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Record W3216336144 · doi:10.3389/fspor.2021.774366

Theorizing Community for Sport Management Research and Practice

2021· review· en· W3216336144 on OpenAlexaff
Kyle Rich, Ramón Spaaij, Laura Misener

Bibliographic record

VenueFrontiers in Sports and Active Living · 2021
Typereview
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsWestern UniversityBrock University
Fundersnot available
KeywordsConceptualizationContext (archaeology)SociologyPoliticsEngineering ethicsFoundation (evidence)Order (exchange)Sport managementResistance (ecology)Public relationsPolitical scienceEngineeringComputer scienceEcologyBusiness

Abstract

fetched live from OpenAlex

Community is a context for much research in sport, sport management, and sport policy, yet relatively few authors explicitly articulate the theoretical frameworks with which they interrogate the concept. In this paper, we draw from communitarian theory and politics in order to contribute to a robust discussion and conceptualization of community in and for sport management research and practice. We provide a synthesis of current sport management and related research in order to highlight contemporary theoretical and methodological approaches to studying community. We distinguish between community as a context, as an outcome, as a site for struggle or resistance, as well as a form of regulation or social control. We then advance a critical communitarian agenda and consider the practical implications and considerations for research and practice. This paper synthesizes current research and establishes a foundation upon which sport management scholars and practitioners might critically reflect on community and deliberatively articulate its implications in both future research and practice.

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)0.024
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.007
Science and technology studies0.0060.062
Scholarly communication0.0130.023
Open science0.0040.012
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.173
GPT teacher head0.475
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations12
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Sports and Active LivingSame topicSport and Mega-Event ImpactsFrench-language works237,207