An analysis of health and safety audits of aquatic facilities in Ontario: 2002–2020
Bibliographic record
Abstract
The risk of drowning in swimming pools is a concern for bathers in Canada. The Aquatic Safety Audit (ASA) is a service provided by the Lifesaving Society (LSS) to assess operations of aquatic facilities in Canada. However, the results of these ASA reports have never been analyzed systematically. We compiled and analyzed ASA reports from 2002 to 2020, received from LSS Ontario, to ascertain the most frequently identified recommendations (i.e., safety deficiencies) and identify trends in the data. A total of 59 ASA reports of aquatic facilities that contained swimming pools (i.e., indoor, outdoor, or both) were examined. The study identified a total of 4,589 recommendations. The general audit category of “Aquatic Facility” (n = 4,000 deficiencies) was more problematic than “Emergency and Operating Procedures” (n = 244), “Personnel” (n = 211), and “Communication” (n = 143). The “deck” subcategory of “Aquatic Facility” had the most deficiencies (n = 1,050). The topmost identified deficiencies were “no medical signs at the entrance points” (n = 37, priority concern) and “inadequate lighting levels” (n = 35, primary recommendation). In our comparative analysis, facilities with at least one outdoor pool and municipally owned facilities were more likely to be associated with safety deficiencies, compared to facilities with indoor pools and nonmunicipally owned facilities (e.g., university, military, private sector). Our study noted that noncompliance and violations of legal requirements were common in aquatic facilities in Ontario. Future studies are suggested to further investigate the poor safety performance of facilities, especially those with outdoor pools or are municipally owned.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".