A legislative scan and literature review of lifeguard staffing requirements at public swimming pools in Canada
Bibliographic record
Abstract
Within the Ontario public pool legislation, a certain number of lifeguards are required for a given number of bathers in a pool at a given time. Of note, these ratios vary across Canada, and there is little to no scientific evidence given for the required lifeguard to bather ratios in legislation or if they are sufficient to ensure bather safety. Our objective was to perform a legislative scan of Canadian public pool legislation as well as a literature review of scientific evidence to support the ratios used in legislation. A case study was also conducted to illustrate the methods found in the literature and apply it to a pool scenario using the lifeguard:bather ratios prescribed in the Ontario legislation. Using keywords across databases, papers were categorized based on five elements that correspond to a proper water rescue (ratio, scanning, technique, vigilance, scanning cues, and zoning). The literature review indicated that more lifeguards allow for a heightened vigilance, an increase in proper scanning technique, as well as coverage of zones. However, more research must be conducted with regards to proper staffing. Additional research should also be conducted to determine the ideal lifeguard:bather ratio, as there is a lack of standardization of these ratios across Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.029 | 0.045 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".