Seeking “Mamatowisowin” to Create an Engaging Social Policy Class for Aboriginal Students
Bibliographic record
Abstract
This article recounts the author’s personal and professional journey of developing a social policy social work course at the First Nations University of Canada. With no social policy text designed for and about Aboriginal peoples, and very few articles written on social policy issues in Aboriginal communities, the author was challenged to create content, pedagogy, and assignment structures that reflected the cultures of her students who come primarily from the plains and woodlands reserve communities of Saskatchewan. By consulting with Elders, colleagues, and students, as well as by paying attention to her own internal sense of stress or delight, she progressively modified the class over three years, releasing all that was‘dry and detached’ while building on all that was fun, relevant and exciting. Along the way, the author was introduced to the néhiyawéwin (Cree) word mamatowisowin, which refers to a state of spiritual attunement and divine inspiration. I realized that, perhaps more than head knowledge, it was mamatowisowin that she most needed in order to create a class that optimally served her students and the university’s vision of a ‘bicultural education’ that is equally grounded in both European and Indigenous knowledge systems.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| 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".