Place of development and dropout in youth ice hockey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research demonstrates that smaller cities in North America are associated with higher rates of elite talent development in sport compared to larger cities [Côté, J., MacDonald, D. J., Baker, J., & Abernethy, B. (2006). When “where” is more important than “when”: Birthplace and birthdate effects on the achievement of sporting expertise. Journal of Sports Sciences, 10, 1065–1073], but little is known about how the environment of different city sizes affects sport participation and dropout. We analysed participation rates and city sizes of 15,565 Canadian youth ice hockey players between 2004 and 2010. Overall, participation counts were negatively correlated with city size, meaning players from larger cities were more likely to drop out, while players from smaller cities were more likely to remain engaged. More specifically, players from cities with populations greater than 500,000 were 2.88 times more likely to end up as dropout than engaged athletes compared to other city sizes. These findings suggest that sport programmes in smaller cities are more conducive towards promoting prolonged participation in sport. In the discussion, we offer possible explanations for this trend.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it