Bibliographic record
Abstract
Objective To examine the gendered impact of community on work–family conflict (WFC) and whether respondents with young children benefit more from community resources compared with other residents. Background Studies suggest that the gender gap in WFC is decreasing. Most attribute this trend to individual‐level antecedents of work and family. However, these explanations do not take into account important community‐level components—specifically, men's and women's differential access to and use of community resources. Method Individual‐level data from 1,702 Canadians matched to census‐level data from the Canadian census were used, and hierarchical linear modeling techniques were employed. Results Key findings were that women and parents with young children experience more conflict in less resourced communities, and collective efficacy affected men's and women's reports of WFC, but in opposite, nonlinear ways: At higher levels of collective efficacy, women reported heightened conflict. For men, this pressure was only felt when efficacy levels were high. Conclusion There are important gender distinctions in reported WFC depending on one's community resources. In some circumstances, these resources are more beneficial for women than men and matter differently for parents with young children compared with those without young children. Implications These findings help inform community and policy‐based initiatives aimed at reducing residents' experiences of WFC, underscoring the utility of promoting efficacious communities.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".