Managing work, family, and school roles: Disengagement strategies can help and hinder.
Bibliographic record
Abstract
The extent to which individuals manage multiple role domains has yet to be fully understood. We advance past research by examining the effect of interrole conflict among three very common and critically important life roles-work, family, and school-on three corresponding types of satisfaction. Further, we examine individual-based techniques that can empower people to manage multiple roles. In doing so, we integrate the disengagement strategies from the work recovery and coping literatures. These strategies focus on taking your mind off the problems at hand and include cognitive disengagement (psychological detachment, cognitive avoidance coping), as well as cognitive distortion (escape avoidance coping). We examine these strategies in a two-wave study of 178 individuals faced with the challenge of managing work, family, and school responsibilities. Findings demonstrated a joint offsetting effect of psychological detachment and cognitive avoidance coping on the relationship between work conflict and work satisfaction. Findings also indicated an exacerbating effect of escape avoidance coping on the relationship between work conflict and work satisfaction, school conflict and school satisfaction, and between family conflict and family satisfaction. Implications for theory and practice are discussed.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".