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Record W4315777590 · doi:10.1186/s12889-023-15011-4

Women suffer but men die: survey data exploring whether this self-reported health paradox is real or an artefact of gender stereotypes

2023· article· en· W4315777590 on OpenAlexafffund
Susan P. Phillips, Madlen O’Connor, Afshin Vafaei

Bibliographic record

VenueBMC Public Health · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsQueen's University
FundersCanadian Institutes of Health Research
KeywordsPsychosocialContext (archaeology)Self-rated healthMedicineMental healthDynamismGerontologyPublic healthBiostatisticsSocial psychologyPsychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Despite consistently reporting poorer health, women universally outlive men. We examine whether gender differences in lived circumstances considered, and meaning attributed to SRH by women and men might explain this paradox. METHODS: In an online survey 917 adults rated their health (SRH) and mental health (SRMH) and reflected upon what life experiences they considered in making their ratings. Descriptive findings were sex-disaggregated. The multiple experiences listed were then subject to factor analyses using principal components methods and orthogonal rotation. RESULTS: Women reported poorer SRH and SRMH. They considered a wider range of circumstances, weighing all but self-confidence and behaviors as more important to SRH than did men. Two underlying components, psychosocial context and clinical status were identified overall. Physical health and pain were more important elements of men's clinical status and behaviors. Comparisons with others of the same age played a larger role in male psycho-social context. Two components also underpinned SRMH. These were clinical problems and psycho-social circumstances for which self-confidence was only important among men. CONCLUSIONS: Women's and men's common interpretation of measures like SRH suggests that women's health disadvantage is neither artefactual nor determined by gendered meanings of measures and does not explain the paradox. SRH and SRMH captured social circumstances for all. Convergence of characteristics women and men consider as central to health is evidence of the dynamism of gender with evolving social norms. The remaining divergence speaks to persisting traditional male stereotypes.

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)0.014
metaresearch head score (Gemma)0.001
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 score0.271
Threshold uncertainty score0.855

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.559
GPT teacher head0.436
Teacher spread0.123 · 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

Citations22
Published2023
Admission routes2
Has abstractyes

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