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Record W1528418513 · doi:10.1111/ecin.12093

NEW MEASURES OF THE COSTS OF UNEMPLOYMENT: EVIDENCE FROM THE SUBJECTIVE WELL‐BEING OF 3.3 MILLION AMERICANS

2014· article· en· W1528418513 on OpenAlexaff
John F. Helliwell, Haifang Huang

Bibliographic record

VenueEconomic Inquiry · 2014
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsUniversity of AlbertaUniversity of British ColumbiaCanadian Institute for Advanced Research
Fundersnot available
KeywordsUnemploymentEconomicsLabour economicsPopulationDemographic economicsPercentage pointPoint (geometry)Social securityRest (music)MacroeconomicsDemographyMathematicsSociology

Abstract

fetched live from OpenAlex

Abstract Using two large U.S. surveys, we estimate the effects of unemployment on the subjective well‐being (SWB) of the unemployed and the rest of the population. For the unemployed, the nonpecuniary costs of unemployment are several times as large as those resulting from lower incomes, while the indirect effect at the population level is 15 times as large. For those who are still employed, a one percentage point increase in local unemployment has an impact on well‐being roughly equivalent to a 4% decline in household income. We also find evidence indicating that job security is an important channel for the indirect effects of unemployment . ( JEL E24 , H23 , J64 , J68 )

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)0.003
metaresearch head score (Gemma)0.011
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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.069
GPT teacher head0.326
Teacher spread0.257 · 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

Citations147
Published2014
Admission routes1
Has abstractyes

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