ral ssBioMed CentBMC Public Health Open AcceResearch article Alcohol, tobacco and illicit drug use amongst same-sex attracted women: results from the Western Australian Lesbian and Bisexual Women's Health and Well-Being Survey
Bibliographic record
Abstract
Background: The prevalence of alcohol, tobacco and illicit drug use has been reported to be higher amongst lesbian and bisexual women (LBW) than their heterosexual counterparts. However, few studies have been conducted with this population in Australia and rates that have been reported vary considerably. Methods: A self-completed questionnaire exploring a range of health issues was administered to 917 women aged 15-65 years (median 34 years) living in Western Australia, who identified as lesbian or bisexual, or reported having sex with another woman. Participants were recruited from a range of settings, including Perth Pride Festival events (67.0%, n = 615), online (13.2%, n = 121), at gay bars and nightclubs (12.9%, n = 118), and through community groups (6.9%, n = 63). Results were compared against available state and national surveillance data. Results: LBW reported consuming alcohol more frequently and in greater quantities than women in the general population. A quarter of LBW (25.7%, n = 236) exceeded national alcohol guidelines by consuming more than four standard drinks on a single occasion, once a week or more. However, only 6.8 % (n = 62) described themselves as a heavy drinker, suggesting that exceeding national alcohol guidelines may be a normalised behaviour amongst LBW. Of the 876 women who provided data on tobacco use, 28.1 % (n =
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.018 | 0.004 |
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".