lenses' for understanding gambling behaviour, analysing its benefits and costs, as well as identifying strategies for action. Harvey A. Skinner (160, p. 286)
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".