Indigenous Service Provider Perspectives of an Online Education Module to Support Safe Clinical Encounters about Family Violence in Canada
Bibliographic record
Abstract
Given colonial genocide, Indigenous peoples are rightfully reticent to disclose their experiences of family violence to practitioners working within mainstream health care and social services. Health care and social service providers (HSSPs) have varied formal education on providing trauma-and-violence informed care to Indigenous and non-Indigenous families affected by family violence, including intimate partner violence and child maltreatment. The purpose of this study is to understand and describe the perspectives of Six Nations of the Grand River community members on the relevance of an education module to support HSSPs to provide physically and emotionally safe care to Indigenous families affected by family violence. Two-Eyed Seeing and Two Row Wampum approaches guided our qualitative study. Twenty-one (66.7% women) Indigenous HSSPs completed a semi-structured interview; 15 identified as a regulated HSSP, nine as a Knowledge Keeper/Cultural Holder, and three as a HSSP trainees. Conventional content analysis guided the development of codes and categories. The Violence, Evidence, Guidance, Action (VEGA)-Creating Safety education module was described as having elements consistent with Indigenous experiences and values, and supportive of Indigenous peoples seeking care from HSSPs for family violence related concerns. Participants described several suggestions to better adapt and align the module content with the diversity of values and beliefs of different Indigenous Nations. Collectively, the Creating Safety module may be used as an educational adjunct to Indigenous-focused, cultural safety training that can support HSSPs to provide physically, emotionally, and psychologically safe care to Indigenous peoples who have experienced family violence. Future work needs to consider the perspectives of other Indigenous communities and Nations.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".