Women and gambling-related harm: a narrative literature review and implications for research, policy, and practice
Bibliographic record
Abstract
BACKGROUND: While the prevalence of women's participation in gambling is steadily increasing, there is a well-recognised male bias in gambling research and policy. Few papers have sought to synthesise the literature relating to women and gambling-related harm and provide practical suggestions to guide future research, policy, and practice which take into account the specific nuances associated with women's gambling. METHODS: A narrative literature review was conducted to review the evidence base on women's gambling behaviours and experiences of harm. Drawing from strategies used effectively in other areas of public health, key elements for a gendered approach to harm prevention were identified and adapted into practical public health research, policy and practice strategies. RESULTS: Results indicated a lack of research that explores women's gambling. Few studies have examined the impact of gambling on the lives of women, with limited understanding of the factors that influence women's engagement with gambling products, and the impact of industry tactics. A gendered approach was identified as a strategy used successfully in other areas of public health to shift the focus onto women and to ensure they are considered in research. In tobacco control, increasing trends in women's smoking behaviour were combatted with targeted research, policy and practical initiatives. These key elements were adapted to create a conceptual framework for reducing and preventing gambling harm in women. The framework provides regulatory direction and a research agenda to minimise gambling-related harm for women both in Australia and internationally. Evidence-based policies should be implemented to focus on the influence of gender and associated factors to address gambling-related harm. Practical interventions must take into account how women conceptualise and respond to gambling risk in order to develop specific harm prevention programs which respond to their needs. CONCLUSION: A gendered approach to gambling harm prevention shifts the focus onto the unique factors associated with women's gambling and specific ways to prevent harm. As seen in other areas of public health, such a framework enables harm measures, policies, and interventions to be developed that are salient to girls and women's lives, experiences and circumstances.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 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".