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Record W2143364931 · doi:10.1177/0165025410365803

Paths to success in young adulthood from mental health and life transitions in emerging adulthood

2010· article· en· W2143364931 on OpenAlexaff
Nancy L. Galambos, Harvey Krahn

Bibliographic record

VenueInternational Journal of Behavioral Development · 2010
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLife satisfactionPsychologyAngerYoung adultMental healthDepressive symptomsMarital statusBivariate analysisClinical psychologyEarly adulthoodLife course approachAdult developmentDevelopmental psychologyDemographyCognitionPsychiatrySocial psychologyPopulation

Abstract

fetched live from OpenAlex

This study followed a school-based sample (N = 920) to explore how trajectories of depressive symptoms and expressed anger from age 18 to 25, along with important life transitions, predicted life and career satisfaction at age 32. A two-group (women and men) bivariate growth model revealed that higher depressive symptoms at age 18 predicted lower life satisfaction in men and women, and lower career satisfaction in women. Slower declines across emerging adulthood in women’s depressive symptoms predicted lower life satisfaction, but slower declines in women’s expressed anger predicted higher career satisfaction. Marital and employment-related transitions were differentially related to men’s and women’s life and career satisfaction. Paths to success in young adulthood are diverse and gendered.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.365
Teacher spread0.342 · 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 source (direct Gemma or distilled Codex), 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

Citations81
Published2010
Admission routes1
Has abstractyes

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