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Record W2085256022 · doi:10.1080/14927713.2014.933511

Boozing, brawling, and community building: sport-facilitated community development in a rural Ontario community

2014· article· en· W2085256022 on OpenAlexaffvenueabout
Kyle Rich, Corliss Bean, Zale Apramian

Bibliographic record

VenueLeisure/Loisir · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsNOSM UniversityUniversity of OttawaWestern University
Fundersnot available
KeywordsSocial capitalTournamentSociologyCommunity developmentIdentity (music)Embodied cognitionCommunity organizationCommunity buildingSocial identity theoryPublic relationsLocal communityPolitical scienceSocial scienceSocial groupLaw

Abstract

fetched live from OpenAlex

Sport, and specifically hockey, is discussed extensively in relation to social identity formation and other social outcomes, both positive and negative, within Canadian society. In this article, we utilize a collaborative analysis to examine an autoethnographic account of participation in a rural community hockey tournament and its various social outcomes. Through this analysis, we discuss the construction of social identities, social capital, nostalgia, and heritage and then we explore the tensions that exist between the values made explicit by institutional sporting bodies, such as the Canadian Sport Policy, and the values embodied by the tournament. We discuss how idiosyncratic elements of the tournament generate social outcomes and promote community development, despite violating institutional norms. By revealing the rift between institutional- and community-level values, we highlight a need for more contextual interpretations of rural community sporting events in order to better understand the complex ways in which they may contribute to local culture and community development.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
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 head0.054
GPT teacher head0.311
Teacher spread0.257 · 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.

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

Citations17
Published2014
Admission routes3
Has abstractyes

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