An Exploratory Examination of Interpersonal Interactions between Peers in Informal Sport Play Contexts
Bibliographic record
Abstract
Athlete-driven informal sport play represents an important context for athlete development. However, in contrast to coach-driven organized sport, little is known about the interpersonal processes driving development in this context. The present study was an exploratory descriptive analysis of the interactive peer behaviors occurring in an informal sport play setting and their relationship to athlete psychological characteristics. Thirty young athletes (<25 years old, Mage = 19.84) participating in informal mixed-age volleyball, soccer, and basketball sessions at a community recreation center were observed and their interactive behavior coded. Participants also completed questionnaire measures of psychological characteristics (competence, confidence, character). Descriptive analyses examined the interaction patterns of young athletes in these contexts. Multiple regression analyses were then conducted to examine the relationships between peer interactive behavior and athlete psychological characteristics. Results point to the social nature of participation in informal sport play contexts and the critical relationship between athlete competence and peer interaction tendencies. This study presents an initial exploration of peer interactive behavior in informal, mixed-age sport play contexts, but continued future research is needed to better understand the developmental processes and implications of participation in these important contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".