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Maternal labour supply and childhood obesity in Canada: evidence from the NLSCY

2008· article· en· W1519778321 on OpenAlexaffvenueabout
Yee Fei Chia

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2008
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOverweightObesityNational Longitudinal SurveysCausality (physics)Childhood obesityWork (physics)Socioeconomic statusDemographyPsychologyEarly childhoodMedicineDevelopmental psychologyChild birthDemographic economicsPediatricsEnvironmental healthEconomicsPregnancySociologyPopulation

Abstract

fetched live from OpenAlex

Abstract. This paper investigates the socioeconomic factors affecting childhood overweight and obesity in Canada using data from the National Longitudinal Survey of Children and Youth. In particular, I attempt to address the issue of whether an increase in the mother's work intensity is associated with an increase in the risk of the child's becoming overweight or obese. I also attempt to evaluate the causality of this relationship and the mechanisms that might facilitate this link. The results suggest that an increase in the mother's work intensity when she first returned to work in the period after the child's birth and before the child started school is associated with an increase in the risk of the child's becoming overweight or obese later in childhood. Conditional on the mother returning to work in the period between the child's birth and the start of school for the child, a 10‐hour increase in the number of hours worked per week when the mother first returned to work is associated with an increase in the probability that the child later becomes overweight or obese that is in the range of 2.5 to 4 percentage points.

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)0.005
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 score0.024
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.008
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0010.001
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 head0.067
GPT teacher head0.179
Teacher spread0.111 · 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

Citations47
Published2008
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Economics/Revue canadienne d économiqueSame topicObesity, Physical Activity, DietFrench-language works237,207