Decolonizing pedagogical approaches to aboriginal literatures in Canada
Bibliographic record
Abstract
This thesis focuses on socially responsible strategies for teaching Aboriginal literatures in Canadian schools, particularly within Secondary level English courses. It articulates the need for a theorized methodology for reading as the basis of this pedagogical project, and argues that, within the context of colonial Canada, this methodology must be a decolonizing one. It outlines the fundamental components of a decolonizing methodology for reading, based on the following imperatives: rooting understanding in Aboriginality; valuing Aboriginal perspectives; challenging Eurocentrism and colonialism; maintaining a sense of reader responsibility; and challenging multiple forms of oppression. This project demonstrates a decolonizing methodology by examining Aboriginal texts by Beatrice Culleton Mosionier, Tomson Highway, Lee Maracle, and Chrystos. These examinations address such issues as colonial schooling in Canada, Aboriginal languages and their importance to Aboriginal cultures, and the possibilities offered by anti-colonialism feminism. Throughout, it raises considerations for educators pursuing an anti-colonial pedagogy through Aboriginal texts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.051 | 0.044 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".