Barriers to Including Indigenous Content in Canadian Health Professions Curricula
Bibliographic record
Abstract
Indigenous peoples in Canada continue to face health care inequities despite their increased risk for various negative health outcomes. Evidence suggests that health professions students and faculty do not feel their curriculum adequately prepares learners to address these inequities. The aim of this study was to identify barriers that hinder the inclusion of adequate Indigenous content in curricula across health professions programs. Semi-structured interviews were conducted with 33 faculty members at a university in Canada from various health disciplines. Employing thematic analysis, four principal barriers were identified: (1) the limited number and overburdening of Indigenous faculty, (2) the need for non-Indigenous faculty training and capacity, (3) the lack of oversight and direction regarding curricular content and training approaches, and (4) the limited amount of time in curriculum and competing priorities. Addressing these barriers is necessary to prepare learners to provide equitable health care for Indigenous peoples. Keywords: Indigenous health, health professions, curricula, faculty perspectives, barriers, Canada
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| 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".