Is Decolonization the Answer to Indigenous Under-achievement? Comparing Rhetoric with Reality in New Zealand and Canada
Bibliographic record
Abstract
The paper compares the rhetoric of decolonization put forth by indigenous scholars with the reality of educational outcomes in New Zealand and Canada and discusses the implications of two common themes emerging from the discourse: (1) cultural determinism in which both First Nations and Maori scholars fundamentally but narrowly depict education as a means to conserve language and cultural heritage -- which results, intentionally or unintentionally, in (2) a hardening of racial/ethnic boundaries. The paper critiques the appropriateness of both themes in the context of the widely accepted notion that indigenous peoples in both countries need to attain higher levels of educational attainment and improve educational performance in order to compete in a knowledge-based, global economy. L'article compare la rhétorique de décolonisation avancée par les érudits autochtones avec la réalité des résultats de l'enseignement en Nouvelle-Zélande et au Canada et discute la portée des deux thèmes communs qui émergent des discours: (1) un déterminisme culturel dans lequel les érudits des Premières Nations et du peuple Maori représentent l'éducation de façon fondamentale mais étroite, comme le moyen de préserver l'héritage linguistique et culturel -- dont les résultats volontaires ou involontaires, amènent à (2) un durcissement des frontières raciales ou ethniques. L'article critique la justesse des deux thèmes dans le contexte de la notion généralement acceptée que les peuples autochtones dans ces deux pays ont besoin d'atteindre un niveau d'éducation plus élevé et d'améliorer leurs accomplissements académiques pour pouvoir compéter dans une économie globale et basée sur la connaissance.
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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 | 0.018 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.035 | 0.075 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 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".