The impact of educational and work trajectories on wellbeing in midlife: A comparison of Canada and Germany
Bibliographic record
Abstract
This study employs longitudinal data from Germany and Canada to investigate how patterns of education, employment and care work influence wellbeing in midlife and how these patterns differ by gender and national context. Although previous research has addressed wellbeing at different life stages, it has rarely examined long-term effects across gendered life trajectories within contrasting welfare state contexts. We conduct separate analyses for men and women using partial proportional odds models (PPO) to estimate wellbeing levels. The models include clusters of educational and employment trajectories, along with socio-demographic variables that capture individual and family contexts known to affect wellbeing. Our results extend prior research demonstrating that education and employment trajectories shape midlife wellbeing, with associations varying by gender and country. Our analyses illustrate that Canadian women are able to draw benefits from part-time work, whereas for German women no consistent associations emerge once family-centred factors are considered. Among German men, wellbeing seems to be shaped primarily by household income, while for Canadian men good health is significantly associated with wellbeing. Our study underscores how gendered life course patterns continue to influence wellbeing and how welfare state regularities reinforce these inequalities. We conclude with a critical reflection on the compatibility of work and family life and its implications for wellbeing among women and men. • Educational and employment trajectories are associated with midlife wellbeing • For Canadian women, wellbeing is linked to forms of flexible employment • For German women, no associations emerge among wellbeing, education and work • For German and Canadian men, wellbeing is associated with individual resources • Welfare state structures reinforce gendered trajectories and wellbeing levels
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".