Loose parts and risky play: playworker perspectives on facilitating a community-based intervention in local parks during the COVID-19 pandemic
Bibliographic record
Abstract
Play encourages physical and social activity creativity, and risk-taking. However, unstructured and risky play is on the decline. Our qualitative study explored the perspectives of Play Ambassadors, who faciliated a community-based loose parts play intervention (‘play hubs’) in Calgary parks during the COVID-19 pandemic. Using semi-structured interviews with 12 Play Ambassadors, four main topics emerged. Experiences Supporting Unstructured Play reflected how they supported play and their perceptions and observations of the play hubs. Learning to Take Risks in Play reflected how Play Ambassadors’ views on risk and facilitating risky play evolved. Value of the Play Hubs reflected Play Ambassador perspectives on the community and personal impacts of the play hubs. Supporting Play during a Pandemic highlighted the challenges encountered in delivering the play hubs. Our findings suggest that community-based play programs in local parks may be a viable strategy for encouraging play, especially when traditional opportunities are restricted.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".