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Record W2461607412 · doi:10.29173/cjs23863

Youth Unemployment and Career Scarring: Social-Psychological Mediating Effects?

2016· article· en· W2461607412 on OpenAlexafffundvenue
Harvey Krahn, Angela Chow

Bibliographic record

VenueThe Canadian Journal of Sociology · 2016
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Alberta
KeywordsUnemploymentYouth unemploymentPsychologyLongitudinal dataLongitudinal studyLabour economicsDemographic economicsEconomicsSociologyMedicineDemographyEconomic growth

Abstract

fetched live from OpenAlex

Unemployment has career scarring effects for adults, and sometimes for youth, but previous research has not directly demonstrated how this occurs. This 14-year (1985-99) longitudinal study reveals that cumulative unemployment between age 18 and age 32 has a negative effect on both total income and quality of employment at age 32. This scarring effect is not mediated by parallel changes in self-esteem, perceived control or extrinsic work values. Labour market mechanisms, rather than social psychological processes, are likely responsible for the career scarring effect of youth unemployment.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.118
GPT teacher head0.397
Teacher spread0.279 · 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

Citations20
Published2016
Admission routes3
Has abstractyes

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