Friend, foe, or both? A retrospective exploration of sibling relationships in elite youth sport
Bibliographic record
Abstract
With the abundance of literature focusing on parental influence in sport, it is important to identify family dynamics that extend beyond parents to include siblings. Research indicates that siblings have the potential to influence social, behavioral, and cognitive development across various achievement domains (Brody, 1998). In this study, sibling influence was explored though semi-structured interviews with previously identified elite youth athletes (N=4) and their sibling who participated in the same sport (N=4). Using a grounded theory and retrospective approach, the purpose was to discover how siblings influence elite youth sport participation. After data analysis of the two groups, two main categories emerged from the data: positive experiences participating in the same sport (e.g., growth of sibling relationship, development of understanding between siblings) and negative experiences participating in the same sport (e.g., sibling competition, emotional response). The participants' descriptions coincide with observational learning theory (Mischel, 1966) and both deidentification (Ansbacher & Ansbacher, 1956) and divergence processes (Darwin, 1859; Sulloway, 1996). The data adds to the probable sibling experiences proposed in the Developmental Model of Sport Participation (Fraser-Thomas, Strachan, & Jeffery-Tosoni, 2013) and provides insight and suggestions for athletes, parents, and coaches on how to best manage sibling relations in sport.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".