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Record W3182917408 · doi:10.1007/s10964-021-01477-1

Changes in Patterns of Social Role Combinations at Ages 25–26 among Those Growing Up in England between 1996 and 2015–16: Evidence from the 1970 British Cohort and Next Steps Studies

2021· article· en· W3182917408 on OpenAlexfundno aff
Thierry Gagné, Amanda Sacker, Ingrid Schoon

Bibliographic record

VenueJournal of Youth and Adolescence · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsnot available
FundersEconomic and Social Research CouncilFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsHealth psychologyHistory of psychologyPsychologyCohortCohort studyDevelopmental psychologyPublic healthGerontologyMedicineCognitive psychology

Abstract

fetched live from OpenAlex

Changes across education, employment, and family life over the past 20 years challenges the capacity of previously established social role combinations to continue representing the experiences of young men and women born since the late 1980s. Latent class analysis was used to derive patterns of role combinations at ages 25-26 in those growing up in England, using data from 3191 men and 3921 women in the 1970 British Cohort Study (1996) and 3426 men and 4281 women in the Next Steps study born in 1989-90 (2015-16). Role combinations in 1996 were well defined by five patterns across genders: educated, work-oriented, traditional family, fragile family, and slow starters. Patterns in 2015-16 diverged across genders (e.g., disappearance of home ownership in the traditional family group among men and higher education as a group identifier among women) and included across genders fewer work-oriented, more slow starters, and a new group of "left behind" who are excluded from work and relationships. Young men and women born around 1990 experienced diverging role combinations characterized by increased delays and inequalities, with fewer being able to attain the milestones traditionally associated with the transition to adulthood by the mid-20s.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.058
GPT teacher head0.331
Teacher spread0.273 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2021
Admission routes1
Has abstractyes

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