Operational impacts at municipal aquatic facilities due to the COVID-19 public health measures
Bibliographic record
Abstract
Due to the COVID-19 pandemic, aquatic facilities were initially closed but then allowed to open with strict public health measures in place. However, it is unclear how these measures impacted pool operations. This study surveyed municipal pool operators in Ontario regarding what public health measures were adopted during the pandemic (March 2020 to March 2022). Results were reported using frequency descriptions and t-tests were conducted to compare responses during and after the pandemic. Overall, 48 pool operators participated, representing a response rate of 23.6%. Every operator made changes to pool entry procedures, implemented social distancing measures, posted public health notices and reduced swim class sizes. Some operators had issues hiring enough qualified staff and, in fact, had to reduce their hours or even close the facility. In addition, labour-intensive duties included increased frequency of cleaning and health screening of every pool visitor. The changes to pool operations and closures may have adversely impacted the mental health of staff and the public, respectively. In anticipation of another pandemic, it is recommended that pool operators provide training and support to their staff. Also, future pandemic guidelines ought to address both public health as well as occupational health and safety best practices.
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 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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.011 |
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; both teacher heads agree on what is shown here.
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".