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Record W1547930545

Social class, gender, and time use: implications for the social determinants of body weight?

2009· article· en· W1547930545 on OpenAlexaffabout
Lindsay McLaren, Jenny Godley, Ian Adam Smith MacNairn

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsObesitySocial classPsychologySocial positionDemographyGerontologyDemographic economicsSocial psychologySociologyMedicineSocial relationEconomics
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: The social gradient in body weight (for example, obesity) departs from the social gradient in other health outcomes. Innovative approaches are needed to understand the observed patterns. This study examines time-use patterns by indicators of socio-economic position, and considers the implications of variations in time use for the social gradient in weight reported in other studies. DATA AND METHODS: The data are from respondents aged 25 to 64 to Canada's 1986 and 2005 General Social Surveys, which focused on time use. Participation in various activities was examined by sex, and by personal income and education, stratified by sex, in both years. RESULTS: Higher-income men and women were more likely than those of lower income to spend time in paid work, commuting and eating out, and less likely to spend time sleeping. Men and women with higher education were more likely than those with lower education to spend time in physical activity (2005 only) and reading. These time-use patterns plausibly contribute to the social gradient in obesity reported in other Canadian studies. INTERPRETATION: The findings suggest that there is value in looking beyond a narrow range of health behaviours toward broader measures of daily routines to gain insight into the social determinants of weight and health.

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 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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.193
GPT teacher head0.473
Teacher spread0.280 · 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 teacher head, not a consensus.

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

Citations33
Published2009
Admission routes2
Has abstractyes

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