An analysis of health and safety audits of aquatic facilities in Ontario: 2002–2020
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 it