An Overview of Work-Life Wellness for Teleworking Couples
Bibliographic record
Abstract
A sizeable number of employees throughout Canada are continuing to telework following the COVID-19 pandemic. Couples who telework may experience tension between their work and personal life. Telework may have both positive and negative impacts on work-life wellness depending on employee circumstances. For example, teleworking women with children may be expected to prioritize their home and family over their work. Even though COVID-related restrictions have eased in Canada, allowing for more freedom around home and work arrangements, it is plausible to expect a long-term shift towards an increased number of employees working from home more often, with associated changes in family dynamics as both partners adjust to this "new normal." In response to the complex relationship between teleworking and work-life wellness in the context of couples, the first author has proposed a study to research work-life wellness for teleworking couples, addressing the research question, "how do teleworking couples construct and cultivate work-life wellness together?". It is anticipated that this study will foster understanding of work-life wellness in teleworking couples, and inform policies, counselling techniques, and future research.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".