Initial Impacts of the COVID-19 Pandemic on the Canadian Labour Market
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this study, we review the initial impacts of the coronavirus disease 2019 (COVID-19) pandemic on the Canadian labour market. We focus on changes in employment and aggregate hours worked between February 2020 and April 2020 while accounting for normal monthly changes in these indicators. We find that COVID-19 induced a 32 percent decline in aggregate weekly work hours among workers aged 20-64 years, alongside a 15 percent decline in employment. We characterize the distribution of work lost, finding that nearly half of job losses are attributed to workers in the bottom earnings quartile. Those most affected by COVID-19 are in public-facing jobs in industries most affected by shutdowns (accommodation and food services), younger workers, paid hourly, and non-union. The results provide context for policy development, with both supply and demand sides of the labour market to consider.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it