Uptake of SARS-CoV-2 workplace testing programs, March 2020 to March 2021
Bibliographic record
Abstract
Structured Abstract Objective To track uptake of workplace SARS-CoV-2 testing programs using publicly-available data (e.g., press releases), supplementing findings from employer surveys. Methods We tracked testing programs reported by 1,159 Canadian and 1,081 international employers across sectors from March 1, 2020 to March 31, 2021. We analyzed trends in uptake of testing programs, including over time and by workplace setting. Results 9.5% (n=110) of Canadian employers and 24.6% (n=266) of international employers tracked reported testing. The prevalence of reported testing programs was less than 20% in some settings associated with high risk of transmission including retail and customer-facing environments, and indoor and mixed blue collar workplaces. Conclusions Publicly-available data suggest that fewer employers are testing than indicated by surveys. Workplace safety in high-risk workplaces could be further improved by implementing testing strategies that deploy both screening and diagnostic tests.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".