Who Gets To Do Medicine: Black Canadian Studies and Medical Education
Bibliographic record
Abstract
Black studies both addresses the epistemic dilemma Eurocentrism makes of Blackness while also understanding Blackness as relational, situating Black activism and intellectual life as intricately connected. Yet discussions of Black studies have generally been excluded from the fields of science and medicine. In this article, I focus on three considerations of Black studies in these fields: Dalhousie University’s rotating senior research chair in Black Studies, which moved into the Faculty of Medicine in 2019; a reflection on the 1968 Sir George Williams Affair, which highlighted the harms anti-Black racism in science studies has upon Black students and communities; and lastly, an examination of who gets to do medicine in Canada. In the almost two-hundred-year history of medical education in Canada, systemic barriers remain in place that obstruct Black people from participating in medical training. I seek to explore how Black studies in medical education is more than an accounting of brutality and atrocities. Science and medical studies also include Black experiences through method, thought, and intervention, thus creating anew.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.067 | 0.036 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".