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Record W4300655020

Does Temporary Interruption in Postsecondary Education Induce a Wage Penalty? Evidence from Canada

2016· preprint· en· W4300655020 on OpenAlexfundaboutno aff
Bernard Fortin, Safa Ragued

Bibliographic record

VenueRePEc: Research Papers in Economics · 2016
Typepreprint
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsnot available
FundersFonds de Recherche du Québec - SantéSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchUniversité Laval
KeywordsWageLabour economicsDemographic economicsEconomics
DOInot available

Abstract

fetched live from OpenAlex

Almost 40% of Canadian youth who left postsecondary education in 1999 had returned two years later. This paper investigates the extent to which schooling discontinuities affect post-graduation starting wages and whether the latter are influenced by the reasons behind these discontinuities. We use data from the 2007 National Graduate Survey. We apply Lewbel’s (2012) generated instruments approach. The source of identification is a heteroscedastic covariance restriction of the error terms that is a feature of many models of endogeneity. We also perform two-stage quantile regressions. We find a positive effect on wages of temporary interruption for men who held a full-time job during their out-of-school spell(s). Both men and women witness a wage decrease if their interruption depends on health issues. Women bear a wage penalty if their interruption is due to a part-time job, to lack of money, or is caused by reasons other than health, work, and money.

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)0.019
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 score0.126
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.061
GPT teacher head0.411
Teacher spread0.350 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicHigher Education Research StudiesFrench-language works237,207