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Record W2912586145 · doi:10.1177/0022146519827612

Time-use Profiles, Chronic Role Overload, and Women’s Body Weight Trajectories from Middle to Later Life in the Philippines

2019· article· en· W2912586145 on OpenAlexaff
Feinian Chen, Zhiyong Lin, Luoman Bao, Zachary Zimmer, Socorro Gultiano, Judith B. Borja

Bibliographic record

VenueJournal of Health and Social Behavior · 2019
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsMount Saint Vincent University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on AgingNational Institutes of Health
KeywordsBody mass indexDemographyGerontologyMedicineChronic diseaseNational Health and Nutrition Examination SurveyFamily lifePsychologyPopulationInternal medicineSociology

Abstract

fetched live from OpenAlex

Although chronic life strain is often found to be associated with adverse health outcomes, empirical research is lacking on the health implications of persistent role overload that many women around the world are subject to, the so-called double burden of work and family responsibilities. Using data from the Cebu Longitudinal Health and Nutrition Survey (1994-2012), we examined the linkage between time-use profiles and body mass index (BMI) trajectories for Filipino women over an 18-year span. Out of the four classes of women with differential levels of a combination of work and family duties, the group with the heaviest double burden has the highest average BMI. In addition, those who have remained in this class for three or more waves of data not only have higher BMI on average but also have experienced the steepest rate of increase in BMI upon transition from midlife to old age.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.111
Threshold uncertainty score0.220

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.350
Teacher spread0.312 · 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

Citations13
Published2019
Admission routes1
Has abstractyes

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