Did perceptions of supportive <scp>work–life</scp> culture change during the <scp>COVID</scp>‐19 pandemic?
Bibliographic record
Abstract
Objective: This article examines whether perceptions of supportive work-life culture changed during the COVID-19 pandemic-and if that depended on (1) working from home; (2) children in the household; and (3) professional status. We test for gender differences across the analyses. Background: During normal times, the "ideal worker" is expected to prioritize the demands of their job and is penalized for attending to family/personal needs while on company time. But the organization and expectations of roles might have changed due to the COVID-19 pandemic. Organizations could have become more empathic or reinforced norms about single-minded devotion to work. Method: In September 2019, we collected data from a national sample of Canadian workers. Then, during a pivotal period of shocks to the economy and social life, we re-interviewed these participants in June 2020. Results: We discovered that overall perceptions of work-life culture became more positive. However, subgroup differences revealed this positive change was muted among employees: (1) who worked from home; (2) with children under age 6 at home; and (3) in professional occupations. We found no subgroup differences by gender. Conclusion: Our findings address speculation about whether employees perceived their employers as becoming more supportive of work-life fit early in the pandemic. Future research should determine (a) longer-term change in work-life culture during and after the pandemic; and (b) whether the actual benefits of supportive work-life culture also changed or if it was "window dressing." This direction suggests it should have more strongly reduced work-life conflict as the pandemic unfolded.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".