Bibliographic record
Abstract
Indigenous women and birthing parents in Canada disproportionately face mistreatment in their maternal healthcare experiences due to systemic anti-Indigenous racism, ongoing harmful impacts of settler colonialism, and power differentials inherent in many healthcare relationships. Indigenous midwives and doulas are important leaders in resisting these conditions and reclaiming traditional Indigenous birth knowledge and practices. Ultimately, they work to uphold Indigenous self-determination and sovereignty. Grounded in an understanding of historical and current challenges regarding Indigenous maternal health, this qualitative study explored how best to situate oneself as a settler researcher and maternal health practitioner to support Indigenous maternal health in a culturally safe, anti-racist manner. In this article, key insights are shared from semi-structured interviews conducted with five prominent Indigenous scholars, midwives and community leaders. These consultants emphasized the central importance of intentional relationships in advancing the reclamation of traditional birth practices and providing culturally safe care, along with the indispensability of Indigenous midwives and doulas in these processes. Consultants also stressed the critical need for increased numbers of, and accessibility to, Indigenous practitioners in communities across the country. Settler practitioners are urged to understand the historical and contemporary impacts of settler colonialism, and the significance of building culturally safe, anti-racist relationships with their Indigenous colleagues and clients.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.247 | 0.063 |
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".