Bibliographic record
Abstract
What are the effects of conflict between home and work?Does work stress affect those who live with you? In the rapidly changing modern work environment, time pressures seem ever increasing and new technology allows work to be conducted any time and anywhere. These are just two of the factors that make it more and more difficult for working men and women to integrate work and home life. Consequently, there is a need for flexible and innovative solutions to manage the work-home interface.Work-Life Balance: A Psychological Perspective presents up-to-date information on work-home issues, including the latest research findings. The book’s emphasis is strongly psychological, with a focus on practical solutions, and includes chapters which deal with psychological issues such as the conflict between work and family, how work stresses may affect partners, and recovery from work. It also includes sections on legal issues, as well as examples of initiatives being implemented by leading employers. Contributors are drawn from the leading researchers in their fields and reflect the international character of the current challenges facing employers and employees.Its practical focus and innovative approach make this an essential book for managers, HR professionals and organizational psychologists, as well as students in these disciplines. The theoretical basis and research focus mean the book will also be invaluable for researchers investigating workplace issues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.009 |
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".