Bibliographic record
Abstract
Sheila Cote-Meek and Taima Moeke-Pickering's book, Decolonizing and Indigenizing Education in Canada highlights the damaging impact of colonialism on current practices in education, and seeks to right the wrongs of colonist education practices by incorporating Indigenous histories, knowledges and pedagogies into present day curriculum.By highlighting the history and impact of colonialism on preserving inequities, this book speaks to a critical issue of discriminatory practices deeply entrenched in the education system.This 316-page edited volume, consisting of 15 chapters, written by 32 contributors, is organized thematically in two parts.Part one (Chapters 1-6) addresses Indigenous epistemologies: exploring the place of Indigenous knowledges in post-secondary curriculum, including Indigenization of the curriculum and pedagogy.Part two (Chapters 7-15) focuses on decolonizing post-secondary institutions: building space in the Academy for Indigenous peoples, resistance, and reconciliation.Chapter 1 provides an articulation of Indigenous epistemologies by rooting it in language, culture, community and land.Given the centrality of land to sustaining and nourishing Indigenous societies, this chapter provides strategies for implementing landbased education.Chapter 2 illustrates Anishinaabe culture, the intimate relationship with the land and Indigenous knowledges being grounded in the lands (p.28).This chapter also illuminates the eradication of authority of Indigenous women, and makes clear that Canadian laws, through the Indian Act, have led to the gender imbalance of contemporary Anishinaabe societies.Such "governance structures were complicit in the marginalization of Indigenous women and the knowledges that enabled their society's survival" (p.27).
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".