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Record W2068465043 · doi:10.1080/0003684042000191138

Evolution of the gender earnings gap among Canadian university graduates

2004· article· en· W2068465043 on OpenAlexaffabout
Ross Finnie, Ted Wannell

Bibliographic record

VenueApplied Economics · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsEarningsResidenceDemographic economicsBachelorGender gapEconomicsGender pay gapDemographySociologyLabour economicsGeographyAccountingWage

Abstract

fetched live from OpenAlex

This paper reports the results of an empirical analysis of the gender earnings gap among recent Canadian Bachelor's level university graduates. The overall gap as of two years leaving university narrowed significantly across successive cohorts of graduates, but widened significantly from two to five years out for all groups. Differences in the explanatory variables ‘explain’ account for between 40% and essentially the entire gap across the different periods, this portion rising from two to five years out and across cohorts. By the final group, all of the gap is thus ‘explained’ at the two-year point in time, and most of it is explained at the five-year mark, meaning that labour market returns (measured in this manner) are largely gender-neutral for the last group of graduates. Hours of work is the single most important influence, while past work experience, job characteristics, family status, and province of residence and language have smaller and more mixed effects.

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)0.004
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 score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.018
GPT teacher head0.166
Teacher spread0.148 · 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

Citations14
Published2004
Admission routes2
Has abstractyes

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