A Forced Vacation? The Stress of Being Temporarily Laid Off During a Pandemic
Bibliographic record
Abstract
A million Canadian workers suddenly became temporarily laid off (TLO) early into the pandemic. How did this affect mental health? Guided by the Stress Process Model (SPM), we would expect that this job disruption should increase psychological distress. However, given the unique context surrounding the early period of the pandemic, we advance the forced vacation hypothesis, which argues that those who became TLO would—at least initially—report lower levels of distress. To address this puzzle, we use a mixed-methods approach combining a national longitudinal survey dataset and in-depth interviews. Our quantitative analyses reveal that individuals who were TLO had lower distress in April 2020 compared with their peers who continued working. Our interviews uncover several potential explanations for these patterns. The findings provide an elaboration to the SPM as the pandemic context altered the meaning of being TLO, making it feel like a “forced vacation”—at least initially.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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 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".