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Record W7104278896 · doi:10.25957/mq38-a911

The state of youth sport research: A systematic review of reviews to identify research themes, trends, gaps, and future directions

2025· article· en· W7104278896 on OpenAlexaff

Bibliographic record

VenueFlinders University Library Research Data · 2025
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsQueen's University
Fundersnot available
KeywordsState (computer science)Systematic reviewGovernment (linguistics)AthletesKey (lock)

Abstract

fetched live from OpenAlex

Youth sport is a dynamic and multifaceted field, encompassing diverse topics such as participation, retention, coaching, talent development, mental health, and wellbeing. While numerous systematic reviews have synthesised evidence on specific aspects of youth sport, the growing volume of these reviews has created a fragmented knowledge base. A systematic review of reviews is needed to consolidate existing evidence, identify overarching patterns, and highlight gaps in knowledge. This approach provides a comprehensive, high-level synthesis that can guide national sport policy, improve practice, and determine future research priorities. This is particularly important in youth sport, where evidence-based interventions can have profound impacts on young people’s physical health, mental wellbeing, and lifelong engagement in sport and physical activity. By streamlining and evaluating the current evidence landscape, this review will offer clear, consolidated guidance for coaches, practitioners, policymakers, and researchers working to optimise youth sport environments and outcomes.

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 imitation

Not 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.

metaresearch head score (Codex)0.085
metaresearch head score (Gemma)0.282
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.915
Threshold uncertainty score0.451

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0850.282
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0130.011
Bibliometrics0.0300.034
Science and technology studies0.0020.003
Scholarly communication0.0100.008
Open science0.0030.005
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.199
GPT teacher head0.446
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designSystematic review
DomainMethods
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractno

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