Work, family, work–family conflict and psychological distress: A revisited look at the gendered vulnerability pathways
Bibliographic record
Abstract
This paper revisited the vulnerability hypothesis to explain the greater level of psychological distress among working women compared to working men. A comprehensive vulnerability model was tested in which work and family stressors and psychosocial resources are directly related to psychological distress and indirectly through work-to-family (WFC) and family-to-work (FWC) conflicts. Data came from a random sample of 989 women and 1,037 men working in 63 Canadian establishments. Multilevel path analyses were performed separately for men and for women. The results show that many work/family stressors and resources are linked to men's or women's psychological distress directly and indirectly through WFC and FWC. However, the z-test used to assess whether the relationships differed significantly between women and men indicated that only two relationships differ significantly between the two groups: experimenting problems with children and a low self-esteem are associated positively to psychological distress through FWC only for women. In addition to showing the specific involvement of work-family conflict in the psychological distress inequality, this study contributes to revealing that testing the differences in the magnitude of the relation offer a more suitable appraisal of the vulnerability mechanism involved in the psychological distress inequality between men and women.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| 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".