Maturational and social factors contributing to relative age effects in school sports: Data from the London Youth Games
Bibliographic record
Abstract
Few studies have investigated whether relative age effects (RAEs) exist in school sport. None have sought to test the competing maturational and social-agent hypotheses proposed to explain the RAE. We aimed to determine the presence of RAEs in multiple school sports and examine the contribution of maturational and social factors in commonplace school sports. We analyzed birth dates of n=10645 competitors (11-18 years) in the 2013 London Youth Games annual inter-school multisport competition and calculated odds ratio (OR) for students competing based on their yearly birth quarter (Q1-Q4). Multivariate logistic regression was used to determine the relative contribution of constituent year (Grade) and relative age in netball and football which used multiyear age groupings. In girls, RAEs were present in the team sports including hockey, netball, rugby union, cricket and volleyball but not football. In boys, RAEs were stronger in common team sports (football, basketball cricket) as well as athletics and rowing. In netball and football teams with players from two constituent years, birth quarter better-predicted selection than did constituent year. Relatively older players (Q1) from lower constituent years were overrepresented compared with players from Q3 and Q4 of the upper constituent years. RAEs are present in the many sports commonplace in English schools. Selection of relatively older players ahead of chronologically older students born later in the selection year suggests social agents contribute to RAEs in school sports.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".