Bibliometric analysis of scientific publications in the field of “inclusion in sports non-formal education” in the Web of Science Core Collection database
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.
Bibliographic record
Abstract
Objective. To substantiate the identity of the national and international terminology on “out-of-school education” and to analyze bibliometric data in the Web of Science Core Collection database to define the research field of “inclusion in non-formal sports education”. Methods. Analysis of scientific and methodological literature and Internet materials; documentary sources; synthesis and generalization; combination of bibliometric methods. Results. The use of the terms “non-formal education” and “sports non-formal education” and their coherence with the terms “out-of-school education” and “health-enhancing physical activity in out-ofschool education institutions” are explained for the relevance of the results of the bibliometricanalysis of scientific publications. A total of 2208 publications from the Web of Science Core Collection database related to inclusion in non-formal sports education were reviewed for the period from 2015 to 27.02.2024 by country, university, and author. Four combinations of words with a logical operator were used – “inclusion” AND “sport” OR “inclusion in sport” AND “nonformal education”. Publications were clustered by keywords and research topics. The analysis of Ukrainian regulatory and legislative texts regulating the functioning of out-of-school education and international educational legislation revealed the identity of the use of the terms “physical education and sports work in out-of-school education institutions” and “non-formal education in sports” for scientific research. The conducted bibliometric analysis of publications in the field of “inclusion in non-formal sports education” from the Web of Science Core Collection database (2015-2024) confirmed the stable and growing interest of scientists in the studied problem. The distribution of publications by countries/regions (the USA, the UK, Spain, Australia, Canada) correlates with the distribution of publications by scientific institutions and leading and most cited authors. The clustering of publications allowed us to identify five clusters that outline the research topics. It was found that the most cited publications within the sample were those published between 2014 and 2018. Keywords: inclusiveness, sports, non-formal education, bibliometrics, mapping, profiling.
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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 arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.024 | 0.124 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it