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Record W4404115067 · doi:10.1080/17430437.2024.2424566

Mapping knowledge structures and theme trends in sport diplomacy: a bibliometric analysis

2024· article· en· W4404115067 on OpenAlex
Joonoh Jeong, Weisheng Chiu, Doyeon Won

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSport in Society · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsDiplomacyTheme (computing)BibliometricsSociology of sportSociologyPolitical scienceRegional scienceSocial sciencePoliticsLibrary scienceComputer science

Abstract

fetched live from OpenAlex

This study aims to analyse knowledge structures and thematic trends in sport diplomacy, an increasingly prominent field. Using bibliometric analysis of 331 studies from the Web of Science (WoS) database, this study identified several key themes, including the role of sport in promoting peace and diplomacy, the use of sport as a tool for soft power, and the challenges and opportunities of hosting sport mega-events. The study also identified several knowledge structures, including the relationship between sport and (international) politics, globalization, and the role of sport in cultural diplomacy. These findings provide insights for researchers, policymakers, and practitioners, guiding theory development, interdisciplinary collaboration, and practical applications. In summary, this study contributes to understanding the evolution and current state of sport diplomacy scholarship, fostering continued progress in this dynamic field.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0210.181
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.370
Teacher spread0.331 · 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