Does a Voluntary Job Change Affect Work-Family Balance?
Bibliographic record
Abstract
The question of work-family balance (WFB) is an area where increasing attention is being paid nowadays since it relates to the health, satisfaction, personal development of employees, to the care for their children, youths and elder family members. The purpose of the paper is to explore the connection between the voluntary job change and the potential improvement of the work-family balance since it was assumed that changing the job voluntarily might bring to a higher WFB as employees could satisfy their needs more effectively in a new working environment, chosen by their own will. Data were collected using a combination of CAWI (computer assisted web interview) and pen and pencil methods. Employees from various companies and public sector organizations from Slovenia were invited to participate in the study. Hierarchical cluster analysis was performed to identify clusters of family-work balancers, i.e. of those, who help with balancing employees’ work and family domains. Kruskal-Wallis test and Mann-Whitney U test were used to explore the correlation between the decision about the voluntary job change and the satisfaction with the work-family balance. The research has shown that the assessment of WFB does not depend on a voluntary job change. The exceptions are the group of employees with children (in a positive direction) and the group of employees without children and no help in the household (in a negative direction). The employees do not use a job change as a tool for increasing WFB. This is probably also due to the closed culture of Slovenians. The managers who do care about their employees and who do not wish to lose their best employees have therefore many possibilities to choose the proper coping strategies to help their employees balance their work and family lives.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".