A "Holy Grail" of Work and Family Life? When and How Schedule Control Functions as a Resource
Bibliographic record
Abstract
Schedule control is a job resource used to determine the timing of paid work and has been touted as a “holy grail” among work-family scholars and practitioners. While prior research has demonstrated that schedule control is linked with better work-life balance and health, it may not be an unfettered job reward. With this dissertation, I advance new knowledge that complicates the resource view of schedule control by integrating theoretical perspectives from diverse fields, including scholarship on roles in the work-family interface, sociology of mental health, and occupational health psychology. My dissertation extends prior research by identifying the conditions and statuses under which schedule control functions as a job resource versus scenarios where it might have circumscribed benefits or even unintended consequences for work-family life and health. Three patterns derived from longitudinal data analysis complicate the characterization of schedule control as solely a job resource. First, in Chapter 2 I reveal some of the downsides of schedule control for the work-family interface. I find that increases in schedule control are associated with a greater frequency of blurring the boundaries between work and nonwork roles. Moreover, schedule control exacerbates the association between job pressure and role blurring—and these observed downsides are stronger for women. Second, in Chapter 3 I compare the protective resource functions of schedule control and mastery for mitigating the detrimental health effects of competing work and family roles. I find that mastery has generalized stress-buffering functions whereby it alleviates the health-harming effects of both directions of work-family conflict. In contrast, schedule control has asymmetrical moderating functions: It attenuates the health effects of work-to-family conflict only. Third, in Chapter 4 I identify some of the status-based inequalities in the relationship between schedule control and job pressure. While I find that increases in schedule control help alleviate job pressure, my results reveal that schedule control is more effective in mitigating job pressure among professionals (relative to non-professionals) and those with more managerial power in the workplace. Collectively, this dissertation integrates interdisciplinary theoretical perspectives to advance knowledge on when and how schedule control functions as a resource for workers.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".