Anti-Black Racism in Healthcare: Could critical race theory prove helpful in the Canadian context?
Bibliographic record
Abstract
Anti-Black racism persists in various Canadian areas, including healthcare. The legacy of white dominance from the period of colonization and slavery has spawned an afterlife of anti-Black racism, which has significantly contributed to shortcomings in Canadian healthcare equity. The underfunding of research specifically examining the experiences of Black communities in healthcare has resulted in a lack of evidence in the available literature and has further contributed to barriers to advocacy for addressing health disparities within these communities. In this commentary, we briefly discuss the history of anti-Black racism in Canada and how it continues to manifest in Canadian healthcare. We suggest that engaging critical race theory in the Canadian racial healthcare equity literature may provide a more nuanced analysis of the root causes of racial health disparities in Canada’s Black communities and is essential for developing effective strategies that address systemic and structural anti-Black racism in the Canadian healthcare environment.
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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 | 0.016 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.032 | 0.054 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 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".