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Record W2800732996 · doi:10.1177/0950017018764534

Workplace Variation in Fatherhood Wage Premiums: Do Formalization and Performance Pay Matter?

2018· article· en· W2800732996 on OpenAlexafffundabout
Sylvia Fuller, Lynn Prince Cooke

Bibliographic record

VenueWork Employment and Society · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaSimon Fraser UniversityCanadian Institutes of Health ResearchEuropean CommissionUniversity of Oxford
KeywordsWageEconomicsContext (archaeology)IncentiveLabour economicsWage inequalityCollective bargainingInequalityEfficiency wageParental leaveOccupational segregationGender pay gapDemographic economicsWork (physics)

Abstract

fetched live from OpenAlex

Parenthood contributes substantially to broader gender wage inequality. The intensification of gendered divisions of paid and unpaid work after the birth of a child create unequal constraints and expectations such that, all else equal, mothers earn less than childless women, but fathers earn a wage premium. The fatherhood wage premium, however, varies substantially among men. Analyses of linked workplace-employee data from Canada reveal how organizational context conditions educational, occupational and family-status variation in fatherhood premiums. More formal employment relations (collective bargaining and human resource departments) reduce both overall fatherhood premiums and group differences in them, while performance pay systems (merit and incentive pay) have mixed effects. Shifting entrenched gendered divisions of household labour is thus not the only pathway to minimizing fathers’ wage advantage.

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)0.006
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 score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.013
GPT teacher head0.259
Teacher spread0.245 · 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

Citations59
Published2018
Admission routes3
Has abstractyes

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