Violence and Health Promotion Among First Nations, Métis, and Inuit Women: A Systematic Review of Qualitative Research
Bibliographic record
Abstract
Indigenous women experience a disproportionate burden of intimate partner violence (IPV) compared to other women in post-colonial countries such as Canada. Intersections between IPV and other forms of structural violence including racism and gender-based discrimination create a dangerous milieu where 'help seeking' may be deterred and poor health outcomes occur. The aim of this review was to explore the perspectives of First Nations, Métis and Inuit (FNMI) women living in Canada about how violence influenced their health and wellbeing. This systematic review of qualitative research used thematic analysis to produce a configurative synthesis. A comprehensive search of electronic databases was conducted. Two reviewers screened studies for relevance and congruence with eligibility criteria. Sixteen studies were included in the review. Four themes with subthemes emerged: 1) ruptured connections between family and home, 2) that emptiness… my spirit being removed, 3) seeking help and being unheard, and 4) a core no one can touch. Together these themes form complex pathways that influenced health among women exposed to violence. Findings from this review highlight the need for collaboration with FNMI women and their communities to prevent IPV and ensure access to trauma and violence informed care (TVIC). The strength and resiliency of FNMI women is fundamental to healing from violence. Working with FNMI women and their communities to build effective interventions and promote culturally meaningful care will be important directions for researchers and policy makers.
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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 | 0.028 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".