Citation impact and reach of the IOC sport and exercise medicine consensus statements
Bibliographic record
Abstract
Background: Research evidence is commonly compiled into expert-agreed consensus statements or guidelines, with an increasing trend towards their publication in peer-reviewed journals. Prominent among these has been the publication of several International Olympic Committee (IOC) tatements to help inform sport and exercise medicine (SEM) practice. This study aimed to assess the citation impact and reach of the IOC statements published between 2003 and 2020. Method: Bibliometric analysis focused on identifying core publications (original statement and linked publications) and quantifying their academic citations (number and Field-Weighted Citation Impact (FWCI)) in journal articles up to February 2022. The analysis includes descriptive data on the country of IOC statement authorship affiliations, where they were published and by whom. The extent to which the IOC statements have been cited in the peer-reviewed literature is presented, together with information about the country of authorship of the citing papers as a measure of international academic reach. Results: 29 IOC statements were composed of 61 core publications. The IOC statements have had 9535 citations from 7863 citing publications. Individual FWCI ranged from 1.2 to 24.3 for core publications. The IOC statements were coauthored by multiple authors, mostly affiliated to countries with well-resourced SEM Authors of citing publications reflected the same geographical regions (ie, the USA, Canada, Australia, UK and western Europe.). Conclusion: Disseminating the IOC statements as open access papers in peer-reviewed journals has resulted in strong citation impact. However, this impact is centred on well-resourced academic circles that may not represent the diversity of SEM. Further research is required to identify if, and to what extent, the IOC statements have impacted SEM practice worldwide.
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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 | 0.108 | 0.402 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.081 | 0.071 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".