The relationship between work arrangements and work-family conflict
Bibliographic record
Abstract
BACKGROUND: A review of the literature determined that our understanding of the efficacy of flexible work arrangements (FWA) in reducing work-family conflict remains inconclusive. OBJECTIVE: To shed light on this issue by examining the relationship between work-to-family conflict, in which work interferes with family (WFC), family-to-work conflict, in which family interferes with work (FWC), and four work arrangements: the traditional 9-5 schedule, compressed work weeks (CWWs) flextime, and telework. METHODS: Hypotheses were tested on a sample of 16,145 employees with dependent care responsibilities. MANCOVA analysis was used with work arrangement as the independent variable and work interferes with family (WFC) and family interferes with work (FWC) as dependent variables. Work demands, non-work demands, income, job type and gender were entered into the analysis as covariates. RESULTS: The more flexible work arrangements such as flextime and telework were associated with higher levels of WFC than were fixed 9-to 5 and CWW schedules. Employees who teleworked reported higher FWC than their counterparts working a traditional 9-to-5 schedule particularly when work demands were high. CONCLUSIONS: The removal of both temporal and physical boundaries separating work and family domains results in higher levels of work-family interference in both directions. The results from this study suggest that policy makers and practitioners who are interested in improving employee well-being can reduce work-family conflict, and by extension improve employee mental health, by focusing on the effective use of traditional and CWW schedules rather than by implementing flextime and telework arrangements.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".