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Record W4385283054 · doi:10.11591/ijere.v12i3.22922

Bibliometric analysis of leadership and physical education based on Scopus data

2023· article· en· W4385283054 on OpenAlexaboutno aff
Novri Gazali, Norazlinda Saad

Bibliographic record

VenueInternational Journal of Evaluation and Research in Education (IJERE) · 2023
Typearticle
Languageen
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsnot available
FundersUniversiti Teknologi MARAUniversitas Islam RiauUniversiti Utara Malaysia
KeywordsScopusTransformational leadershipCurriculumPhysical educationPublicationEducational leadershipPsychologyMedical educationPolitical sciencePedagogyMEDLINEMedicineSocial psychology

Abstract

fetched live from OpenAlex

This paper aims to conduct a bibliometric analysis of articles published in the Scopus database on leadership and physical education. The bibliographic data set was administered using VOSviewer. According to the search results, there were a combined 614 articles on leadership and physical education studies. Additionally, the researchers restricted the search to English-language journal articles and the types of documents that may be found. Consequently, 427 articles worth of records were discovered. Based on publications in the Scopus database, the findings revealed that the development of publications in the fields of leadership and physical education has increased, although there is an up-and-down trend from year to year; “quest” became the first choice among other publication media to publish research results; Beauchamp from Canada is the most contributing and influential author on this topic; physical education, physical activity, leadership, curriculum, transformational leadership, adolescents, health, sport, professional development, and education are keywords that frequently feature in those. Therefore, by highlighting specific gaps, a thorough analysis of leadership in physical education might help scholars and practitioners advance current understanding in this 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.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.022
metaresearch head score (Gemma)0.147
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.147
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.3020.332
Science and technology studies0.0020.001
Scholarly communication0.0090.005
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.613
GPT teacher head0.689
Teacher spread0.077 · 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

Labeled directly by 2 models reading the full record.

Bibliometrics

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Other design
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

Citations7
Published2023
Admission routes1
Has abstractyes

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Same venueInternational Journal of Evaluation and Research in Education (IJERE)Same topicSports and Physical Education ResearchCategoryBibliometricsFrench-language works237,207