Parental influence on sport participation in elite young athletes.
Bibliographic record
Abstract
AIM: To ascertain how talented young British swimmers, gymnasts, tennis and soccer players are introduced to their sport, and to identify how they are encouraged into intensive systematic training. METHODS: Two hundred and eighty-two elite young athletes (aged 8 to 17 yrs) and their parents were interviewed in their homes to identify how and why they started intensive training. RESULTS: Of the 4 sports studied (soccer, gymnastics, tennis, and swimming), parents of swimmers were more likely introduce their children to the sport (70%), while parents of gymnasts (42%) were the least likely to do so. However, in this sports parents played a lesser role in the transition to intensive training (6% and 5%, respectively). Nearly half the soccer players (47%) became involved in the sport because of their own interest, with the majority making the transition to intensive training because of encouragement by a coach (65%). Self-motivation (27%) and parental influence (57%) brought children into tennis with 25% of the young athletes in the sample autonomously deciding to start intensive training. Children from the lower socio-economic classes were underrepresented, and the total number of 1-parent families (5.3%) was considerably less than current British national norms (16.1%). CONCLUSION: In Britain, young athletes' involvement in high level sport is heavily dependent on their parents, with sports clubs and coaches playing an important later role. In the present socio-economic and cultural situation, many talented youngsters with less motivated parents will not undertake sport. Talented youngsters from a poorer economic background will be heavily disadvantaged, especially in sports such as tennis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".