Exploring the relationship between the relative age effect and youth development among male house league ice hockey players
Bibliographic record
Abstract
Sport participation provides children with the opportunity to develop physical health, psychosocial, and motor skills (Côté et al., 2007). The outcomes related to sport involvement are broad, and can consist of both positive and negative experiences. One such factor that can influence an athlete's experience in sport is the relative age effect (RAE; Barnsley et al., 1985). Relative age effects are developmental and selective advantages associated with being born earlier in the year relative to a predefined cut-off date. Hockey has become one of the most popular sports among researchers to study RAEs (Cobley et al., 2009), likely due to its cultural significance in many countries (Dixon et al., 2011; Musch & Grondin, 2001). Hockey displays strong evidence of birthdate (dis)advantages in a variety of competitive levels (Barnsley et al., 1985; Barnsley & Thompson, 1985; Chittle et al., 2015). The current study examined if relative age influences youth developmental experiences among male ice hockey players. Male house league ice hockey players completed an on-line survey that solicited their date of birth and responses to the Youth Experience Survey for Sport (MacDonald et al., 2012). Our analysis revealed no RAE among the house league hockey players. The MANOVA results revealed no significant multivariate differences between quartile of birth and the five YES-S dimensions (p = .493). It is reassuring that the experiences of the house league ice hockey players in our sample do not differ in their developmental experiences as a consequence of when they were born throughout the selection year.Acknowledgments: The authors would like to thank the Social Sciences and Humanities Research Council for funding this project.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".