Strategies for Work-Life Balance for Women in the Academic Profession of Sri Lanka
Bibliographic record
Abstract
Most researchers are investigating work-life balance as a Human Resource Management tool used to attract, motivate and retain skilled employees rather than focusing on how individuals achieve work and personal life satisfaction when engaging work and family roles. This study shifts the focus from the engagement perspective that is highly beneficial for the organization to an enhancement perspective that increases the quality of personal life. This study aimed to explore and describe strategies for the work-family balance that can potentially contribute to the family wellbeing of women in the academic profession in Sri Lanka. Semi-structured interviews exploring the experiences of work-life balance were undertaken with thirty women lecturers in state universities in Sri Lanka. Data were analyzed using thematic analysis. The findings suggest the following strategies: compartmentalizing and separating roles between work and life, fostering personal relationships, building a professional support system, a better plan schedule, and organization, self–care in terms of personal, physical, and mental health, learning and research-based work environment, effective communication in both domains, and utilization of technology and focus on sacrificing personal life for success. The identified strategies, specifically for the Sri Lankan context and that it does so from the perspective of Sri Lankan women academics.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".