Women’s experiences of alcohol-related severe intimate partner violence: Findings from formative research in South Africa
Bibliographic record
Abstract
Abstract Introduction: Gender-based violence (GBV) is a threat to the health and well-being of women globally, and a key barrier to the achievement of the Sustainable Development Goals 3.3 and 5.2. Harmful alcohol use is a recognised risk factor for the perpetration and experience of GBV, particularly, intimate partner violence, and for the severity of intimate partner violence. This paper seeks to explore the role of alcohol in women’s experience of severe intimate partner violence (SIPV) in South Africa. Methods: We conducted a qualitative study, using six focus group discussions and 20 in-depth interviews with 62 demographically diverse adult women from three provinces in South Africa (Gauteng, KwaZulu-Natal, and the Western Cape) who sought help for SIPV. Findings: Women reported alcohol-related SIPV, frequently describing that her partner intentionally started arguments after he had been drinking. Their abuse included controlling and coercive behavior that restricted their movement and ability to participate in daily activities, economic abuse, and instances of severe physical and sexual intimate partner violence and attempted femicide. They viewed men's alcohol use as a ‘right’ associated with masculinity, that often intersected with expressions of masculinity, including controlling behavior, dominance, and aggression, and performing a provider role, especially among friends in taverns and bars. Conclusions: Planning for effective prevention, providing services and policy efforts requires an understanding of the complexity of the interaction between men's alcohol abuse and their perpetration of SIPV particularly in a context like South Africa, where both harmful alcohol use and GBV are prevalent.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".