Athlete Leadership Development in Sport: A Systematic Scoping Review (SPORTDiscus EBSCO).
Bibliographic record
Abstract
Objectives: This is a protocol for a systematic scoping review. The objective of this review is to help identify, clarify and examine the available evidence on athlete leadership development. Introduction: Cross-sectional and experimental research indicates that athlete leaders in sport teams are key drivers of effective team functioning and their teammates well-being. Therefore, in the recent years, researchers have developed and tested several athlete leadership interventions. However, a comprehensive review of these interventions has not yet been conducted and is therefore, the primary goal of the current systematic scoping review. Inclusion criteria: Studies which include athletes engaging in competitive sport whose athlete leadership potential is being developed will be included within this systematic scoping review. Methods: Five key databases including Web of Science Core Collection (SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, BKCI-S, BKCI-SSH, ESCI, CCR-EXPANDED), SportDiscus (via EBSCO), PubMed, Embase and Cochrane Library (CENTRAL and CDSR) will be used to conduct the search. The search will be conducted in May 2021. Filters will be included to limit the search to the English Language. All types of articles (including descriptive, qualitative, quantitative and reviews) will be considered. References will be imported and deduplicated using EndNote (Clarivate Analytics). Titles and abstracts will then be screened by two independent reviewers for assessment against the inclusion criteria for the review. We will also conduct a search for grey literature by (a) conducting a search on 'Open access Theses and Dissertations' and 'ProQuest Theses and Dissertations' (b) using forward and backward snowballing from the final articles that will be included within this review and (c) contacting authors whose papers will be included within the review.
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 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 | 0.071 | 0.106 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.023 | 0.023 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.048 | 0.009 |
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".