Relative Age Effect in Individual Sports. A Systematic Review
Bibliographic record
Abstract
Relative Age Effect (RAE) refers to the influence that month birth could have over the performance of people born in the same year. Most RAE studies indicate that individuals born in the first quartiles of a given year may present biological, physical, cognitive, psychological advantages over those who were born in the last months of the same year. Such variations could affect performance, leading to overestimation of observed results at the evaluation time. Although RAE had become a well-studied phenomenon, few is known about the prevailing studies methodological characteristics, as well as the breakthroughs over the theme, particularly, in individual sports. Thus, this systematic review investigated the state of art of RAE in individual sports. Results reveal RAE was found among athletes of individual sports; most studies described RAE in individual sports, nevertheless, few established relations between RAE and other variables (i.e. anthropometry, technical performance.) besides the quarter of birth. Findings indicate most RAE studies in individual sports focus their methodologies and results on describing athletes’ percentage born in each quartile of the year. Therefore, the theme requires a new approach, focused on the relation of RAE with sports talent identification and athlete development processes in individual sports.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".