MétaCan
Menu
Back to cohort
Record W3174878119 · doi:10.1093/annweh/wxab024

COVID-19 Experiences, PPE, and Health Concerns in Toronto, Canada Bicycle Delivery Workers: Cross-sectional Pilot Survey

2021· article· en· W3174878119 on OpenAlexafffundabout
Marianne Harris, Tracy L Kirkham

Bibliographic record

VenueAnnals of Work Exposures and Health · 2021
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsToronto Metropolitan UniversityOccupational Cancer Research CentreUniversity of Toronto
FundersRyerson University
KeywordsCross-sectional studyCoronavirus disease 2019 (COVID-19)Environmental health2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Occupational safety and healthPersonal protective equipmentMedicineMedical emergencyVirologyOutbreak

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.192
GPT teacher head0.442
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueAnnals of Work Exposures and HealthSame topicInfection Control and VentilationFrench-language works237,207