Challenging anti-racism in nursing education: A moral and professional call to action
Bibliographic record
Abstract
The call to implement anti-racism pedagogy in nursing education and practice is reverberating globally. Racist ideologies are foundational to systems of health inequity. An antiracist approach is critical to dismantling systemic racism and promoting optimal health outcomes in the quest for health equity. Therefore, employing an anti-racist pedagogy within nursing education that allows students and teachers to reflect on their roles in dismantling racist structures and transforming equity outcomes in practice and society, is a moral undertaking. However, for nursing education to make significant inroads in health equity, it cannot be guided by the same Eurocentric motives and value systems that continue to shape health inequities. We must transcend the boundaries of Eurocentric knowledge construction to intentionally shift how nurses think and practice within systems of inequities. Alongside the pressing and growing call for radical transformation of students and teachers through anti-racist pedagogy, we also provide directions to teaching strategies that support the uptake of anti-racism in nursing curricula and classroom engagement.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".