COVID-19 Experiences, PPE, and Health Concerns in Toronto, Canada Bicycle Delivery Workers: Cross-sectional Pilot Survey
Bibliographic record
Abstract
OBJECTIVES: To pilot recruitment methods for bicycle delivery workers in Toronto, Canada and to assess workers' experiences with COVID-19 and personal protective equipment (PPE). METHODS: This was a cross-sectional study. An online survey was deployed and advertised via social media with both paid and free postings in July and August of 2020. An incentive draw was used to motivate participation. These analyses summarized descriptive statistics of the sample and variables relevant to COVID-19. RESULTS: Complete responses were received from 35 participants. No participants reported a diagnosis of COVID-19, however four participants indicated experiencing symptoms. Most participants reported they used PPE, especially masks and/or respirators (97.1%) and 71.4% of participants indicated their employer provided them with PPE (masks or gloves). Participants expressed concern about precarious work and uncertainty about their own COVID-19 exposure risk. CONCLUSIONS: Bicycle delivery workers are a precarious working population that may be difficult to reach for research recruitment purposes. Given their essential role in deliveries during the COVID-19 pandemic, further work is needed to characterize exposures and risks in this population.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".