Commentary – Advancing Nursing in Canada: Toward the Elimination of Anti-Black Racism
Bibliographic record
Abstract
This commentary challenges historic and contemporary issues within nursing and provides direction toward a more inclusive future for nursing. This is a call-to-action for nurses, nursing students and nurse allies to advance effort toward the elimination of anti-Black racism in nursing in Canada. To achieve this, it is imperative to move beyond the performative and adopt practices that enable critical reflection and action. Addressing the manner in which exclusion is reinforced and perpetuated requires interrogation of four distinct yet interconnected processes of racial exclusion and discrimination. Notwithstanding, the future of nursing requires a critical examination of the role of nursing in and relationship with oppressive institutions, including prisons. Abolition, regarded as a radical stance, argues that beyond disproportional incarceration rates, prisons exist within a system of punishment that inflicts long-lasting irreparable mental and physical trauma upon individuals, families and communities. The effects of incarceration on mental, physical and spiritual health is a healthcare crisis that is in direct opposition to the core tenets of nursing and health.
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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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.038 | 0.034 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".