First Peoples, Indigeneity, and Teaching Indigenous Writing in Canada
Bibliographic record
Abstract
We begin with a land acknowledgment because of our responsibility to locate ourselves. We signal our relationship with the people on whose land we live as guests. Acknowledging this relationship is the foundation of decolonial practice in classrooms and universities sitting on Indigenous land. Most people’s experience, family, and education in Canada has contributed to their “epistemic ignorance” about Indigenous worldviews. Those educated in universities are situated as experts; Indigenous people as objects of knowledge. Our recognition of ourselves as guests entails a responsibility to learn from the traditional owners of the land with critical humility. In Canada, university literary study began in the 1890s with British literature; Canadian literature was admitted only in the 1970s, a change propelled by nationalism and an origin myth of an “empty wilderness.” When Indigenous literature began to be taught in the 1990s, it was added to the existing framework. Now after the Indian Residential School Truth and Reconciliation Commission report (2015), the desire for a speedy reconciliation risks leaving that frame intact. Indigenous pedagogies, land-based and urban, are proposed as a way of rethinking how we teach literature and Indigenous literatures.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.045 | 0.017 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".