Fifteen years of publishing in English language journals of sport and exercise psychology: authors’ proficiency in English and editorial boards make a difference.
Bibliographic record
Abstract
In this study we investigated the representation of countries and continents in the publication of six English language journals of sport and exercise psychology from 1997 until 2011. We selected all articles (N = 2093) published in the Journal of Sport and Exercise Psychology, The Sport Psychologist , Journal of Applied Sport Psychology, Journal of Sport Behavior, Psychology of Sport and Exercise, and International Journal of Sport and Exercise Psychology during 1997–2011 and all proceedings (N = 2034) in the last four World Congress of Sport Psychology (1997, 2001, 2005, and 2009). Then, we classified them by country and continent where the first author's institution was located. Five English-speaking countries (USA, UK, Canada, Australia, and New Zealand) represented 82% of the total publications in the six journals and 38.5% of congress proceedings. These were followed by five European countries (France, Germany, Greece, Norway, and Belgium) accumulating 10% of the total publications. The continents of Asia, Africa, and Latin America represented less than 4% of the publications but 28.2% of congress proceedings. There was a very high correlation between continents' representation in journal editorial boards and journal publications. Reviewers and readers should be aware of systematic errors that might happen in the review process of submitted manuscripts describing studies which have been conducted in non-English-speaking countries but which are eventually rejected in English language journals of sport and exercise psychology.
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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 | 0.044 | 0.168 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
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".