Teaching Indigenous health within an anti-racist, anti-colonial pedagogical framework: using Indigenous resurgence to explore the experiences of medical school instructors
Bibliographic record
Abstract
Anti-Indigenous racism in Canada creates numerous barriers that restrict access to safe, effective, and timely health care for Indigenous people. In the wake of the Truth and Reconciliation Commission of Canada (TRC) and growing reports of anti-Indigenous racism in the health care system, medical schools have been tasked with changing how they prepare students to work with Indigenous communities. Using a critical approach to teaching that seeks to transform systems of colonial-based oppression is relatively new in Canadian medical education, and how medical educators navigate this terrain remains largely unexamined. The central purpose of this qualitative study was to explore and uncover the relational aspects of teaching Indigenous health issues using an anti-racist and anti-colonial approach. Using an emerging framework informed by Indigenous resurgence, the stories of the medical educators were considered in relation to the evolving social discourse concerning Indigenous-settler relations in Canada. Knowledge was gathered using a combination of Kovach’s (2010) conversational method, which is grounded in an Indigenous worldview that aligns with my nêhiyawak identity, and a mobile research approach called guided walks. The gathered knowledge was translated into condensed stories which were further analyzed to identify a set of meta-stories that recovered key lessons and knowledge shared by the educators. In sharing their stories, medical educators situated themselves and their work within the relational dynamics of settler colonial society. While their work was at times met with resistance, the educators found ways to address the challenges that included self-reflective learning and peer mentoring. The entrenched Western ideologies in medicine continue to act as a formidable barrier to transforming medical learners’ perspectives about the lived realities of Indigenous peoples’ ongoing colonial oppression. However, the stories in this study as viewed through the lens of Indigenous resurgence reveal that facilitating discussions that provoke critical dialogue on issues of colonialism can create movement forward in a way that is safe, respectful, and potentially transformative for all concerned. The lessons identified could inform the work currently underway to meet the TRC’s call to implement a mandatory anti-racist Indigenous health course in all Canadian medical schools.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.035 | 0.034 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| 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".