Exploring the link between sexual orientation, work-life balance satisfaction and work-life segmentation
Bibliographic record
Abstract
Purpose The purpose of this paper is to, using several cycles of the Canadian General Social Survey (GSS) covering 2010–2015, examine the patterns of work-life balance (WLB) satisfaction and work-life segmentation by sexual orientation. Design/methodology/approach In this paper, multivariate regression analysis is used. Findings The analysis shows that men living with a male partner are more satisfied with their WLB than their heterosexual counterparts. No statistically significant difference is found between women who live with a female partner and their heterosexual counterparts, in WLB satisfaction. Work-life segmentation is operationalized by the odds of being at the top levels of the life satisfaction scale without being satisfied with the circumstances of one’s job. Controlling for a wide range of characteristics, working Canadians living with a same-sex partner, regardless of their genders, are found more likely to have segmented their work and life domains than their heterosexual counterparts. Originality/value The paper, for the first time, investigates how sexual orientation relates to WLB satisfaction and work-life segmentation. This study exploits a unique opportunity offered by the Canadian GSSs in which WLB satisfaction is directly surveyed, all the while partnered sexual minorities are identifiable.
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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 | 0.003 |
| 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 | 0.000 | 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".