Variegated racism: exploring experiences of anti-Black racism and their progression in medical education
Bibliographic record
Abstract
BACKGROUND: Addressing anti-Black racism in medical education in Canada has become increasingly urgent as more Black learners enter medical institutions and bring attention to the racist harms they face. We sought to gather evidence of experiences of racism among Black medical learners and to explore the contexts within which racism is experienced by learners. METHODS: Drawing on critical race and structural violence theories, we conducted interviews with Black medical faculty, students, residents, and staff at the University of Saskatchewan College of Medicine between May and July 2022. We thematically analyzed interviews using instrumental case study methodology. RESULTS: Thematic analyses from 13 interviews revealed 5 central themes describing experiences of racism and the compounding nature of racist exposures as learners progressed in medicine. Medical learners experienced racism through uncomfortable encounters and microaggressions. Blatant acts of racism were instances where patients and superiors harmed students in various ways, including through use of the N-word by a superior in 1 instance. Learners also experienced curricular racism through the absence of the Black body in the curriculum and the undue pathologizing of Blackness. Medical hierarchies reinforced anti-Black racism by undermining accountability and protecting powerful perpetrators. Finally, Black women medical learners identified intersecting oppressions and misogynoir that compounded their experience of racism. We propose that experiences of racism may worsen as learners progress in medicine in part because of increases in the sources of and exposure to racism. INTERPRETATION: Anti-Black racism in medical education in Canada is experienced subtly through microaggressions or blatantly from different sources including medical faculty. As Black learners progress in medicine, anti-Black racism may become worse because of the compounding effects of exposures to a wider range of sources of racist behaviour.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.006 |
| 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".