“Because you love us as much as we love you”: The role of community relationships in facilitating Indigenous engagement in healthcare
Bibliographic record
Abstract
Grounded in relational worldviews and ways of being, Indigenous health on Turtle Island once thrived. However, colonization disrupted and sought to delegitimize Indigenous relationships, having devastating impacts on Indigenous health and contributing to persistent Indigenous health disparities. Making matters worse, Indigenous Peoples face barriers to engagement in mainstream Canadian healthcare, including racism and the marginalization of Indigenous relational conceptions of health and ways of caring. Using an Indigenous methodology, we explored Kanyen'kehá:ka (Mohawk) relationality between community members and community-based healthcare providers (n = 25), and how these ways of relating shaped engagement in community-based care. Our analysis identified three key themes: in Kenhté:ke (Tyendinaga) the concept of health goes beyond western definition and is broadly defined and relational; connectedness and shared experiences are foundational to Kenhté:ke identity and ways of caring; and relationships that reflect community connection foster more engagement in healthcare than otherwise in western care settings. These findings have critical implications for western norms of healthcare professional training and practice and the need to include Indigenous relational ways of caring and conceptions of health. • Kanyen'kehá:ka conceptions of health are wholistic and relational. • Connection is foundational to Kenhté:ke identity and ways of caring. • In Kenhté:ke, connection facilitates engagement in community-based healthcare. • Community connection also has the potential to facilitate engagement in self-care.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.015 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".