Youth Developmental Experiences Among Female Hockey Players: The Role of Relative Age
Bibliographic record
Abstract
Relative age differences can lead to varying sport participation opportunities; however, scant research has focused on the impact of relative age on experiences within sport. This study explored if youth developmental experiences differed by relative age among competitive female ice hockey players. Players within Ontario (n = 264) completed an online survey that contained the Youth Experience Survey for Sport (YES-S) along with additional demographic questions. The YES-S measures 5 dimensions of positive (i.e., personal and social skills, cognitive skills, goal setting, and initiative) and negative developmental experiences in sport. The results of the multivariate analysis of variance (MANOVA) suggested that the developmental experiences reported by athletes did not differ across birth quartiles (Wilks’ Lambda = 0.940, F (15, 707.105) = 1.061, p = .390). Although there was a relative age effect (RAE) trend within this sample of competitive female ice hockey players, the differences across birth quartiles were not statistically significant. It appears that relative age does not result in youth having different positive and negative sporting experiences. Exploring the characteristics of sport environments (e.g., coaches, practices) and personality traits of competitive athletes to better understand how relatively younger athletes continue their participation in sport despite being at a perceived disadvantage warrants further investigation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".