The direct and indirect effect of time use on subjective well-being: gender differences at different life stages
Bibliographic record
Abstract
Time is heterogeneously perceived in its meaning and value depending on things and beings involved. How people allocate their 24 hours per day reflects personal needs and is a fundamental question in activity-based travel demand analysis. This study aims to explore the inherent heterogeneity of time by investigating different time use patterns among population subgroups, and how time allocation contributes to subjective well-being (SWB) across these groups. To achieve this, the study uses data from the 2015 Canadian General Social Survey (GSG) on Time Use and stratifies the sample based on gender and age to reveal differences in time use and SWB between males and females within each age group, with parenthood further amplifying the differences. Then, the study employs multi-group structural equation models (SEM) to examine the direct and indirect effects of time use on SWB, while accounting for variations between genders and age groups. The analysis identifies seven notable activity types, including non-discretionary and leisure categories, which directly impact SWB or indirectly influence it through mediation by four factors: time crunch, stress, health, and mental health. The mediation analysis explains the mechanisms by which time use on different activities affects SWB. The results shed light on critical gender differences at different life stages regarding the role of time use for different aspects of well-being. The heterogenous time use-SWB connections provide valuable insights into comprehending diverse decisions made in activity-based travel demand.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".