DRINKING PATTERNS AND PERSPECTIVES ON ALCOHOL POLICY: RESULTS FROM TWO ONTARIO SURVEYS
Bibliographic record
Abstract
AIMS: Previous research has shown that heavier drinkers, in comparison to light drinkers or abstainers, are more likely to favour increased access to alcohol and relaxation of control policies. Often, studies have not examined whether attitudes to alcohol policies vary according to a respondent's pattern of drinking. This study examined the association between drinking variables and views on policy, using six drinking variables and six topics on alcohol policy. METHODS: Data were available from two Ontario surveys conducted in 2000 and 2002, which took representative samples of adults, aged 18 and older, selected by random digit dialling, who participated in interviews over the telephone (n = 1294 and 1206, respectively). Drinking variables include drinking status, drinking frequency, usual number of drinks, typical weekly volume, frequency of 5+ drinks per occasion and Alcohol Use Disorders Identification Test (AUDIT) scores. Six policy items were examined: alcohol taxes, warning labels, density of retail alcohol outlets, privatization of government liquor stores, alcohol advertising and consultation with health experts on decisions on alcohol policy. Logistic regression analyses included five demographic variables: gender, age, marital status, education and income. RESULTS: Among males, there was strong support for increased access to alcohol and fewer controls over alcohol policies. This relationship, although not as strong, also emerged for frequent consumers, high volume drinkers and those with a higher AUDIT score. CONCLUSION: Whether it is intentional or not, government policies that tend to make alcohol more available cater to young, heavy-drinking males who possibly experience problems in connection with their drinking behaviour.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".