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Record W2047757997 · doi:10.1007/s13524-012-0096-x

Widowhood and Mortality: A Meta-Analysis and Meta-Regression

2012· review· en· W2047757997 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.

Bibliographic record

VenueDemography · 2012
Typereview
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsMcGill University
FundersNational Heart, Lung, and Blood InstituteNational Institutes of Health
KeywordsDemographyConfidence intervalMeta-analysisHazard ratioCovariateMedicineRegression analysisMeta-regressionProportional hazards modelGerontologyStatisticsInternal medicine

Abstract

fetched live from OpenAlex

The study of spousal bereavement and mortality has long been a major topic of interest for social scientists, but much remains unknown with respect to important moderating factors, such as age, follow-up duration, and geographic region. The present study examines these factors using meta-analysis. Keyword searches were conducted in multiple electronic databases, supplemented by extensive iterative hand searches. We extracted 1,377 mortality risk estimates from 123 publications, providing data on more than 500 million persons. Compared with married people, widowers had a mean hazard ratio (HR) of 1.23 (95% confidence interval (CI), 1.19-1.28) among HRs adjusted for age and additional covariates and a high subjective quality score. The mean HR was higher for men (HR, 1.27; 95% CI, 1.19-1.35) than for women (HR, 1.15; 95% CI, 1.08-1.22). A significant interaction effect was found between gender and mean age, with HRs decreasing more rapidly for men than for women as age increased. Other significant predictors of HR magnitude included sample size, geographic region, level of statistical adjustment, and study quality.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.440
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.252
GPT teacher head0.450
Teacher spread0.198 · 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