Relative Age Effects in Women's Rugby Union From Developmental Leagues to World Cup Tournaments
Bibliographic record
Abstract
UNLABELLED: Annual age cohort groupings promote relative age effects (RAEs), which often, inadvertently, create participation and attainment biases between relatively older and younger players within the same age cohort. In a globally evolving sport, women's rugby team selection practices may potentially bypass qualified players as a result of maturational differences. PURPOSE: Our study examined the prevalence of RAEs in women's rugby union. METHOD: Player data (age range = 4-21+ years) were gathered from the 2006 and 2010 Rugby World Cups (n = 498) and from Canadian (n = 1,497) and New Zealand (NZ; n = 13,899) developmental rugby leagues. RESULTS: Although no evidence of an RAE was found in the World Cup samples, chi-square analyses identified some typical and atypical patterns of RAEs at the developmental levels (w ≥ .3). Younger developmental groups displayed a typical RAE patterning with a greater representation of older players (Canadian 13-year-olds, w = .58; NZ 4-year-olds, w = .35), whereas older developmental groups displayed an atypical RAE patterning with a greater representation of younger players (Canadian 19-year-olds, w = .58; NZ 17-year-olds, w = .32). Further, a traditional RAE emerged in the Canadian 11- to 15-year-old age group, χ2(3) = 10.92, p < .05, w = .30. CONCLUSION: The lack of homogeneity of traditional RAEs across the sample questions the existence of a single, clear RAE in women's rugby. Some evidence of participation inequalities at the developmental levels suggests that further RAE research in more varied sociocultural contexts may be necessary.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".