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Record W1753576769

Parental Work Schedules and Child Obesity

2007· article· en· W1753576769 on OpenAlexaff
James Chowhan, Jennifer M. Stewart

Bibliographic record

VenueSSRN Electronic Journal · 2007
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsCarleton UniversityMcMaster University
Fundersnot available
KeywordsEveningScheduleNational Longitudinal SurveysShift workWork (physics)Work scheduleWork hoursPsychologyDemographic economicsObesityWorking hoursDevelopmental psychologyDemographyEconomicsMedicineLabour economicsSociologyEngineeringPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Increasing female labour force participation has been a major change in the labour market, but there have been other substantial changes, such as the move to a 24-hour economy. Researchers have found that children were more likely to have emotional or behavioural problems when parents worked non-standard hours (Strazdins et al., 2004). We use the Canadia National Longitudinal Survey of Children and Youth (NLSCY) to study this relationship for child weight status. The NLSCY contains information on maternal and paternal work patterns. We can distinguish between regular daytime schedule or shift, regular evening shift, regular night shift, rotating shift (change from days to evenings to nights), split shift, on call, and irregular schedule. The survey also asks whether the parent usually worked weekends. We use various statistical techniques to examine the relationship between parental work schedules and child weight status.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.018
GPT teacher head0.346
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 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

Citations2
Published2007
Admission routes1
Has abstractyes

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