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The quarter-life crisis? Precarious labour market status and mental health among 25-year-old in England

2019· article· en· W2944369787 on OpenAlexaboutno aff
Morag Henderson

Bibliographic record

VenueLongitudinal and Life Course Studies · 2019
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
FundersEconomic and Social Research Council
KeywordsMental healthOddsQuarter (Canadian coin)Ethnic groupEducational attainmentGerontologyDemographyDemographic economicsPsychologyMedicineGeographyPolitical scienceSociologyPsychiatryLogistic regressionEconomicsEconomic growth

Abstract

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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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.366
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2019
Admission routes1
Has abstractyes

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