The KAIROS Blanket Exercise: Engaging Indigenous ways of knowing to foster critical consciousness in medical education
Bibliographic record
Abstract
PURPOSE: Indigenous Peoples across Turtle Island (North America) experience ongoing health disparities tied to the effects of colonization and persistent racism toward Indigenous Peoples. Educating future clinicians to develop a critical consciousness is an important way to work toward cultural safety and improve the health care experiences of Indigenous patients. The present study evaluated the ability of the KAIROS Blanket Exercise (KBE) to foster critical consciousness. METHODS: Two hundred thirteen medical students at the University of Toronto participated in the KBE. Subsequently, 174 students completed a paper evaluation, designed to capture concepts of cultural safety and critical consciousness. Data were analyzed using quantitative and qualitative methods to identify shifts in perspectives. RESULTS: The majority of students reported the exercise altered the way they viewed those from backgrounds different from their own, and comments regarding bias, power and privilege were highlighted throughout the responses. Engaging in critical reflection through dialogue and revealing the complex sociopolitical context of Indigenous Peoples' history were emphasized as central to this transformation. CONCLUSIONS: Following participation in the KBE, medical students demonstrated a shift in their perspectives. This suggests that creating curricular space for critical pedagogy may be effective in fostering critical consciousness, ultimately encouraging reflexive practice and social action.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".