How do parents find ways to support their children's involvement in sport?
Bibliographic record
Abstract
Research consistently highlights the support parents provide to children in sport. However, we know little about what parents do that enables them to provide such support. Understanding how parents are able to support their children is necessary to ensure coaches, organizations, and practitioners can help parents support their child's sporting endeavours. Thus, the purpose of this study was to identify how parents are able to support their children in sport. Semi-structured interviews were conducted with 42 parents of regional and national adolescent tennis players. The interviews were transcribed and subjected to inductive content analysis. Data analysis revealed four ways parents were able to support their children. Participants worked with their spouse to discuss decisions regarding player progression and share tennis-related tasks. Participants turned to other parents for information regarding coaching and tournaments, and to share the tennis experience. Coaches were expected to do more than just coach the players. Coaches were required to provide information to parents regarding all aspects of tennis and to be a source of emotional support. Finally, parents sought out information regarding tennis development from external sources. These findings indicate that parents seek out information and emotional support from a variety of sources. Sports organizations, coaches, and practitioners can help parents by facilitating opportunities to meet other parents, ensuring extensive and detailed resources are developed for parents, and ensuring coaches are educated in all aspects of youth sport. By enhancing the support for parents, parents will be better able to support their children.Acknowledgments: This research was funded in part by a research grant from the International Tennis Federation
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".