Improving the response to intimate partner violence experienced by First Nations people in the primary care setting: provider perspectives on Manitoulin Island
Bibliographic record
Abstract
Indigenous women and men living in Canada experience disproportionately high rates of intimate partner violence (IPV) compared to non-Indigenous women and men, which is best explained within a colonial context. Despite the wide range of adverse physical, sexual and psychological outcomes of IPV, a coordinated approach to the phenomenon has yet to be established in the healthcare and social services system on Manitoulin Island, a region in Northeast Ontario. This project was aimed to address that gap at the primary care level through community based participatory research. Using a Grounded Theory and qualitative research approach, primary care providers (n=31) participated in focus groups and interviews to discuss their perceptions of what is required to improve the response to IPV in the primary care setting. The analysis focused on elucidating the barriers and facilitators that exist within current practices, those of which prevent or ease the delivery of care to First Nation patients who are experiencing IPV. Suggestions for culturally relevant improvements at a health care provision and community level are discussed. Further studies should include knowledge translation back into the communities on Manitoulin Island as well as the perspectives of the survivors of intimate partner violence and their perception of what can be improved within current provider practices.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".