Mother–Father Parity in Work–Family Conflict? The Importance of Selection Effects and Nonresponse Bias
Bibliographic record
Abstract
Abstract Do mothers experience worse work–family conflicts compared with fathers? Yes, according to trenchant and influential qualitative studies that illuminate mothers’ deeply felt problems from work demands that intrude into family life. No, suggest studies employing representative samples of employed parents that show mothers’ and fathers’ have similar work-to-family conflict. We assess these paradoxical depictions of parents’ lives using panel data from the national Canadian Work, Stress and Health study (2011–2019). We argue that comparable reports from men and women are misleading because they overlook mothers’ adjustment of work hours in the face of high conflict. As evidence, we reveal a gender suppression effect whereby mothers report higher conflict than fathers when adjusting for work hours in the baseline sample. Next, we show that mothers are more likely to leave paid work because of conflict. In fact, they are three times more likely than fathers to leave because of conflict’s focal predictor—having young children. These findings reflect mothers’ adjustment to the conflict they might already experience or anticipate. We use pooled person-year data and fixed-effects regression with logit specification to estimate the hazard of not working at the next wave by gender. We underscore the selection of some mothers into surveys or subsequent waves because it excludes those who systematically dropped out due to higher conflict and its primary predictor of having young children. We argue the observed “gender symmetry” of conflict is an artifact and illustrate the importance of theorizing stress processes over time to understand contradictory work–family conflict scholarship.
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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 | 0.134 | 0.280 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".