kiwētotētan: ininiw kiskinomākēwin a framework for decolonial education
Bibliographic record
Abstract
Pre-contact Indigenous Nations were vibrant with their own legal, government, and education systems. Indigenous education was community-led and grounded in the spiritual, emotional, physical and mental development of the child. Teachings were tied to the land following the natural cycles, and language was passed down through ceremony and time on the land. Following the creation of the Canadian state, Indigenous education systems were eroded, leaving detrimental impacts on communities and youth that are ongoing today. In recent decades, many communities have taken the initiative to restore community-led Indigenous education systems. The work presented here, Ininiw kiskinomākēwin, was collectively built with both Ininiwak and Anishinabe Elders and educators from Northern Manitoba and can be adapted to fit other First Nations groups across Canada. Ininiw kiskinomākēwin conveys the pre-contact methods for ensuring children and youth grow and become healthy, contributing members of society, and includes teachings involving family, community, language, land, and spirit. The implementation of this work is ongoing; critical components related to building a local teacher workforce, engaging Elders, supporting parents and having access to the land will shape how we choose to educate current and future generations.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".