Perceived challenges of early childhood educators in promoting unstructured outdoor play: an ecological systems perspective
Bibliographic record
Abstract
Unstructured outdoor play has been recognized for its beneficial impacts on children’s healthy development; however, unfortunately, opportunities for children to engage in meaningful play are limited. Early learning and childcare centres can be essential settings for unstructured outdoor play, and educators can play a vital role in supporting children’s opportunities, yet they face numerous barriers. We conducted five focus groups with 40 professionals working in the early childhood education field (educators, students and licensing officers) in British Columbia, Canada, to examine their experiences and perceived challenges in promoting children’s unstructured outdoor play. Participants’ identified challenges were mapped on the ecological system and ranged from microsystem concerns (e.g. knowledge and skills) to mesosystem concerns (e.g. lack of shared understanding with parents and colleagues), exosystem concerns (e.g. licensing regulations) and macrosystem concerns (e.g. societal risk aversion). We recommend evidence-based strategies to address each of the identified barriers, targeting each ecological system level.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".