The Role of Growth and Maturation During Adolescence on Team Selection and Short-Term Sports Participation
Bibliographic record
Abstract
Older (born in a month at the start of the team selection year; termed relative age (RA)), more mature adolescent athletes are more likely to be selected onto youth teams. However, little is known as to whether selection onto a team influences an individual’s short-term sports participation. PURPOSE: (i) to investigate the relationship of RA, anthropometrics, and maturity on team selection and (ii) the short-term (3 years) consequence of selection on sports participation. METHODS: 851 participants were recruited from six bantam team sport try-outs: soccer, football, basketball, volleyball, baseball and hockey. Parental heights, date of birth, date of test, height, sitting height and weight were recorded and age at peak height velocity (APHV) and final adult height predicted. Athletes were placed in month quartiles for month of birth.Reference standards were used to create z-scores. Sports participation was recorded at try outs and at 3 year follow-up. Analysis included chi-squared and ANOVA. RESULTS: The sample showed an over representation of the first and second birth month quartiles (p < 0.05). Z-scores for height ranged from 0.1 (1.1) to 1.8 (1.2) and were significantly different between sports (p<0.05). Some height and APHV differences were found between selected and non-selected athletes (p < 0.05). 4% of non-selected athletes dropped out of all sport participation. 84% of selected athletes were still in the same sport compared to 68% of athletes still in the same sport but who were not selected. DISCUSSION: In general athletes at try-out were already taller than the general population, in some sports were maturing earlier, and were born early in the selection year. If not selected a large percentage changed sports. Coaches should be aware of the consequences of selecting the oldest, tallest and more mature athletes on continued sports participation.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".