Gender Differences in Alcohol Use and Risk Drinking in Ontario Ethnic Groups
Bibliographic record
Abstract
This article examines prevalence and gender differences of alcohol use and risk drinking in a representative sample of Ontario adults. Data were drawn from the Centre for Addiction and Mental Health (CAMH) Monitor survey of Ontario adults aged 18 and older collected between January 2005 and December 2010. The prevalence of self-reported lifetime, current, and high-risk drinking were all higher among the Canadian and the European-origin groups compared with other ethnic groups. Within-group gender differences were evident for all ethnic groups. The narrowest gender gap was observed within the North European group and the widest in the South Asian group. The non-European ethnic groups had higher rates of abstinence and lower alcohol consumption rates; nevertheless, a considerable proportion of people from these groups may be at risk of alcohol-related harm due to risky and harmful alcohol consumption patterns. Future research should continue to investigate alcohol use in these groups and identify subgroups at risk and factors that increase or decrease their vulnerability to risky and problem drinking.
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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 | 0.001 |
| 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".