The quarter-life crisis? Precarious labour market status and mental health among 25-year-old in England
Bibliographic record
Abstract
Despite an increase in living standards and material comforts in industrialised societies, today's ‘emerging adults’ (aged from late teens to mid-to-late 20s) face greater challenges than ever before. The aim of this paper is to explore the relationship between labour market status and mental health for the ‘millennial generation’ in England, and whether it varies by gender and ethnicity. This study will be the first to draw on the results from the 2015 sweep of Next Steps data when the sample members are aged 25 and, together with the previous seven sweeps, bring the debate up to date by providing first estimates of the life condition of contemporary emerging adults. We find black and minority ethnic groups have lower odds of reporting mental ill-health at age 25 than the white group. With respect to labour market status, we find that net of socio-economic characteristics, educational attainment, behavioural variables and income at age 25, those who are unemployed are more than twice as likely to report symptoms of poor mental health as those who are employed. Shift workers and those on zero-hours contracts are also at a greater risk of mental ill-health by 47% and 44% respectively than those who are not shift workers or zero-hours workers. We find no significant difference for those who have a second job or are on a permanent contract for mental health at age 25 compared to those who do not have a second job or are on a temporary contract.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".