Anti‐Black racism: Gaining insight into the experiences of Black nurses in Canada
Bibliographic record
Abstract
The call to address anti-Black racism in workplaces resonates across several organizations and institutions in Canada. But specifically, the coronavirus disease 2019 pandemic shed further light on how health inequities negatively impact the Black community. After conducting a literature review of the experiences of Black nurses in Canada, a deeper understanding of their plight was gained. In healthcare, the findings from the Black Nurses' Task Force report conclude that anti-Black racist practices are pervasive in nursing, and there remains a paucity of research in this area. This study builds off the report by exploring how Black nurses experience anti-Black racism while working in Canada's healthcare system. Inspired by critical race theory and Black feminist thought, an exploratory qualitative research study was conducted, using semistructured interviews to gather data. The study concludes that Black nurses experience anti-Black racism within the workplace, and it manifests itself through some of the attitudes of colleagues, patients, and nurses in leadership roles. Despite policies and statements that were in place to protect them, anti-Black racism continues to occur systematically. The findings point to the need for change in the overall workplace culture, which includes a fair representation of Black nurses in leadership roles, further research to identify best practices for tackling anti-Black racism within Canada's healthcare system, and mandatory training on anti-Black racism for healthcare leaders, educators, and service providers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".