Culturally Safe Health Initiatives for Indigenous Peoples in Canada: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Cultural safety has the potential to improve the health disparities between Indigenous and non-Indigenous Canadians, yet practical applications of the concept are lacking in the literature. PURPOSE: This study aims to identify the key components of culturally safe health initiatives for the Indigenous population of Canada to refine its application in health-care settings. METHODS: We conducted a scoping review of the literature pertaining to culturally safe health promotion programs, initiatives, services, or care for the Indigenous population in Canada. Our initial search yielded 501 publications, but after full review of 44 publications, 30 were included in the review. After charting the data, we used thematic analysis to identify themes in the data. RESULTS: We identified six themes: collaboration/partnerships, power sharing, address the broader context of the patient's life, safe environment, organizational and individual level self-reflection, and training for health-care providers. CONCLUSION: While it is important to recognize that the provision of culturally safe initiatives depend on the specific interaction between the health-care provider and the patient, having a common understanding of the components of cultural safety, such as those that we identified through this research, will help in the transition of cultural safety from theory into practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.015 | 0.021 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 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".