An overview of prevalence surveys of problem and pathological gambling in the Nordic countries
Bibliographic record
Abstract
Estimates of the prevalence of gambling problems among adults by sampling from whole population registries have been made in Finland, Iceland, Norway, and Sweden. The studies in Norway and Sweden are fairly similar, showing a higher prevalence in Sweden according to the South Oaks Gambling Screen Revised (SOGS-R), and similar prevalence according to the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) screens. The difference is unexpected because Norway has relatively more gambling machines and Norwegian citizens spend more money on gambling. However, the low response rates in Norway may explain the result. Preliminary results from Iceland (2005) with a DSM-IV screen do not differ from those from Norway and Sweden concerning prevalences of pathological gambling, but differ from Norway concerning problem gamblers. However, different DSM-IV screens were used in the three countries, and response rates differed. With these reservations, the past-year prevalence of pathological gambling in Iceland, Norway, and Sweden is about 0.3%, as estimated from DSM-IV screens. Studies of gambling problems among young people have only been performed in Norway.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".