Impact of Availability on Gambling: A Longitudinal Study
Bibliographic record
Abstract
OBJECTIVE: Legalized gambling opportunities have markedly increased in most industrialized countries. While most authors agree that the rate of pathological gamblers is related to the accessibility of gambling activities, no published studies have yet empirically estimated the impact of the introduction of new gambling activities within a longitudinal study. Thus, we evaluate the impact of the opening of a casino on gambling activities among nearby inhabitants. METHOD: A random sample of 457 respondents from the Hull area (experimental group) and 423 respondents from the Quebec City area (control group) completed the South Oaks Gambling Screen and related questions, both before the opening of the Casino de Hull and 1 year later. Within each household contacted, a resident was randomly chosen by selecting the adult whose birthday was next. RESULTS: The experimental group exposed to the new casino showed a significant increase in 1) gambling on casino games, 2) the maximum amount of money lost in 1 day on gambling, 3) reluctance toward the opening of a local casino, and 4) the number of participants who reported knowing a person who has developed a gambling problem in the last 12 months. CONCLUSION: The impact of legalized gambling is discussed in relation to the availability of gambling.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".