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Record W2530310014 · doi:10.1080/02701367.2016.1229863

Sport and Recreation Are Associated With Happiness Across Countries

2016· article· en· W2530310014 on OpenAlexaff
Shea M. Balish, Dan Conacher, Lori Dithurbide

Bibliographic record

VenueResearch Quarterly for Exercise and Sport · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHappinessRecreationAssociation (psychology)Social psychologyPsychologyTest (biology)Political scienceLaw

Abstract

fetched live from OpenAlex

PURPOSE: Preliminary findings suggest sport participation is positively associated with happiness. However, it is unknown if this association is universal and how sport compares to other leisure activities in terms of an association with happiness. This study had 3 objectives: (a) to test if sport membership is associated with happiness, (b) to test if this relationship is universal, and (c) to compare sport membership to other leisure activities. METHOD: = 48). The critical variables included measures of membership in different leisure activities (e.g., sport membership) and self-reported happiness. RESULTS: Even when controlling for known covariates such as perceived health, those who report sport/recreation membership are more likely to report being happy compared with non-sport members (OR = 1.38; 95% CI [1.24, 1.53]). Being a member of a sport organization had a greater association with happiness than did being a member of other leisure activities. Follow-up analyses suggested that this association is nearly universal. CONCLUSIONS: This study offers initial evidence that sport membership elicits happiness across many different societies. Although the causal direction remains unclear, this study establishes a positive association between happiness and sport membership. Future research should target the mechanism(s) of this effect, which we hypothesize are meaningful social relations.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.399

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 studies0.0000.000
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 head0.050
GPT teacher head0.386
Teacher spread0.336 · 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

Citations32
Published2016
Admission routes1
Has abstractyes

Explore more

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