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Record W1970616962 · doi:10.1007/s11556-009-0054-9

Sport participation and positive development in older persons

2009· article· en· W1970616962 on OpenAlexaff
Joseph Baker, Jessica Fraser‐Thomas, Rylee A. Dionigi, Sean Horton

Bibliographic record

VenueEuropean Review of Aging and Physical Activity · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of WindsorYork University
Fundersnot available
KeywordsContext (archaeology)Affect (linguistics)Positive Youth DevelopmentPsychologyConceptual frameworkGerontologyDevelopmental psychologySociologyMedicineSocial scienceGeography

Abstract

fetched live from OpenAlex

Abstract In many Western countries, more and more people are living longer. As part of this demographic shift, increasing numbers are participating in Masters sport. In the past, sport was considered important for the development of young people; however, the potential for sport participation to affect positive development across the lifespan is now recognized. The purpose of this paper is to introduce conceptual frameworks from developmental psychology that are being used to understand youths’ positive development through sport, and to explore these frameworks in the context of sport as an avenue for positive development in older persons. To achieve this aim, we outline research on sport participation as it applies to youth development and consider relevant aspects as they broadly apply to development later in life. This discussion highlights the inherent paradox of sport participation—that it has the potential to provide considerable positive growth but also the potential for significant negative consequences. Finally, we explore areas of future research related to positive development in older persons through sport.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.026
GPT teacher head0.331
Teacher spread0.305 · 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

Citations122
Published2009
Admission routes1
Has abstractyes

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