The effect of safer play equipment on playground injury rates among school children
Bibliographic record
Abstract
BACKGROUND: Changes to Canadian Standards Association (CSA) standards for playground equipment prompted the removal of hazardous equipment from 136 elementary schools in Toronto. We conducted a study to determine whether applying these new standards and replacing unsafe playground equipment with safe equipment reduced the number of school playground injuries. METHODS: A total of 86 of the 136 schools with hazardous play equipment had the equipment removed and replaced with safer equipment within the study period (intervention schools). Playground injury rates before and after equipment replacement were compared in intervention schools. A database of incident reports from the Ontario School Board Insurance Exchange was used to identify injury events. There were 225 schools whose equipment did not require replacement (nonintervention schools); these schools served as a natural control group for background injury rates during the study period. Injury rates per 1000 students per month, relative risks (RRs) and 95% confidence intervals (CIs) were calculated, adjusting for clustering within schools. RESULTS: The rate of injury in intervention schools decreased from 2.61 (95% CI 1.93-3.29) per 1000 students per month before unsafe equipment was removed to 1.68 (95% CI 1.31-2.05) after it was replaced (RR 0.70, 95% CI 0.62-0.78). This translated into 550 injuries avoided in the post-intervention period. In nonintervention schools, the rate of injury increased from 1.44 (95% CI 1.07-1.81) to 1.81 (95% CI 1.07-2.53) during the study period (RR 1.40, 95% CI 1.29-1.52). INTERPRETATION: The CSA standards were an effective tool in identifying hazardous playground equipment. Removing and replacing unsafe equipment is an effective strategy for preventing playground injuries.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".