Iitsim’kaatsita : enhancing relations between Indigenous women and registered nurses : journeying toward transformative reconciliation to foster maternal health equity
Bibliographic record
Abstract
Iitsimákaatsita: Enhancing Relations between Indigenous Women and Registered Nurses was a four-phase, Indigenous-led mixed-methods study that investigated how nursing contributes to and/or mitigates perinatal health inequities experienced by Blackfoot women in southern Alberta. Grounded in Siksikaitsitapi (Blackfoot ways of knowing), Indigenous Research Methodologies (IRM), and guided by Critical Indigenous Feminism (CIF) and Red Intersectionality (RI), this dissertation centers Indigenous women’s voices, knowledge systems, and sovereignty to disrupt colonial framings of health and care. In Phase 1, a culturally specific survey tool was co-developed in partnership with a Blackfoot Advisory Circle to reflect community priorities, relational ethics, and Blackfoot understandings of health and wellbeing. The survey was used to capture Blackfoot women’s perinatal experiences and serve as a foundation for later phases. Phase 2 involved administering the survey with 107 Blackfoot women, whose responses revealed widespread experiences of racism, surveillance, and cultural exclusion in nursing care, alongside expressions of strength, resistance, and the women’s ongoing engagement with Blackfoot perinatal traditions. These findings challenge deficit-based narratives and offer a sovereignty-affirming framework for understanding Indigenous women’s health experiences. Phase 3 engaged 27 perinatal nurses across five focus groups to reflect on the survey findings and explore their roles in reinforcing or disrupting systemic harm. Nurses identified the limitations of cultural competency frameworks and described both institutional constraints and moments of relational care rooted in kinship (understood here not simply as familial ties, but as relational accountability and ethical responsibilities to others), advocacy, and anti-colonial intent. Across community and hospital settings, nurses enacted—and at times resisted—the systemic structures that shape care for Indigenous families. Phase 4 returned findings to Blackfoot communities through knowledge-sharing gatherings to support accountability, relational repair, and community-led action. Overall, the study offers an Indigenous-led, community-engaged model for health research and nursing practice. It demonstrates how equity-oriented, culturally grounded care must be rooted in Indigenous sovereignty and relational responsibility. This dissertation contributes to nursing scholarship and Indigenous Peoples’ health by illuminating pathways to transform perinatal care in ways that uphold the voices, values, and well-being of Indigenous women.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.007 |
| 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".