Integrating equity and social justice for indigenous peoples in undergraduate health professions education in Canada: a framework from a critical review of literature
Bibliographic record
Abstract
Understanding how to create structural change by actively counteracting racialized ways of interacting with Indigenous peoples at an individual and organizational level within health care systems and health professions education is essential for creating a more inclusive, equitable, and healthier society. In health professions education, the primary means of teaching about health inequities has been to frame them as stemming from culturally or ethnically based issues. While attention to culturally specific practices can be valuable to health and healing in some contexts, education that solely focuses on Indigenous cultures risks perpetuating cultural stereotypes and othering, rather than focusing on how Eurocentric systems continue to exert oppressive effects on Indigenous peoples. We present an organizational transformation framework grounded in equitable partnerships from a comprehensive critical review of the literature on the integration of equity and social justice in undergraduate health professions education with a focus on Indigenous health. We did a thematic analysis of the results and discussions presented in the 26 selected articles to identify promising practices and challenges associated with the integration of equity and social justice in undergraduate health professions education. The framework resulting from this analysis is composed of three interrelated components: 1) adopt critical pedagogical approaches that promote Indigenous epistemologies; 2) partner with Indigenous students, educators and communities; 3) engage educators in critical pedagogical approaches and health equity issues. This framework could guide the development of contextually tailored interventions that contribute to decolonizing health professions education.
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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 | 0.043 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.013 | 0.021 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".