The Precarity of Progress: Implications of a Shifting Gendered Division of Labor for Relationships and Well-Being as a Function of Country-Level Gender Equality
Bibliographic record
Abstract
Abstract The onset of the COVID-19 pandemic saw a shift toward a more traditional division of labor–one where women took greater responsibility for household tasks and childcare than men. We tested whether this regressive shift was more acutely perceived and experienced by women in countries with greater gender equality. Cross-cultural longitudinal survey data for women and men ( N = 10,238) was collected weekly during the first few months of the pandemic. Multilevel modelling analyses, based on seven waves of data collection, indicated that a regressive shift was broadly perceived but not uniformly felt. Women and men alike perceived a shift toward a more traditional division of household labor during the first few weeks of the pandemic. However, this perception only undermined women's satisfaction with their personal relationships and subjective mental health if they lived in countries with higher levels of economic gender equality. Among women in countries with lower levels of economic gender equality, the perceived shift predicted higher relationship satisfaction and mental health. There were no such effects among men. Taken together, our results suggest that subjective perceptions of disempowerment, and the gender role norms that underpin them, should be considered when examining the gendered impact of global crisis.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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 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".