Unpredictable Work Schedules and Gender Divisions of Domestic Labor
Bibliographic record
Abstract
Unpredictable work schedules dictated by employers can be difficult to reconcile with parental obligations. As such, they may motivate different strategies for managing and dividing domestic labor among partnered parents. Drawing on pooled cross-national survey data of dual-earner heterosexual parents of young children in Canada, Germany, Poland, Italy, Sweden, and the United States, we investigate the relationship between the predictability of parental work schedules and divisions of housework and childcare. Analyses reveal stronger adaptations in childcare than housework, with results suggesting that when parental availability is uncertain, families tend to rely more often on the partner with a regular schedule to manage and meet children's needs. When both parents have unpredictable schedules, fathers also take on a greater share of childcare. The implications of fathers’ unpredictable schedules thus differ depending on whether the mother also works an unpredictable schedule, highlighting the importance of analyzing parents’ schedules together. Household economic security and gender egalitarian attitudes around fathers’ caregiving also condition the relationship between unpredictable schedules and divisions of domestic labor. Overall, findings highlight the need to expand understanding of time availability in research on domestic labor beyond total work hours to wider and more relational temporal dimensions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".