Investigating young adults’ mental health and early working life trajectories from a life course perspective: the role of transitions
Bibliographic record
Abstract
BACKGROUND: Many young adults leave the labour market because of mental health problems or never really enter it, through early moves onto disability benefits. Across many countries of the Organisation for Economic Co-operation and Development, between 30% and 50% of all new disability benefit claims are due to mental health problems; among young adults this moves up to 50%-80%. OUTLINE: We propose a research agenda focused on transitions in building young adults' mental health and early working life trajectories, considering varying views for subgroups of a society. First, we briefly review five transition characteristics, then we elaborate a research agenda with specific research questions. RESEARCH AGENDA: Our research agenda focuses on transitions as processes, in time and place and as sensitive periods, when examining young adults' mental health and early working life trajectories from a life course perspective. As more and more childhood and adolescent cohorts mature and facilitate research on later life labour market, work and health outcomes, transition research can help guide policy and practice interventions. FUTURE CROSS-DISCIPLINARY RESEARCH: In view of the many challenges young adults face when entering the changing world of work and labour markets, future research on transitions in young adults related to their mental health and early working life trajectories will provide ample opportunities for collaborative cross-disciplinary research and stimulate debate on this important challenge.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".