Applying an Anti-Racist Pedagogy to Develop and Deliver a Racial Microaggressions Workshop for Occupational Therapy Students
Bibliographic record
Abstract
Many workshops about identifying, understanding, and responding to microaggressions have been designed and delivered to learners within health education. However, few workshops implement an anti-racist pedagogical approach, and none presented in the literature have been created specifically for occupational therapy students. Anti-racist pedagogical approaches explicitly link interpersonal and institutional/structural oppressions to ensure that the impacts of microaggressions are not minimized by focusing solely on interpersonal interactions. A specific workshop is needed to address the noted persistence of racial microaggressions directed at clients, families, students, and practitioners within occupational therapy contexts and due to the embeddedness of practitioners in clients’ daily lives. To address the gap in curricular intervention tools, a workshop was designed and implemented. The workshop was delivered to master's professional entry-level occupational therapy students with the goal of raising knowledge of racial microaggressions and confidence to actively respond when microaggressions occur in their classroom, fieldwork, and future practice. This workshop was developed and delivered using an anti-racist pedagogy and a transformative learning approach within the occupational therapy curriculum of a Canadian university. This paper presents the content, process, and pedagogical underpinnings of the workshop and introduces a trauma-informed and strength-based model for responding to microaggressions. When introduced through an anti-racist pedagogy, we demonstrate how a workshop on racial microaggressions provides an opportunity to teach occupational therapy students key tenets of racism and anti-racism as they manifest in and beyond occupational therapy. An anti-racist approach can inform pedagogical planning for microaggression workshops delivered across and beyond health 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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".