Barriers in accessing intimate partner violence services: Intersecting views of immigrant and minority ethnic survivors and community organization workers
Bibliographic record
Abstract
BACKGROUND: Intimate partner violence (IPV) can have serious physical and mental health consequences for women. Women from immigrant and/or ethnic minority backgrounds may face additional barriers in accessing support. This research was based in a multicultural and marginalized neighborhood in Montreal (Canada) with a high incidence of IPV. OBJECTIVES: (1) To better understand the needs and challenges of women survivors of IPV who come from immigrant and/or ethnic minority backgrounds, and the barriers they face in seeking help; (2) to understand the perspectives of community organization workers on immigrant and ethnic minority survivors' needs and barriers in accessing services, as well as their knowledge about how to best support survivors. DESIGN: We employed a mixed-methods design using a community-based participatory approach. Bronfenbrenner's socioecological model was used as a theoretical framework to analyze the findings. METHODS: We conducted in-depth individual interviews with 7 female survivors of IPV from immigrant and/or ethnic minority backgrounds and conducted surveys with 23 community organization workers. RESULTS: The study shows a dissonance in views between survivors and workers. The survivors identified barriers to accessing support at each level of Bronfenbrenner's ecosystem, reflecting the complexity of their situations. For example, (1) macro-system: inadequacy of the legal system, racism; (2) exo-system: accessibility of services, poor quality of services, distrust of institutions; (3) micro-system: social and family pressure, poor social integration; (4) onto-system: language barriers, lack of knowledge of resources, feelings of fear and shame. The workers mainly noted barriers at the onto-level, which was primarily linked to gender and immigration status. Only 52% had ever attended a training on IPV. Most of their organizations had no referral protocol nor educational material about services for IPV for clients. CONCLUSION: Community-based organizations that do not specialize in IPV often work with survivors and are therefore an important resource in IPV prevention and survivor care. Training them on IPV, sensitizing them to understand the systemic barriers the survivors experience, and equipping their organizations are key strategies for developing a coordinated, community-based response to IPV.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".