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Record W2106072119 · doi:10.1123/ssj.29.2.186

Socioeconomic Status and Sport Participation at Different Developmental Stages During Childhood and Youth: Multivariate Analyses Using Canadian National Survey Data

2012· article· en· W2106072119 on OpenAlexaffabout
Philip White, William McTeer

Bibliographic record

VenueSociology of Sport Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsWilfrid Laurier UniversityMcMaster University
Fundersnot available
KeywordsSocioeconomic statusPsychologyContext (archaeology)Promotion (chess)Developmental psychologyMultivariate analysisEarly childhoodPhysical activityLongitudinal studyMultivariate statisticsNational Longitudinal SurveysTest (biology)DemographyPolitical scienceGeographyMedicineSociologyPopulationDemographic economics

Abstract

fetched live from OpenAlex

This study examines the relationship between socioeconomic status (SES) and sport and physical activity involvement at different stages of childhood and adolescence in Canada. From the previous literature on SES and health-related behavior, there was reason to test competing hypotheses on the direction of the predicted relationship. The data employed in our analyses came from Cycle 3 of the National Longitudinal Survey of Children and Youth—1998–1999. Results, after controls, showed that SES was a significant predictor of sport involvement among 6–9 year-olds, but not for 10–15 year-olds. In the younger group, the higher the family SES the more frequent was the involvement. The effects of SES were much stronger for organized sport involvement than for participation in an informal context. The discussion bears on the implications of these findings for later adult physical activity and sport involvement and their ramifications for sport and exercise promotion policy.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.005
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.172
GPT teacher head0.389
Teacher spread0.217 · 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

Citations56
Published2012
Admission routes2
Has abstractyes

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