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Record W2558832343 · doi:10.1080/14927713.2016.1252939

Impact of casual leisure on serious leisure experiences and identity in a Canadian junior hockey context

2016· article· en· W2558832343 on OpenAlexaffvenueabout
Bradley MacCosham, François Gravelle

Bibliographic record

VenueLeisure/Loisir · 2016
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCasualAmateurPsychologyLeisure activityContext (archaeology)Identification (biology)Leisure studiesField hockeyPerceptionAthletesIce hockeySocial psychologyApplied psychologyAdvertisingPhysical therapyMedicinePolitical scienceTourismPhysical medicine and rehabilitationGeography

Abstract

fetched live from OpenAlex

The purpose of this study was to explore dropout amateur Junior hockey players’ perceived leisure lifestyle when pursuing Junior hockey and how casual leisure influences serious leisure identification and perceived performance. A total of 15 dropout amateur Junior hockey players participated in this study. Each took part in a semi-structured interview. Findings suggested that amateur Junior hockey players perceived their leisure lifestyle as less than optimal prior to dropping out, which had a negative influence on serious leisure identification, performance and perception of hockey. This was mainly because participants over-identified to hockey and neglected other leisure interests, such as casual leisure activities. Furthermore, findings suggested that casual leisure participation could be beneficial towards serious leisure identification and mental and physical performance. This study also highlights the sensitive relationship between some of the characteristics of serious leisure pursuers.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0090.003
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.021
GPT teacher head0.340
Teacher spread0.319 · 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

Citations8
Published2016
Admission routes3
Has abstractyes

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