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Record W4235869465 · doi:10.33423/ajm.v19i4.2392

Non-Cognitive Skills: How Much Do They Matter for Earnings in Canada?

2019· article· en· W4235869465 on OpenAlexaffabout

Bibliographic record

VenueAmerican Journal of Management · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsEmployment and Social Development Canada
Fundersnot available
KeywordsConscientiousnessAgreeablenessBig Five personality traitsNeuroticismWageEarningsNon cognitiveExtraversion and introversionPsychologyCognitionCognitive skillEconomicsDemographic economicsPersonalityLabour economicsSocial psychology

Abstract

fetched live from OpenAlex

Evidence from different countries suggests that non-cognitive skills play an important role in wage determination and overall social outcomes, but studies for Canada are scarce. We contribute to filling this gap by estimating wage regressions with the Big Five traits using the Longitudinal and International Study of Adults. Our results indicate that conscientiousness is positively associated with wages, while agreeableness, extraversion, and neuroticism are associated with negative returns, with higher magnitudes on agreeableness and conscientiousness for females. Cognitive ability has the highest estimated wage return so, while significant, non-cognitive skills do not seem to be the most important wage determinant.

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)0.005
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 score0.022
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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