Moving Pedagogy Outside: Reading a Graduate English Course with the Concepts of Fort Pedagogy, Indigenous Métissage, and the wâhkôhtowin Imagination
Bibliographic record
Abstract
Where do we learn? What are our experiences of relationships in those contexts? Could teaching a course outside activate the wâhkôhtowin imagination? Can walking begin to repair relationships? Donald suggests that it can; and yet, another of the concepts Donald discusses, that of fort pedagogy, cautions us to listen and not claim. Is it possible for me, a White descendent of European immigrants, to learn from the wâhkôhtowin imagination without re-enacting fort pedagogy? In this article, I examine possibilities for anti-colonial pedagogy as I reflect on a student’s learning experiences—my own—from my dual positionality as PhD student and English literature instructor. Thinking alongside Indigenous Métissage (Donald, 2009, 2012), fort pedagogy (Donald, 2009), and the wâhkôhtowin imagination (Donald, 2021), I examine my experiences in an innovative graduate English course taught largely outside and consider ways pedagogy can shift relationships to place and to one another.
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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 | 0.003 | 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 | 0.013 | 0.014 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".