RESEARCH ARTICLE Influential Factors on the Relative Age Effect in Alpine Ski Racing
Bibliographic record
Abstract
The relative age effect (RAE), which refers to an over-representation of selected athletes born early in the selection year, was proven to be present in alpine ski racing in all age cate-gories at both national and international levels. However, the influential factors on, or the causal mechanisms of, the RAE are still unknown. Therefore, the aim of the present study was to examine three possible influential factors on the relative age effect in alpine skiing: physical performance, anthropometric characteristics and biological maturational status. The study included the investigation of 282 elite Austrian youth ski racers and 413 non-athletes (comparison group) of the same age (10–13 years) and region. Six physical perfor-mance tests were performed, body mass and height were assessed, and the age at peak height velocity (APHV) was calculated. A significant RAE was present in the ski racers. No differences were shown in the physical performance characteristics or in the calculated APHV between the relative age quarters. These results suggest that ski racers born in the last quarter can counteract the relative age disadvantages if they already present the same level of physical performance and maturational status as those born at the beginning of the year. The height and weight of ski racers born at the beginning of the year were significantly higher compared to the non-athletes, and ski racers born in relative age quarter 1 were taller and heavier compared to the ski racers of the other quarters. This indicates that the anthro-pometric characteristics influence the selection process in alpine ski racing, and that rela-tively older athletes are more likely to be selected if they exhibit advanced anthropometric characteristics.
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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 | 0.001 | 0.000 |
| 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 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".