A Guide to Conducting Systematic Reviews of Coaching Science Research
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
Research in coaching science continues to grow and as such, there is a need for rigorous tools to help make sense of the rapidly expanding literature. The purpose of this paper is to provide a detailed description of a systematic review methodology that can be used to summarise literature in coaching science. To do so, we present a test case of a systematic review we conducted on the sport coaching experiences of global Indigenous populations. More precisely, we conducted a systematic review of English, Spanish, French, Mandarin, and Portuguese peer-reviewed journal articles, spanning twelve databases (e.g., Sport Discus, ERIC, and Scopus) from 1970 to 2014. ENTREQ and COREQ guidelines were followed to report the results of the systematic review, and Bronfenbrenner’s ecological systems theory was used as a theoretical framework to extract and synthesise relevant findings from the included articles. In sum, this paper presents a robust methodology for systematically reviewing research in coaching science and provides practical insights for those who endeavour to conduct rigorous literature searches in this domain.
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.
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 | 0.026 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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