Occupational pressures of frontline workers enforcing COVID-19 pandemic measures in Ontario and Quebec, Canada
Bibliographic record
Abstract
BACKGROUND: During the COVID-19 pandemic, low-wage public-facing frontline workers (FLWs), such as grocery store clerks, were required to monitor retail customers and enforce COVID-19 protocols. OBJECTIVE: This analysis aimed to examine FLWs experiences of enforcing COVID-19 pandemic measures. METHODS: Between September 2020 and March 2021, in Ontario and Quebec (Canada), we conducted in-depth interviews about customer-related work and health risks with FLWs who interacted with the public (n = 40) and their supervisors (n = 16). Using a lens of situational analysis, verbatim transcripts were coded according to recurring topics. RESULTS: We found that enforcing public health measures placed already-precarious workers in difficult occupational health circumstances. Enforcement of measures created additional workplace responsibilities, stress, and exposed them to potentially negative reactions from customers. CONCLUSIONS: Interventions to better support these workers and improved methods of protection are discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 teacher head, 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".