Bibliographic record
Abstract
Abstract This chapter examines the personal and contextual factors of youth sport that affect sport expertise and developmental outcomes. The developmental model of sport participation (DMSP) is used as a comprehensive framework that outlines different pathways of involvement in sport. Activities and contexts that promote continued sport participation and expert performance are discussed as the building blocks of all effective youth sport programs. This chapter provides evidence that performance in sport, participation, and psychosocial development should be considered as a whole instead of as separate entities by youth sport programmers. Adults in youth sport (i.e., coaches, parents, sport psychologists, administrators) must consider the differing implications of concepts such as deliberate play, deliberate practice, sampling, specialization, and program structure at different stages of an athlete's talent development. Seven postulates are presented regarding important transitions in youth sport and the role that sampling and deliberate play, as opposed to specialization and deliberate practice, can have during childhood in promoting continued participation and elite performance in sport.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".