Interpersonal, institutional, and structural racism in Canadian nursing: A culture of silence
Bibliographic record
Abstract
BACKGROUND: Alongside declarations against racism, the nursing profession in Canada needs examination of experiences of racism within its ranks. Racism at multiple levels can create a context wherein racialized nurses experience barriers and ongoing marginalization. PURPOSE: This critical interpretive qualitative study asks how interpersonal, institutional, and structural racisms intersect in the professional experiences of racialized nurses in Canada, and how nurses respond. METHODS: Self-identified racialized nurses (n = 13) from across Canada were recruited primarily through snowball sampling, and each was interviewed by phone or in person. Once transcribed, interviews were analyzed inductively, which led to the levels of racism as a guiding framework. RESULTS: From entry to nursing education throughout their careers participants experienced racism from instructors, patients, colleagues and managers. Interpersonal racism included comments and actions from patients, but more significantly lack of support from colleagues and managers, and sometimes overt exclusion. Institutional racism included extra scrutiny, heavier workloads, and absence in leadership roles. Structural racism included prevalent assumptions of incompetence, which were countered through extra work, invisibility and hyper-visibility, and expectations of assimilation. Racialized nurses were left to choose among silence, resisting (often at personal cost), assimilation and/or bolstering their credibility through education or extra work. Building community was a key survival strategy. CONCLUSIONS: Everyone in nursing needs to challenge the culture of silence regarding racism. White nurses in particular need to welcome discomfort, listen and learn about racism, then speak out to help disrupt its normative status.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".