Bibliographic record
Abstract
In sport, deliberate practice theory has significantly impacted research on expertise and what has been known as talent/skill development. A wealth of data shows how practice volume distinguishes across groups that vary in their level of skill attained. This theory has led to models of skill development which vary in their emphasis on early or late engagement in deliberate practice and early engagement in play and diversified sport involvement as compared to practice. Deliberate practice theory has been widely studied in dynamic team sports, such as soccer. Here we review research from work we have conducted over the past six years, based on comparisons of highly elite male and female soccer players. We have evaluated prospectively and cross-sectionally, the developmental activities most related to successful transitions and adult success at the highest level of sport, as well as relations between these activities and technical and tactical skills development and indices of motivation. Our data show that successful, adult elite athletes, in the UK and Canada, are defined by what is termed the early engagement pathway. This is characterized by majority engagement in the chosen sport since early childhood, although not exclusive engagement, and engagement in relatively high volumes of self-directed play, in addition to high volumes of more formal, structured practice. We discuss issues with some of this research, including those related to measurement, and present ideas for future research based against the backdrop of the deliberate practice framework.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".