Integrating Diverse Ways of Knowing and Challenging Epistemic Injustice: An Example of Emancipatory Curricula in Canadian Nursing Education
Bibliographic record
Abstract
Purpose Colonial frameworks remain embedded within nursing education, mandating a critical and ethical response to the Truth and Reconciliation Commission's Calls to Action to integrate diverse knowledge systems into curricula and pedagogical practices. This paper aims to provide settler educators with a structured framework to decolonize educational practices and fostering culturally safe and reciprocal learning environments. Methods This framework integrates decolonial approaches from scholars and collectives, adapting them to local Indigenous contexts and institutional initiatives. The framework's five-phase process — (1) Grounding, (2) Interrogation, (3) New Learning, (4) Commitment, and (5) Rebuilding— was used to guide the critical examination and transformation of curriculum and pedagogy. Major Findings: Called to deepen their colonial consciousness, the authors engaged in learning and unlearning through intentional relationships with local Indigenous communities, being gifted knowledges from Elders and Indigenous scholars. The authors critically reflected on how nursing is taught and evaluated, focusing thier transformative change on their Health in a Global Context and Enacting Social Justice nursing courses. This process revealed the epistemic injustice and pervasive white-centring embedded in course design, assessments, and pedagogical approaches. Engaging in the decolonizing framework led to course redesign that prioritizes diverse ways of knowing in content, assessment, and pedagogy. Conclusion This study highlights how engaging in a minor reform, can become a catalyst for broader decolonization efforts, but true transformation requires sustained commitment, critical self-reflection, and institutional accountability. Decolonizing nursing education is a collective responsibility, that involves dismantling colonial frameworks and actively prioritizing Indigenous knowledges within nursing pedagogy and practice.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.053 | 0.040 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".