An evaluation of the amount, type and use of shade at public playgrounds in Guelph, Ontario, Canada
Bibliographic record
Abstract
INTRODUCTION: The provision of shade at outdoor recreation sites such as playgrounds confers a variety of public health benefits. It can prevent overexposure to solar ultraviolet radiation, and, in turn, protect against skin cancer. Further, shade mitigates heat and may promote physical activity. In this study, we evaluate and describe the amount, type and use of shade at public playgrounds. METHODS: Using a modified shade audit tool, shade audits were conducted to visually evaluate shade coverage at 85 city-operated playgrounds in Guelph, Ontario, Canada, in summer 2019. RESULTS: The main play area of most playgrounds (68%) had no shade available. Although the areas surrounding playgrounds had more shade coverage than the main play areas, we also found minimal shade coverage (> 0% to 30%) in this area for many playgrounds (48%). All shade over main play areas was provided by trees (i.e. natural shade). Permanent, built shade structures were observed in the surrounding area of 13% of playgrounds. Shade coverage in the areas surrounding playgrounds was positively correlated with the number of individuals (rs = 0.259; p = 0.017), children (rs = 0.270; p = 0.012), and active individuals (rs = 0.253; p = 0.020) using the surrounding area. This suggests that individuals seek shade at playgrounds and may be more active in shaded areas. CONCLUSION: Children have limited protective shade available to them at playgrounds. Future research is needed to determine how to best increase shade provision and to further explore the impact it has on playground usage, activity levels, temperature and UVR exposure.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".