Relative Age and Positive Youth Development in Youth Sport: Do Developmental Assets Play a Role in Creating Advantage Reversals in Female Soccer?
Bibliographic record
Abstract
Relative age effects (RAEs) are commonly associated with advantages for older athletes. However, a variety of benefits attributed to ‘advantage reversals’ have been observed among relatively younger professional athletes. Considering psychosocial development as a proposed mechanism, the purpose of this study was twofold: (1) To explore an association between developmental assets (i.e., facilitators of positive youth development [PYD]) and RAEs; (2) To assess whether overall developmental asset levels are protective against sport dropout. The Developmental Assets Profile© was distributed to members of a one-year cohort of post-adolescent, female soccer players from Ontario, Canada. The presence of differences between groups of relatively older (H1; n = 64) and younger (H2; n = 57) participants and developmental asset scales were assessed using discriminant analysis. A binary logistic regression was conducted to assess whether overall developmental asset levels are protective against sport dropout, with consideration of relevant factors. Findings suggest that relatively younger, female players score higher in two internal categories: commitment to learning and positive values. The overall developmental asset scores were not found to be protective against dropout. This study provides preliminary, albeit cautious, support that ‘advantage reversals’ may be in part associated with enhanced PYD resulting from developmental sport experiences.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".