Positive youth development in sport: Mapping the scientific structure using a citation network analysis
Bibliographic record
Abstract
The systematic analysis of academic publishing and citation practices serves as an indication of the conceptual and intellectual structure of a defined field of study. To highlight the structure of research in sport-based positive youth development (PYD), 198 peer-reviewed qualitative and quantitative empirical research articles (published between 1999 and 2020) were subject to citation network analysis. This analysis used Bibliometrix, an open-source R package that used metadata drawn directly from Web of Science database entries. Descriptive analyses highlighted a steady increase in publication frequency across two decades (annual growth rate = 3.36%), and outlined the most prominent contributors to PYD research as a function of authors, articles, sources, and references. Further, we represent the structure of the field using (a) a co-occurrence network of keywords to illustrate six conceptual themes, (b) a co-citation network, which highlighted three clusters of articles more likely to be cited together, and (c) an authorship network to illustrate the presence of different research silos conducting research in sport-based PYD. In all, this review of publishing and citation practices in sport-based PYD is the first to bring the research together in full to map the emergence of conceptual trends over time as well as the authors, articles, and journals associated with these developments. We conclude the presentation with a series of recommendations that relate to foundational PYD texts, elements of a published manuscript used in bibliometric analysis, and a need for greater conceptual clarity in the field of sport-based PYD research.Acknowledgments: Canada Research Chairs Program
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".