How do proactive employees reduce work-family conflict? Examining the influence of flexible work arrangements
Bibliographic record
Abstract
Purpose We examined who is more likely to use flexible work arrangements (FWAs) to alleviate work-family conflict (WFC) and under what conditions the use of FWAs actually reduces WFC. Design/methodology/approach We tested the model using survey data collected at two time points from 217 employees. Findings Proactive employees are more likely to use flextime to alleviate WFC (b = −0.03; 95% biased-corrected CI: [−0.12, −0.01]) and this mediation relationship is not moderated by their level of low work-to-nonwork boundary permeability. In addition, only when proactive employees have a low work-to-nonwork boundary permeability does their use of flexplace alleviate WFC (b = −0.07, 95% bias-corrected CI: [−0.1613, −0.0093]). Originality/value We expand our understanding of who is more likely to utilize FWAs by identifying that employees with proactive personality are more likely to use flextime and flexplace. We also advance our understanding regarding the conditions whereby FWA use helps employees reduce WFC by identifying the moderating role of work-to-nonwork boundary permeability on the relationships between both flextime and flexplace use on WFC.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".