Sober Curiosity: A Qualitative Study Exploring Women’s Preparedness to Reduce Alcohol by Social Class
Bibliographic record
Abstract
BACKGROUND: Urgent action is required to identify socially acceptable alcohol reduction options for heavy-drinking midlife Australian women. This study represents innovation in public health research to explore how current trends in popular wellness culture toward 'sober curiosity' (i.e., an interest in what reducing alcohol consumption would or could be like) and normalising non-drinking could increase women's preparedness to reduce alcohol consumption. METHODS: Qualitative interviews were undertaken with 27 midlife Australian women (aged 45-64) living in Adelaide, Melbourne and Sydney in different social class groups (working, middle and affluent-class) to explore their perceptions of sober curiosity. RESULTS: Women were unequally distributed across social-classes and accordingly the social-class analysis considered proportionally the volume of data at particular codes. Regardless, social-class patterns in women's preparedness to reduce alcohol consumption were generated through data analysis. Affluent women's preparedness to reduce alcohol consumption stemmed from a desire for self-regulation and to retain control; middle-class women's preparedness to reduce alcohol was part of performing civility and respectability and working-class women's preparedness to reduce alcohol was highly challenging. Options are provided for alcohol reduction targeting the social contexts of consumption (the things that lead midlife women to feel prepared to reduce drinking) according to levels of disadvantage. CONCLUSION: Our findings reinstate the importance of recognising social class in public health disease prevention; validating that socially determined factors which shape daily living also shape health outcomes and this results in inequities for women in the lowest class positions to reduce alcohol and related risks.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".