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Resistance and Empowerment through Leisure: The Meaning of Competitive Sport Participation to Older Adults

2002· article· en· W1986209775 on OpenAlexvenueno aff
Rylee A. Dionigi

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsEmpowermentContext (archaeology)Meaning (existential)Competitor analysisThematic analysisPsychologyQualitative researchResistance (ecology)AthletesSocial psychologyInterpersonal communicationPopulationSociologyGender studiesSocial sciencePolitical scienceMedicineMarketingGeography

Abstract

fetched live from OpenAlex

It is well established that the developed world’s population is aging. This trend has influenced increased scholarly and media interest into the benefits of leisure, sport and physical activity in later life, as well as an explosion of sporting events for mature athletes. However, the lack of qualitative research pertaining to older peoples’ experiences in competitive sport is surprising. The purpose of this article is twofold: first, to present the qualitative findings of a study that explores the meaning of competitive sport participation to a group of older adults, and second, to examine their meanings within a broader socio-cultural context. Data were collected through participant-observation and semi-structured interviews with competitors (aged 55 to 94 years) at the 8th Australian Masters Games in 20013. The findings were analyzed using strategies consistent with both constant comparative and thematic analyses. The three major themes emerging from the data suggest that competitive sport provides a leisure context for older people to resist the negative factors associated with older age at the individual, interpersonal or shared level, and gain a sense of personal empowerment, regardless of their motive for participation.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.505

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 studies0.0010.000
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 head0.032
GPT teacher head0.334
Teacher spread0.302 · 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 designQualitative
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

Citations47
Published2002
Admission routes1
Has abstractyes

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