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Record W2801359211 · doi:10.1177/1474904118770818

Higher education for happiness? Investigating the impact of education on the hedonic and eudaimonic well-being of Europeans

2018· article· en· W2801359211 on OpenAlexfundno aff
Janine Jongbloed

Bibliographic record

VenueEuropean Educational Research Journal · 2018
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFlourishingEudaimoniaHappinessWell-beingOperationalizationVocational educationPsychologyLife satisfactionHigher educationSocial psychologyDevelopmental psychologyPedagogyPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

This study examines the impact of post-secondary education on the well-being of Europeans, comparing single-item hedonic and multi-dimensional eudaimonic models of well-being, operationalized as ‘satisfaction with life’ (SWL) and ‘flourishing’. The results indicate that the impact of education varies significantly when well-being is defined from each of these two perspectives: although vocational education is not significantly associated with the SWL of women and men, it is significantly associated with the extent to which both men and women are flourishing in their lives. Tertiary education is significant across all models for both SWL and flourishing. This study highlights the importance of comprehensive conceptualizations and measurements of well-being in European educational research and public policy.

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)0.004
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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.138
GPT teacher head0.464
Teacher spread0.326 · 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

Citations73
Published2018
Admission routes1
Has abstractyes

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