The Distribution of COVID-19 Related Risks
Bibliographic record
Abstract
This paper documents two COVID-related risks, viral risk and employment risk, and their distributions across the Canadian population.The measurement of viral risk is based on the VSE COVID Risk/Reward Assessment Tool, created to assist policymakers in determining the impacts of economic shutdowns and re-openings over the course of the pandemic.We document that women are more concentrated in high viral risk occupations and that this is the source of their greater employment loss over the course of the pandemic so far.They were also less likely to maintain one form of contact with their former employers, reducing employment recovery rates.Low educated workers face the same virus risk rates as high educated workers but much higher employment losses.Based on a rough counterfactual exercise, this is largely accounted for by their lower likelihood of switching to working from home which, in turn, is related to living conditions such as living in crowded dwellings.For both women and the low educated, existing inequities in their occupational distributions and living situations have resulted in them bearing a disproportionate amount of the risk emerging from the pandemic.Assortative matching in couples has tended to exacerbate risk inequities.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".