Importance of skills development on labour market participation among workers aged 35 or older - a systematic review of prospective cohort studies
Bibliographic record
Abstract
OBJECTIVE: Continuous skills development is important for keeping up with new demands in workplaces and may also influence labour market participation. This systematic review aims to determine whether skills development affects labour market participation among workers aged 35 or older. MATERIALS AND METHODS: A systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was conducted. We searched Web of Science Core Collection, PubMed, EBSCO, ProQuest and Ovid in May 2023, and conducted an additional search in Google Scholar in November 2023. Eligibility criteria were; 1) prospective cohort studies 2) workers 35+ years 3) participation in, or opportunities to participate in skills development 4) outcomes related to labour market participation and 5) studies published in English or Scandinavian languages. Two independent reviewers’ extracted data, assessed the risk of bias (Newcastle Ottawa Scale) and evaluated the certainty of the evidence (GRADE) of the included studies. RESULTS: The literature search identified 5,147 records, of which 19 (n=1,089,749 and 759,931 person-years) met the inclusion criteria. GRADE indicated a “very low” quality of evidence for all outcomes. Overall, 12 studies found an association: 1) four studies found that skills development / opportunities for skills development reduced early retirement, 2) one study found that a lack of skills development increased the likelihood of early retirement, and 3) seven studies found that skills development / opportunities for skills development were associated with working longer. CONCLUSIONS: This systematic review presents varied findings concerning the link between skills development and labour market participation. TRIAL REGISTRATION: This systematic review was registered with PROSPERO (CRD42023419005).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.017 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".