Moving Beyond Ignorance and Epistemic Violence: Indigenous Health Nurses' Response to Systems Transformation
Bibliographic record
Abstract
Health inequity among Indigenous populations continues to widen despite advances in Indigenous health research. Under Canada's esteemed universal healthcare system, Indigenous populations continue to experience much poorer health outcomes due to the intersectional legacies of colonialism and racism. In this commentary, we reflect on structural, systemic and service delivery racism at all levels of care, which are deeply embedded in historical, political, institutional and socioeconomic policies and practices that continue to perpetuate harm and genocide of Indigenous Peoples. We call for immediate action to re-establishing epistemic justice and reframing Indigenous knowledge systems in nursing practices, policies, research and education as the starting point in counteracting systemic racism.
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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 | 0.045 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.077 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.005 | 0.018 |
| Research integrity | 0.017 | 0.033 |
| 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".