Hazardous Alcohol Use in 2 Countries: A Comparison Between Alberta, Canada and Queensland, Australia
Bibliographic record
Abstract
OBJECTIVES: This article aimed to compare alcohol consumption between the populations of Queensland in Australia and Alberta in Canada. Furthermore, the associations between greater alcohol consumption and socio-demographic characteristics were explored in each population. METHODS: Data from 2500 participants of the 2013 Alberta Survey and the 2013 Queensland Social Survey were analyzed. Regression analyses were used to explore the associations between alcohol risk and socio-demographic characteristics. RESULTS: A higher rate of hazardous alcohol use was found in Queenslanders than in Albertans. In both Albertans and Queenslanders, hazardous alcohol use was associated with being between 18 and 24 years of age. Higher income, having no religion, living alone, and being born in Canada were also associated with alcohol risk in Albertans; while in Queenslanders, hazardous alcohol use was also associated with common-law marital status. In addition, hazardous alcohol use was lower among respondents with a non-Catholic or Protestant religious affiliation. CONCLUSIONS: Younger age was associated with greater hazardous alcohol use in both populations. In addition, different socio-demographic factors were associated with hazardous alcohol use in each of the populations studied. Our results allowed us to identify the socio-demographic profiles associated with hazardous alcohol use in Alberta and Queensland. These profiles constitute valuable sources of information for local health authorities and policymakers when designing suitable preventive strategies targeting hazardous alcohol use. Overall, the present study highlights the importance of analyzing the socio-demographic factors associated with alcohol consumption in population-specific contexts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".