Etuaptmumk (Two-Eyed Seeing) in <i>Nature’s Way-Our Way</i> : braiding physical literacy and risky play through Indigenous games, activities, cultural connections, and traditional teachings
Bibliographic record
Abstract
Growing philosophical and empirical evidence shows that physical literacy and risky play enriches movement opportunities, while also fostering increased physical activity, wholistic health, and wellness across the lifespan. However, physical literacy and risky play have typically been theorized and practiced from a western worldview. In response, Nature’s Way-Our Way is an initiative designed to ground physical literacy and risky play in Indigenous games, activities, cultural connections, and traditional teachings, as enacted in Early Childhood Education Centres across Saskatchewan, Canada. This article explores Nature’s Way-Our Way’s theoretical underpinnings of Etuaptmumk (Two-Eyed Seeing), adopted to braid together the strengths of Indigenous Knowledges with western knowledge through practices of Indigenous métissage (land and story-based approaches to curriculum informed by relationality). Providing examples of culturally rooted resources, this article shows how the Nature’ s Way-Our Way initiative supports Indigenous self-determination and sovereignty to foster increased physical activity, wholistic health, and wellness across the lifespan.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".