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Record W2419896452 · doi:10.1016/s0731-2199(06)17013-2

How much does Obesity Matter? Results from the 2001 Canadian Community Health Survey

2006· article· en· W2419896452 on OpenAlexaffabout
William J. MacMinn, James McIntosh, Caroline Yung

Bibliographic record

VenueAdvances in health economics and health services research · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsStatistics CanadaHealth Canada
Fundersnot available
KeywordsSocioeconomic statusObesityBody mass indexMedicineDiabetes mellitusCommunity healthGerontologyDemographyEnvironmental healthDiseaseHealth equityPublic healthPopulationEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

A five category self-reported health indicator together with the self-reported prevalence of diabetes and heart disease for older Canadians, are examined using data from five cohorts of men and women from the 2001 Canadian Community Health Survey. Consistent with other studies we find that smoking and dietary behaviors are highly correlated with general self-reported health, diabetes, and heart disease. Individual standardized weight, the body mass index, was negatively associated with health outcomes for all age groups, but became less important with age as socioeconomic variables became more important. Socioeconomic variables explained more of the variation in health outcomes than the combined effects of tobacco use and excessive weight problems. In addition, there is compelling evidence that obesity could overtake smoking as the leading cause of health problems in Canada.

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)0.003
metaresearch head score (Gemma)0.011
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 score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.009
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.096
GPT teacher head0.434
Teacher spread0.338 · 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

Citations6
Published2006
Admission routes2
Has abstractyes

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