Transformation and Re-Creation: Creating Spaces for Indigenous Theorising in Canadian Aboriginal Studies Programs
Bibliographic record
Abstract
Abstract This paper explores the professional experience of an Anishnabe educator working in various organisations teaching Indigenous knowledge issues in both Aboriginal and primarily non-Aboriginal settings. The reflections span a number of years of teaching Aboriginal worldview and knowledge issues courses and include formal evaluations from both Aboriginal and non-Aboriginal students who have participated in the courses over that time. This paper draws upon two examples of educational institutions where Indigenous knowledge is being explored: the University of Toronto’s Aboriginal Studies Program and the Centre for Indigenous Environmental Resources’ (CIER) National First Nations Youth Environmental Education and Training Program. Both settings represent special places for thinking about decolonising Indigenous education. Integral to Aboriginal philosophy and decolonising education is the role elders play in informing and implementing meaningful education for Aboriginal learners. Both programs involve elders in central roles where they are recognised as authorities, facilitators and teachers. Discussion is offered on the subject of Aboriginal philosophies pertaining to education and some models for acting upon them, particularly as they relate to environmental education. Further analysis summarises the challenges faced by both programs and initiatives taken to advance Aboriginal educational goals. Finally, recommendations are made as to the types of changes which may be undertaken to realise creative spaces for resistance and creativity.
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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 | 0.017 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.053 | 0.039 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".