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Record W2979820122 · doi:10.1080/2159676x.2019.1673467

Understanding the experiences in adult introductory sport programmes: a case study of learn-to-curl leagues

2019· article· en· W2979820122 on OpenAlexaffabout
Simon Barrick, Heather Mair

Bibliographic record

VenueQualitative Research in Sport Exercise and Health · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of WaterlooUniversity of Calgary
Fundersnot available
KeywordsLeagueNormativeCurlingPsychologyPublic relationsPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Little is known about the experiences of adults as they try a new sport. In this paper, we present findings from a qualitative case study where we sought to understand the experiences of adults trying the sport of curling in two introductory leagues in a central Canadian city. Findings indicate curling, as experienced by participants in these introductory leagues, can be effective in terms of building community and meeting the diverse needs of adults (e.g. providing opportunities to meet other adults). In particular, we identified the following themes: (1) bridging and expanding social connections; (2) valuing, acquiring, and improving skills; and (3) belonging as a curler? These findings represent primary characteristics that the league participants in this study valued and were searching for. This study builds on the existing adult sport participation literature by engaging Green’s (2005) theory of normative sport development to demonstrate important qualities programmers should consider in designing introductory sport and leisure programs.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.204

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0120.008
Scholarly communication0.0030.003
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.458
GPT teacher head0.578
Teacher spread0.120 · 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 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

Citations6
Published2019
Admission routes2
Has abstractyes

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