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Record W3212924546 · doi:10.1123/jsm.2021-0179

Institutional Theory in Sport: A Scoping Review

2021· review· en· W3212924546 on OpenAlexaff
Jonathan Robertson, Mathew Dowling, Marvin Washington, Becca Leopkey, Dana Ellis, Lee Smith

Bibliographic record

VenueJournal of Sport Management · 2021
Typereview
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsLaurentian University
Fundersnot available
KeywordsScholarshipInstitutional theoryLegitimacyIsomorphism (crystallography)SociologyPublic relationsEmpirical researchPolitical sciencePositive economicsSocial scienceEpistemologyLawEconomics

Abstract

fetched live from OpenAlex

Institutional theory has generated considerable insight into fundamental issues within sport. This study seeks to advance Washington and Patterson’s review by providing an empirical review of institutional theory in sport. We follow Arksey and O’Malley’s scoping review protocol to identify 188 sport-related institutional studies between 1979 and 2019. Our review provides evidence regarding the state of institutional scholarship within sport via an analysis of authorship, year, journal, methodology, method, study population, and use of institutional constructs (legitimacy, isomorphism, change, logics, fields, and work). Rather than a hostile takeover or a joint venture proposed in Washington and Patterson’s review, the relationship between fields is more aptly described as a diffusion of ideas. By developing an empirical review of institutional studies in sport, we hope to expedite the diffusion of ideas between the two fields and work toward realizing the collective benefits any future joint venture may bring.

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)0.029
metaresearch head score (Gemma)0.095
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.032
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.095
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0320.030
Science and technology studies0.0020.003
Scholarly communication0.0060.006
Open science0.0020.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.084
GPT teacher head0.425
Teacher spread0.341 · 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 designSystematic review
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

Citations69
Published2021
Admission routes1
Has abstractyes

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