Outcomes of antiracist pedagogy in health professions education: a scoping review
Bibliographic record
Abstract
In health professions education, there is a call to rethink pedagogical practices and institutions that often perpetuate racism, colonialism, and other systems of oppression. Researchers have stressed the importance of integrating critical pedagogies, such as antiracist pedagogy, to help learners understand societal and structural factors behind health inequities and recognize power dynamics in health science and healthcare. Various antiracist pedagogical interventions have been designed, but their outcomes remain unclear. Based on Levac et al.'s framework, a scoping review was conducted to map the literature evaluating the outcomes of antiracist pedagogy in health professions education. A systematic database search was conducted between April and June 2022 for articles describing evaluation methods and outcomes of antiracist pedagogical interventions in health professions education. We included 41 articles in the final selection. The data was organized within the following themes: aim of intervention, type of intervention, evaluation tools, outcomes and indicators for each of Kirkpatrick's levels of training evaluation, theoretical frameworks, and authors' positionalities. The thematic analysis revealed that, in most cases, evaluations targeted participants' attitudes on systemic racism, their racial identity and critical awareness, as well as their satisfaction with the activities. The antiracist pedagogical interventions were rarely evaluated beyond learners' perceptions. Discrepancies were also raised between the principles of antiracist education and the use of antiracist pedagogy to design, implement and evaluate the outcomes of antiracist pedagogical interventions in health professions education. Although only a few interventions had transformative outcomes beyond individuals, we identified promising pedagogical strategies to foster engagement and motivation to transform professional practices.
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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 | 0.031 | 0.125 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.021 | 0.022 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 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".