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Record W2261090427 · doi:10.1016/j.jegh.2015.12.003

Democracy predicts sport and recreation membership: Insights from 52 countries

2016· article· en· W2261090427 on OpenAlexaff
Shea M. Balish

Bibliographic record

VenueJournal of Epidemiology and Global Health · 2016
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsDalhousie University
Fundersnot available
KeywordsRecreationDemocracyInequalityPoliticsWorld Values SurveyPublic healthDemographic economicsDemographyMedicinePolitical sciencePsychologySocial psychologySociologyEconomicsLaw

Abstract

fetched live from OpenAlex

=52). Multiple hierarchal nonlinear Bernoulli models tested: (1) if countries' levels of democracy moderate gender differences in sport and recreation membership; and (2) if democracy is associated with increased sport and recreation membership for both males and females. Countries' level of democracy fully moderated gender differences in sport and recreation membership across countries. Moreover, democracy was positively associated with both male and female membership, even when controlling for individual and country-level covariates. Democratic political regimes may confer health benefits via increased levels of sport and recreation membership, especially for females. Future research should test mediating mechanisms.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.059
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.078
GPT teacher head0.442
Teacher spread0.364 · 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.

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
Published2016
Admission routes1
Has abstractyes

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