Debunking early single sport specialisation and reshaping the youth sport experience: an NBA perspective
Bibliographic record
Abstract
Among many parents and coaches, it is believed that early single sport specialisation is essential for future competitive sport success and, further, that a high level of achievement in youth sports predicts future success. Owing to these misconceptions, youth sport has become focused on results at young ages rather than the overall development process, including physical and psychosocial health and well-being. The emphasis on competitive success in youth sports has been driven by a variety of factors including efforts to make elite travel or club teams, attend exclusive camps or showcase events, secure high school roster spots, garner collegiate scholarships and achieve professional careers. In addition, in the USA, the college recruiting process itself is a significant issue, with those as young as the eighth grade committing to a college programme.1 All of this has led to pressure to begin high-intensity training and single sport specialisation in childhood. As a consequence, many parents and young athletes are concerned that not specialising early will place them at a disadvantage in achieving their sport-related goals. In the sport of basketball, a recent National Collegiate Athletic Association (NCAA) survey found that ∼49% of men and 55% of women at the Division 1 level …
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.014 | 0.020 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".