Control or Out of Control: work-life boundary management under the hybrid working context, In: Work Family Researcher Network Conference 2024, Concordia University, Montreal, 19-21, June, 2024.
Bibliographic record
Abstract
The widespread adoption of hybrid work has transformed work-life boundaries, providing increased control while also posing challenges through boundary blurring. This shift necessitates a nuanced understanding of how employees navigate evolving demands in their work and non-work domains, impacting their overall well-being and productivity. This paper bridges boundary control and flexibility implementation literature to explore employee experiences in hybrid work settings, focusing on boundary control and blurring. Using a longitudinal diary-interview approach, we collected 218 diary entries and 34 interviews from 19 academics and 15 professional staff in UK Higher Education for this research. Our findings reveal that hybrid work has a mixed effect on work-life boundary management; It enhances temporal and physical boundary control between work and non-work while exacerbating behavioural and psychological boundary blurring, often due to work intensification and ideal work culture. Notably, professional staff with fixed hybrid work schedule senses a culture shift away from the ideal work, granting them greater agency in boundary management. This research expands work-life literature by explaining how hybrid work amplifies and diminishes boundary control through a two-level interaction of individual perceptions and event-based behaviours. It underscores the pivotal role of workplace culture in shaping work-life boundary management in the hybrid work context, offering both theoretical insights and practical recommendations for diverse flexible work implementations. Our research makes several important contributions to the literature. First, we expand upon the existing work-life boundary literature by explaining how hybrid working exacerbates boundary blurring through a two-level interaction regarding individual perceptions and event-based behaviour. Hybrid working elevates the tensions of juggling between work and life domains. Similar to what is found in the work-life flexibility literature (Kossek., et al, 2020; Canibano, 2019), flexible working raises tensions about working overtime, working outside of normal hours and availability legacy issues. We then unveiled new tensions regarding heightened ‘always on’ expectations, team disconnection and work inefficiency. This would result in combined boundary blurring, including physical, temporal, behavioural, psychological and multi-task dimensions (Clarke, 2000; Allen, et al., 2014).
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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 | 0.006 | 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 | 0.007 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".