Local Indigenous ways of knowing and learning in the classroom through Community-engaged learning
Bibliographic record
Abstract
This paper reflects on the impact of community-engaged learning (CEL) in post-secondary education, as guided by local Indigenous community members, specifically members of the Anishinaabeg Nation and more specifically Mississauga peoples. This CEL way of educating highlights a fundamental difference between Indigenous axiology, where localized relationships and community contributions are paradigm, with traditional Euro-Western hegemonic pedagogies. Within this framework, we hope to contribute to the larger discourse in revising the axiological foundation applied to knowledge within the Academy, based on authentic expressions of an Indigenous way of knowing and learning. We seek to recapitulate the ways that knowledge in the field of anthropology (and post-secondary education in general) is valued and assessed through the first-hand experiences of two cis male Anishinaabe academics, and one cis female Japanese Canadian academic, involved in the development and delivery of community-engaged learning on Turtle Island.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.016 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.017 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".