Pro-Alcohol-Use Social Environment and Alcohol Use among Female Sex Workers in China: Beyond the Effects of Serving Alcohol
Bibliographic record
Abstract
The current study was designed to fill the literature gap by examining the roles of the pro-alcohol social environment in alcohol use among female sex workers (FSWs) in China. In this study, a total of 1,022 FSWs were recruited through community outreach from both alcohol-serving and nonalcohol-serving commercial sex venues in Guangxi, China. The pro-alcohol social environment was measured in four areas: institutional norms, institutional practices, risk perceptions and peer norms. The measures of the pro-alcohol social environment were significantly associated with the venues' alcohol-serving practices, with FSWs from those venues reporting a more positive pro-alcohol social environment than their counterparts from nonalcohol-serving venues. However, these pro-alcohol social environment measures were independently predictive of alcohol use after controlling for venues' alcoholserving practices and other demographic characteristics. Public health interventions need to target environmental-structural factors through altering pro-alcohol-use social norms and practices at both institutional and individual levels among FSWs in China.
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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 | 0.001 | 0.001 |
| 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".