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Record W2038661001 · doi:10.1300/j074v19n03_08

The Gender Wealth Gap: Structural and Material Constraints and Implications for Later Life

2007· article· en· W2038661001 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Women & Aging · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNational wealthInequalityDifferential (mechanical device)Demographic economicsNet worthVulnerability (computing)EconomicsHealth and Retirement StudySocial securityDebtSurvey data collectionLabour economicsSociologyDemographyFinance

Abstract

fetched live from OpenAlex

Wealth is an important measure of economic well-being, because while income captures the current state of inequality, wealth has the potential for examining accumulated and historically structured inequality. This presentation documents the extent of gender inequality in wealth for Canadian women and men aged 45 and older. The analysis uses data from the 1999 Canadian Survey of Financial Security, a large nationally representative survey of household wealth in Canada. Wealth is measured by total net worth as measured by total assets minus debt. We test two general hypotheses to account for gender differences in wealth. The differential exposure hypothesis suggests that women report less wealth accumulation because of their reduced access to the material and social conditions of life that foster economic security. The differential vulnerability hypothesis suggests that women report lower levels of wealth because they receive differential returns to material and social conditions of their lives. Support is found for both hypotheses. Much of the gender differences in wealth can be explained by the gendering of work and family roles that restricts women's ability to build up assets over the life course. But beyond this, there are significant gender interaction effects that indicate that women are further penalized by their returns to participation in family life, their health and where they live. When women do work, net of other factors, they are better able to accumulate wealth than their male counterparts.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.012
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.270
Teacher spread0.250 · 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