A season-long examination of the motivational tone of coach-athlete interactions in youth sport
Bibliographic record
Abstract
Coaches are a primary influences on athletes’ experiences in youth sport (Horn, 2008). However, the motivational tone of coaches’ behaviour has not been directly observed, not has its influence on athlete development been examined. The purpose of this short-term longitudinal study was to examine potential associations between the motivational tone exhibited by competitive youth sport coaches in their individualized interactions with athletes and athletes’ developmental trajectories over the course of a competitive season. 55 coach-athlete dyads from five competitive youth volleyball teams were observed at three time points. Athletes in each dyad completed measures of the 4C’s of athlete development at each time point. Cluster analysis revealed the presence of three distinct clusters based on athletes’ developmental trajectories over the course of the season: 1) high and increasing, 2) low and decreasing, and 3) moderate and maintaining. Profile analysis confirmed the longitudinal trajectories were significantly different between all clusters across all 4C’s. Analysis of dyadic interaction profiles revealed significant differences in interactive behaviour between clusters. Athletes in the low and decreasing cluster experienced significantly more performance-related interaction from their coach with a mastery or controlling motivational tone. Athletes in the high and increasing cluster experienced significantly more non-sport related communication from their coach. The present study on motivational tone lends insight into “how” coaches interact with their athletes and the resulting influence on athlete development. The results suggest that even with typically beneficial motivational tone, the relative amount of interaction in relation to other athletes maybe critical to its effectiveness.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".