Embracing risk in the Canadian woodlands: Four children’s risky play and risk-taking experiences in a Canadian Forest Kindergarten
Bibliographic record
Abstract
Children are born with an intrinsic drive and natural curiosity to explore the world around them. Just as young children are attracted to the natural world, they too are enticed by the physical challenges and risk-taking experiences that such environments provide. Based on research conducted at one of Canada’s first Forest Kindergartens and using Sandseter’s conceptualization of risk, this article aims to explore the safe risk-taking and risky play experiences of four children at a nature-based early years programme in rural Ontario. Not only does this research add to the growing body of empirical evidence surrounding risk and nature-based learning in the early years but also provides a unique Canadian perspective not often discussed in the literature. An incidental outcome of this work is exposing researchers and practitioners to the types of safe risk-taking and risky play experiences that may occur within an early years Canadian context.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.030 | 0.009 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".