The impact of relative age and community size on female ice hockey participation in Ontario
Bibliographic record
Abstract
An athlete's developmental environment has the potential to impact continued participation in sport and ultimate level of achievement. Researchers have suggested that when an athlete is born relative to peers and the size of the community where their sport development occurs may be important. The purpose of this study was to examine the pattern of relative age and rate of participation in communities of varying size in Ontario. Female hockey registration information was provided by the OWHA for the 2010-2011 season (n = 27,881). Given the age group cut-off in hockey of December 31st of a given year, the birthdates were coded in quartiles: Q1-January to March; Q2-April to June; Q3-July to September; Q4-October to December. Population distributions were obtained from Statistics Canada for 2011. A chi-square goodness-of-fit analysis was performed for each population category within an age division to identify relative age patterns. From the chi-square analyses, an over-representation of relatively older players was observed across all age divisions for small, medium, and large population centres (? < 0.05). No relative age differences were observed for rural communities (
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".