An Attachment Theory Perspective in the Examination of Relational Processes Associated With Coach-Athlete Dyads
Bibliographic record
Abstract
The aim of the current study was to examine actor and partner effects of (a) athletes' and coaches' attachment styles (avoidant and anxious) on the quality of the coach-athlete relationship, and (b) athletes' and coaches' quality of the coach-athlete relationship on relationship satisfaction employing the actor-partner interdependence model (Kenny, Kashy, & Cook, 2006). Coaches (N = 107) and athletes (N = 107) completed a questionnaire related to attachment styles, relationship quality, and relationship satisfaction. Structural equation model analyses revealed (a) actor effects for coaches' and athletes' avoidant attachment styles on their own perception of relationship quality and coaches' and athletes' perception of relationship quality on their own perception of relationship satisfaction, and (b) partner effects for athletes' avoidant attachment style on coaches' perceptions of relationship quality and for coaches' perceptions of relationship quality on athletes' perceptions of relationship satisfaction. The findings highlight that attachments styles can help us understand the processes involved in the formation and maintenance of quality relational bonds between coaches and athletes.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".