Young women's engagement with gambling: A critical qualitative inquiry of risk conceptualisations and motivations to gamble
Bibliographic record
Abstract
BACKGROUND: Younger women's engagement with gambling has changed over recent decades due to a range of socio-cultural, environmental and commercial factors. However, younger women's distinct lived experiences with gambling have rarely been considered. The following critical qualitative inquiry explored factors that influenced younger women's engagement with gambling and their perceptions of gambling risks. METHODS: Semi-structured interviews were conducted with 41 Australian women aged 18-40 years. Participants were asked questions relating to their reasons for gambling, and the perceived risks associated with gambling. Reflexive thematic analysis was used to interpret the data. RESULTS: Five themes were constructed from the data. First, women reported that they gambled to escape their everyday lives, with some women reporting gambling within their own homes. Second, women reported gambling for financial reasons, particularly to change their life circumstances and outcomes. Third, gambling was used by women as a way to connect with social network members. Fourth, gambling was an incidental activity that was an extension of non-gambling leisure activities. Finally, lower risk perceptions of participants' own gambling risk contributed to their engagement and continuation of gambling. CONCLUSION: Public health and health promotion initiatives should recognise that young women's gambling practices are diverse, and address the full range of socio-cultural, environmental and commercial factors that may influence younger women's engagement with gambling.
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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 | 0.017 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".