The developmental and professional activities of female international soccer players from five high-performing nations
Bibliographic record
Abstract
We study the developmental and professional activities engaged in by 86 female adult soccer players from the senior national teams of Australia, Canada, England, Sweden, and the United States of America. Players completed the Participation History Questionnaire (PHQ) to elicit the amount and type of activities engaged in across their developmental and professional years, including milestones, soccer-specific activity and engagement in other sport activity. Greater specialisation than diversification characterised their childhood developmental activities, including all players starting in soccer in childhood and accumulating more hours in soccer activity than other sports during this period. However, interindividual variation further characterised these childhood activities, with a proportion of players diversifying into other sports and/or soccer play to a greater or lesser degree during childhood when compared to the other players. The amount of coach-led soccer practice increased for all players across their development culminating in an average of 15–16 h/wk across a 40-week season in early adulthood. In contrast, the amount of engagement in other sports and soccer peer-led play varied between players but generally decreased across adolescence to negligible amounts in late adolescence. Findings are commensurate with the deliberate practice framework and early engagement.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".