Twenty years of scientific production in sport and exercise psychology journals: A Bibliometric Analysis in Web of Science
Bibliographic record
Abstract
© 2022 Sociedad Revista de Psicologia del Deporte. All rights reserved.The present study analyzed the last twenty years (2001 to 2020) of scientific production in sport and exercise psychology (SEP) journals indexed in Web of Science. Ten journals were selected. Psychology of sport and exercise was the journal with the highest number of articles per year (n = 82). USA was the most productive country (n = 1553). University of Birmingham (n = 195) was the institution most prolific, and Social Sciences and Humanities Research Council of Canada (n = 239)was the funding agency most present. Nikos Ntoumanis (n = 67) was the most prolific author. Physical activity (n = 326) was the keyword with most occurrences. Open access represents 27.24% of articles. We concluded that the majority of journals published in the English language and with no open access. Self-determination theory is a well consolidated theoretical framework in the last twenty years in SEP journals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.104 | 0.115 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".