Balancing act: The relationship between work-family balance, gender, quality of life indicators and self-rated health.
Bibliographic record
Abstract
Substantial numbers of Canadians work shifts. The reasons individuals work shifts are varied and complex. Prior research regarding the relationship between work-family balance, gender, quality of life indicators and health has yielded mixed results. The goal of this research was to examine the association between work-family balance, quality of life indicators and Canadians' overall health status while controlling for socio-economic status, education, family structure and life satisfaction. The two objectives of this study were: 1) to explore how the relationship between work-related characteristics, quality of life and overall health status is different among Canadian male and Canadian female workers, controlling for age, education, socio-economic status, family structure, and life satisfaction and, 2) to examine the relationship between shift configuration and employees' overall health status, controlling for socio-economic status, gender, education, family structure and life satisfaction. This study involved analyses of cross-secional national data from the General Social Survey (GSS) 2006, Cycle 20. The sample for the study included employed men and women who were married or living in common-law relationships, ages 18 through 69. Bivariate and logistic regression analyses were conducted to address the stated research objectives. Appropriate survey weights were applied to estimate population characteristeics. To fully account for the survey's complex sample design, mean bootstrap weights were used for variance estimation and calculation of confidence intervals. Findings indicated that for women and shift workers, both work-to-family spillover and family-to-work spillover were predictve of poor self-rated health. Spillover was not a predictor of poor health for men or day workers. Shift configuration was not found to be significantly correlated with poor self-rated health. Analyses should be repeated to test for interaction between shift work and sleep quality as sleep quality was controlled for in this study.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".