Changes in labour market histories and their relationship with paid work around state pension age: evidence from three British longitudinal studies
Bibliographic record
Abstract
Abstract Many countries have implemented policies to extend working lives in response to population ageing, yet there remains little understanding of what drives paid work in later life, nor how this is changing over time. This paper utilises the 1988/89 Survey of Retirement and Retirement Plans, the 1999 British Household Panel Survey and the 2008 English Longitudinal Study of Ageing, to investigate drivers of paid work in the ten years surrounding state pension age (SPA) for women and men in, comparing cohorts born in the 1920s, 1930s and 1940s. Using optimal matching analysis with logistic and multinomial regression models, the study assesses the relative importance of lifecourse histories, socio-economic circumstances and contemporaneous factors, in determining paid work in mid- and later life. Participation in paid work in the five years preceding and beyond SPA increased markedly for men and women across cohorts, with women's lifecourses and engagement with paid work changing considerably in these periods. However, for women, a lifetime history of paid work remained a crucially important predictor of paid work in later life, and this relationship has strengthened over time. Experiencing divorce has also become an important driver of paid work around SPA for the youngest cohort. Having children later, and still having a mortgage, also independently predict labour force participation for women and men. Across all cohorts and for women and men, working at these older ages was a function of higher income and better health. These findings suggest that policies which enable people to maintain ties to paid work across the lifecourse may be more effective at encouraging later-life employment than those concerned only with postponing the retirement transition.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".