Test of Work-to-Family and Family-to-Work Models of Conflict and Satisfaction: An Analysis of Dual Career Couples in Bangladesh
Bibliographic record
Abstract
Greater access of women to education and the job market has led to the increased participation of women in professional employment throughout the world. Bangladesh is no exception from this trend of change which is creating the phenomenon of dual-career couples (two working people in a committed relationship). This trend has radically changed traditional family structures and gender roles in society. These types of couples need to integrate both their work and family life together. This is creating challenges for both dual-career couples and their employers. Past research has posited that the imbalance between work and family lives, or the conflict between work and family lives of the dual-career couples can significantly reduce employee productivity, performance, job satisfaction, family satisfaction, and life satisfaction. This, in turn, hinders the performance of a business by affecting its organizational innovation, efficiency, and effectiveness.The current study tested predictions regarding the nature of relationships among these variables on 180 dual career couples (N=360) in Bangladesh. Literature reviews suggested two forms of conflict; work-to-family conflict and family-to-work conflict among these dual career couples. Models were developed by addressing these two types of conflict and testing the relationship with various types of satisfaction. A structured questionnaire was used as the primary source for data collection. Results reveal that work-to-family conflict negatively predicts job satisfaction and life satisfaction. No evidence is found regarding the relationship of family-to-work conflict with job and family satisfaction.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".