Exploring the national scope of outdoor nature-based early learning programs in Canada: Findings from a large-scale survey study
Bibliographic record
Abstract
Across Canada, early learning nature-based programs are gaining popularity with many new programs being implemented each year. Currently, little is known about the number, type, pedagogies, and curricula content of Canadian outdoor and nature-based early learning programs. Thus, this mixed methods study was conducted to explore this growing movement. In total, two hundred educators, representing 165 various programs across Canada completed an online survey. Fifty-one percent of the participants reported having a diploma in Early Childhood Education or similar qualification. In addition, it was estimated that between 40 000 to 60 000 Canadian children, mostly aged between 3 to 9 years, had taken part in these programs during 2018-2019. Moreover, findings suggested that weather conditions can impact the time spent outdoors and that emergent, child-centered curricula rooted in play were guiding the pedagogy of a large percentage of the represented programs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".