Decolonizing the Curriculum: Policy Implications for Indigenous Knowledge Integration in National Education Systems
Bibliographic record
Abstract
This study explores the integration of Indigenous knowledge into national education systems as a central strategy for curriculum decolonization. Focusing on case studies from Canada and New Zealand, the research investigates how policy frameworks and classroom practices intersect to promote or hinder the inclusion of Indigenous epistemologies. Findings reveal that while national policies in both countries emphasize cultural inclusion and reconciliation, actual implementation varies widely across schools. Successful integration depends significantly on community engagement, teacher training, and leadership support. However, systemic challenges such as standardized assessments, insufficient curricular guidance, and minimal Indigenous representation in policymaking continue to limit the depth of curricular transformation. The study highlights the importance of creating dialogic and culturally grounded educational environments to foster equity, identity affirmation, and epistemic justice in multicultural societies.
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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 | 0.019 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".