De/colonization: perspectives on/by indigenous populations in global Canadian contexts
Bibliographic record
Abstract
This article offers systematic review of literature on the educational colonization of Indigenous populations within global Canadian contexts. Questions guiding this study were, ‘What colonizing dynamics exist in education for Canadian aboriginal populations, and what decolonizing dynamics suggest progress or advancement?’ Across disciplines, sources were located with perspectives on decolonizing education for aboriginal populations, in addition to policy reforms and effects on aboriginal learning. Using a document analysis approach, 85 articles and reports identifying colonizing and decolonizing dynamics were analyzed. Four overarching themes revealing de/colonizing dynamics within Canada emerged: colonizing through testing cultures; building Indigenous education system-wide; unsettling colonial teaching and learning; and unpacking discourse central to decolonization. What Canadian Indigenous literature imparts about colonization and the future is socially, politically, and educationally important. Tribal justice – an enduring problem of humanity – is a collective and global responsibility for which interventions are needed. Social, political, and educational recommendations from the literature are advanced for building up a glocal perspective that enriches the contribution of this work to the wider literature.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.015 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".