Why it is Important to Indigenize Outdoor Play Curriculum
Bibliographic record
Abstract
The outdoors and land provide many beneficial aspects that affect an individual's development. The education system in Canada has been taught in a Westernized perspective for a long time now, leaving the Indigenous community to not feel as secure and respected. This research mainly focuses on the Ontario curriculum, and looks at the need for indigenizing outdoor play curriculum in the Primary years of education (Kindergarten - Grade 3). There is a need for Ontario citizens to work together on gaining more knowledge around the land we reside, learn, and play on. In my research I will examine how the Land supports and benefits children’s development and growth. The wholistic approach to learning is embedded in the land and frames Indigenous worldviews. These are learning principles that I value. This wholistic framework of learning and engaging in outdoor pedagogy on the land will guide me through my research. A literature review was done for this research using reliable sources that examine the significance of understanding more about the land and how important it is for our overall health and well-being. This literature review resulted in gaps detected that the Ontario Curriculum does not share about outdoor play in respects to Indigenous people about their history and practices. Overall, more looks into each of the Ontario curriculum documents need to be examined on where Indigenous perspectives on the land are prevalent or missing. Indigenizing outdoor curriculum is necessary in order to build a strong community for all children in education.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".