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Record W6903392569 · doi:10.11575/prism/48072

Indigenous Health in Postgraduate Medical Education: Pathways for Enhancing Anti-racism Literacy and Praxis for Advanced Trainees

2025· other· en· W6903392569 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPraxisRacismIndigenousHealth equityExperiential learningEquity (law)Health careCommissionExperiential knowledge

Abstract

fetched live from OpenAlex

Racism is detrimental to health; it widens gaps in health inequities by marginalizing specific populations and sustaining structures that perpetuate harm. This results in social fragmentation that hampers the capacity of affected communities to achieve well-being. Racial hierarchies tend to characterize aspirations for equity as unachievable, using the complexity of the need to shift institutions, attitudes, and whole cultures to undermine expectations that equity be a core component and not simply an added benefit of a just society. This doctoral thesis aims to mitigate the impact of racism on health disparities experienced by Indigenous peoples in Canada by addressing unequal treatment in health systems through the advanced training of healthcare professionals, specifically medical residents across specialties. It is aligned with the Truth and Reconciliation Commission of Canada’s (TRC) Call to Action #24, which emphasizes the expansion of “skills-based training in intercultural competency, conflict resolution, human rights, and anti-racism” for all health professionals in Canada. Decolonial and anti-racist education are promising pathways explored here for advancing healthcare equity, as they place historical, political, and social experiences at the centre of the learning process and objectives. These pedagogies promote the active involvement of learners, an approach that would seem to suit advanced medical trainees whose programs usually involve practice-based experiential learning mentored by established physicians. Such training also offers the possibility for adult learning approaches known to favour behaviour change, such as critical self-reflection over time. However, medical residency and fellowship training often involve limited exposure to the lived realities of Indigenous patients and, in turn, limited direct feedback or guidance from these. This complicates possibilities for integrating historical, political, and social components of Indigenous-focused anti-racism. This thesis presents a largely qualitative body of work that approaches these dilemmas in three parts. It begins by eliciting guidance from semi-structured interviews conducted in one Canadian province with Indigenous individuals who have accumulated experiences in health systems and health professional training (n=12). It then draws on a document analysis of formal Indigenous training in post-graduate medical education (PGME) across Canada. Finally, it returns to perspectives on health professional learning among advanced medical trainees through semi-structured interviews with non-Indigenous residency preceptors (n=19) and residents (n=14) across specialties. These sources offer insight into Indigenous guidance for PGME training in Indigenous health and anti-racism in Canada, current approaches across medical schools, and needs and possibilities for growing Indigenous-focused anti-racism learning from mentors and mentees within PGME programs. This work emphasizes that addressing anti-Indigenous racism in healthcare is essential for achieving Indigenous health equity. Integrating insights from 45 interviews and the scanning of 1179 curricular documents related to PGME with a close review of 46 containing any form of Indigenous content, this work offers a preliminary index of specialty-specific Indigenous health and anti-racism content as a potential starting point for more refined curricular development. An important implication of this work is greater clarity around how training may incorporate unique dilemmas faced in distinct medical fields and the cultural, social, and geopolitical diversity of Indigenous peoples in Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0140.004
Scholarly communication0.0090.006
Open science0.0020.020
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0250.003

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.

Opus teacher head0.023
GPT teacher head0.378
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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