Couples' changing work patterns in the United Kingdom and the United States during the COVID‐19 pandemic
Bibliographic record
Abstract
Going beyond a focus on individual-level employment outcomes, we investigate couples' changing work patterns in the United Kingdom (UK) and the United States (US) during the COVID-19 pandemic. Analyzing longitudinal panels of 2186 couples from the Understanding Society COVID-19 Survey (UK) and 2718 couples from the Current Population Survey (US), we assess whether the pandemic has elevated the importance of human capital vis-à-vis traditional gender specialization in shaping couples' work patterns. The UK witnessed a notable increase in sole-worker families with the better-educated partner working, irrespective of gender. The impact of the pandemic was similar but weaker in the US. In both countries, couples at the bottom 25% of the prepandemic family income distribution experienced the greatest increase in neither partner working but the least growth in sole-worker arrangements. Through a couple-level analysis of changing employment patterns, this study highlights the importance of human capital in shaping couples' paid-work organization during the pandemic, and it reveals the socioeconomic gradient in such organization.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".