Mapping the role of structural and interpersonal violence in the lives of women: implications for public health interventions and policy
Bibliographic record
Abstract
BACKGROUND: Research on interpersonal violence towards women has commonly focused on individual or proximate-level determinants associated with violent acts ignores the roles of larger structural systems that shape interpersonal violence. Though this research has contributed to an understanding of the prevalence and consequences of violence towards women, it ignores how patterns of violence are connected to social systems and social institutions. METHODS: In this paper, we discuss the findings from a scoping review that examined: 1) how structural and symbolic violence contributes to interpersonal violence against women; and 2) the relationships between the social determinants of health and interpersonal violence against women. We used concept mapping to identify what was reported on the relationships among individual-level characteristics and population-level influence on gender-based violence against women and the consequences for women's health. Institutional ethics review was not required for this scoping review since there was no involvement or contact with human subjects. RESULTS: The different forms of violence-symbolic, structural and interpersonal-are not mutually exclusive, rather they relate to one another as they manifest in the lives of women. Structural violence is marked by deeply unequal access to the determinants of health (e.g., housing, good quality health care, and unemployment), which then create conditions where interpersonal violence can happen and which shape gendered forms of violence for women in vulnerable social positions. Our web of causation illustrates how structural factors can have negative impacts on the social determinants of health and increases the risk for interpersonal violence among women. CONCLUSION: Public health policy responses to violence against women should move beyond individual-level approaches to violence, to consider how structural and interpersonal level violence and power relations shape the 'lived experiences' of violence for women.
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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 | 0.039 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.013 | 0.023 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".