Relative Age Effect: Beyond the Youth Phenomenon
Bibliographic record
Abstract
ABSTRACT The relative age effect (RAE) refers to the oversampling of youth born in the first quarter of the birth year when auditioning for selected age-restricted sports. This advantage conferred to the older athlete is the result of the older athlete being more physically and emotionally mature and, therefore, assumed to be a more advanced player. Chosen players will be exposed to better coaching, competition, teammates, and facilities in their respective sport. This RAE was first described in 1988 for ice hockey, and has since been described in numerous other sports, with a vast majority of the literature demonstrating an RAE in small cohorts, as well as in team sports and sports that incorporate a ball (i.e. soccer, basketball, hockey, etc). We extended the exploration of an RAE beyond specific sports by examining the birth quarter of over 44,000 Olympic athletes birth dates, born between 1964 and 1996. Our hypothesis is that not only did an RAE exist in Olympic athletes, but that it existed across selected categories of athletes (by gender), such as team vs individual sports, winter vs summer athletes, and sports using a ball vs those not using a ball. The fractions of births in the first vs the fourth quarter of the year were significantly different (p < 0.001) from each other for the summer and winter Olympians, ball and nonball sports, and team as well as individual sports. This significant difference was not gender specific. We found the general existence of an RAE in Olympic athletes regardless of global classification. Joyner PW, Mallon WJ, Kirkendall DT, Garrett WE Jr. Relative Age Effect: Beyond the Youth Phenomenon. The Duke Orthop J 2013;3(1):74-79.
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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 | 0.011 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".