Labor markets in crisis: The causal impact of Canada's COVD19 economic shutdown on hours worked for workers across the earnings distribution
Bibliographic record
Abstract
We use Statistics Canada's Labour Force Survey to explore the labor market impacts of the novel coronavirus (COVID-19). Specifically, we adopt a unique identification strategy to examine the heterogeneous causal effects of the COVID-19 economic shutdown by governments on hours worked across the earnings distribution in Canada, focusing on individuals who remained employed in March and April. Most early crisis analyses found that workers in the bottom of the earnings distribution experienced a much larger negative shock to hours worked than workers in the top of the earnings distribution. However, some low-income individuals are also working more as a result of the COVID-19 economic shutdown, and this nuance is missed when only considering the net effect. When we condition on whether workers lost or gained hours, we find that workers in the bottom of the earnings distribution experienced not only the largest percentage reduction in hours, but also the largest percentage increase in hours.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".