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Record W1980356378 · doi:10.1300/j013v38n01_01

Age and the Gender Gap in Distress

2003· article· en· W1980356378 on OpenAlexaffabout
Peggy McDonough, Lisa Strohschein

Bibliographic record

VenueWomen & Health · 2003
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDistressDisadvantagedDisadvantagePsychologyContext (archaeology)Vulnerability (computing)GerontologyDemographyPopulationDevelopmental psychologyClinical psychologyMedicineSociologyPolitical scienceGeography

Abstract

fetched live from OpenAlex

Women report more psychological distress than men and recent evidence suggests that this gap increases with age. It has been argued that the widening differential in distress reflects the progressive and cumulative nature of women's disadvantaged work and family roles. Drawing on the cumulative disadvantage hypothesis and social stress theory, we test: (1) whether exposure to chronic stress accounts for an increasingly larger proportion of the gender effect on distress with age; and (2) whether women are increasingly more vulnerable to the effects of chronic stress on distress with age. Data are from the 1994 wave of the Canadian National Population Health Survey, a national probability sample of women and men aged 20 and older (N = 13,798). Exposure to long-term stress helps us understand gender differences in distress for those in their pre-retirement years. However, contrary to the cumulative disadvantage hypothesis, the model became increasingly less likely to explain such differences with age. Gendered vulnerability to long-term stress was not evident in the sample. The implications of these findings are discussed with particular reference to our ongoing efforts to understand health in the context of social structure and subjectivity.

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 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)0.002
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 score0.337
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.089
GPT teacher head0.417
Teacher spread0.328 · 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 teacher head, 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

Citations26
Published2003
Admission routes2
Has abstractyes

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