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Record W2102573894

The gender wage gap in the public and private sectors in Canada

2005· article· en· W2102573894 on OpenAlexaboutno aff
Xiaofang Cheng

Bibliographic record

VenueUniversity Library - University of Saskatchewan (University of Saskatchewan) · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsnot available
Fundersnot available
KeywordsWageLabour economicsPrivate sectorPublic sectorBusinessEconomicsDemographic economicsPolitical scienceEconomic growthEconomy
DOInot available

Abstract

fetched live from OpenAlex

The Canadian labour market experienced a considerable decline in the male-female pay gap during years 1988 to 1992. After 1992, however, the gender wage gap decreased only slightly. This paper will study the issue of difference in the explained gender wage gap in both the public and the private sectors and will examine the components of change in the wage gap between 1991 and 1996. We measure and decompose the gender wage differentials into explained and unexplained parts separately for the public and private sectors in Canada for the census years 1991 and 1996, and compare changes in the earnings gap between 1991 and 1996 in both sectors. The analysis is based on Oaxaca decomposition and Juhn-Murphy-Pierce decomposition techniques. Results show that gender wage differentials are present in both sectors, although at a lower level in the public sector than in the private sector. In 1996, 67 percent of the wage gap is attributable to the unexplained part in the public sector, while in the private sector, this figure is 76 percent. Generally, males tend to have higher return to experience and more favorable occupation and industry distributions, which can account for the gender wage gap. Our findings also show that the overall gender wage gap decreases in both the public sector and the private sector between 1991 and 1996. This decrease is mainly attributed to the diminishing of the unexplained portion. In both the public and the private sectors, improvements in women’s wage-determining factors and ranking relative to those of men contributed to a narrowing of the gender wage gap.

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 score0.089
Threshold uncertainty score0.647

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.010
Science and technology studies0.0080.002
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.014
GPT teacher head0.151
Teacher spread0.137 · 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
Published2005
Admission routes1
Has abstractno

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Same venueUniversity Library - University of Saskatchewan (University of Saskatchewan)Same topicLabor market dynamics and wage inequalityFrench-language works237,207