An exploration of Indigenous cultural safety within cancer care strategies in Canada
Bibliographic record
Abstract
Cultural safety is a vital continuum needed in biomedical healthcare to address historical and systemic inequities faced by First Nations, Inuit, and Métis Peoples in Canada. Cultural safety seeks to create environments where people receiving care feel welcomed and respected, free from discrimination and cultural misunderstandings. This continuum is crucial for improving Indigenous health outcomes and building trust between healthcare providers and Indigenous communities. This research investigated how different regions in Canada, framed implementing cultural safety in healthcare environments by asking: How are provincial and territorial cancer care strategies proposing culturally safe care for Indigenous Peoples within healthcare facilities? Drawing on a qualitative approach, a thematic analysis is utilized, examining four provincial and one territorial cancer care strategy. Through a thematic analysis, key themes emerged related to culturally safe care principles, practices, and physical space design. The findings highlight the varying degrees of integration of Indigenous cultural safety principles across regions, with some strategies demonstrating comprehensive approaches to the key themes, while others show limited responses. This research underscores the importance of incorporating Indigenous voices, health perspectives, and Traditional Healing Practices into the development and implementation of cancer care strategies to ensure high-quality care for Indigenous individuals, families, and communities. Recommendations for researchers and policymakers include promoting culturally safe physical spaces and features for these populations.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.034 | 0.013 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".