119: The Need for Safer Pool Fencing: A 10 Year Retrospective Study of Paediatric Drownings
Bibliographic record
Abstract
Drowning is the second leading cause of injury related death for Canadian children. For every child who dies from drowning, another five receive emergency department care for nonfatal drowning injuries. Approximately 50% of private pool drownings involve 1–4 year olds, with the majority lacking true four-sided fencing and self-closing, self-latching gates. Private pools are key locations for interventions, as safety features can be added to prevent children from accessing pools without caregivers' awareness. Many cities in Canada have attempted to improve pool safety; however, by-laws do not fully identify with pool enclosure recommendations issued by the Office of the Chief Coroner of Ontario. To identify drowning incidences involving the paediatric population in order to focus prevention efforts and develop potential intervention strategies. A retrospective chart review was conducted from January 2004 to December 2013 for drowning and nonfatal submersion diagnoses in children under 18 across three urban hospitals. Cases where the manner of drowning was suicide or homicide were excluded. Medical records were examined using the electronic databases Sovera and Meditech. There were 61 drowning incidences during the ten years, and almost half (44%) of these occurred in private pools (Figure 1). Of those in private pools, 19 of 27 were in the 1 to 4 age group category. Moreover, 74% of incidences that occurred in private pools were classified as unsupervised/supervision distracted. Information regarding true 4-sided fencing showed no 4-sided fence in 10 of 27 cases and in 15 of 27 it was unknown. Of the eight deaths that occurred during the study period, seven of eight were within the 1 to 4 age group. Five of the deaths occurred in a private pool where there was no 4-sided pool fencing. The results identified the age group 1 to 4 as a vulnerable population to focus on with regard to drowning. In addition, a large portion of drowning incidences and deaths in this age group occurred in private pools, which offers a focal point for prevention. The results suggest that reducing the access of this age group to private pools may prevent and reduce drowning incidences and deaths. Thus, an initiative for by-law changes regarding the implementation of safer pool fencing in private pools across the country is needed to prevent drowning incidences, and has the potential to reduce the number of deaths and injuries from childhood drownings.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".