Examining the congruency of coaching behaviours in relation to cohesion and performance
Bibliographic record
Abstract
Research with coaches has shown that these individuals influence perceptions of team cohesion (e.g., Jowett & Chaundy, 2004) and affect a team's performance (e.g., Garland & Barry, 1990). However, research has examined these relationships primarily using only the athlete's perspective of their coach's leadership behaviour. Therefore, the purpose of the present study was to examine the congruency between athlete and coach perceptions of the leadership behaviours the coach displays, and its relationship to perceptions of cohesion and performance. Participants were varsity athletes (N = 199) and their coaches. The athletes completed inventories measuring their coach's leadership behaviours (transformational and transactional), cohesion, and performance. The coaches rated themselves on the leadership behaviour inventories. Difference scores were used to determine congruency between athletes and coaches. As such, two groups were created: (a) athletes who under-evaluated and (b) athletes who over-evaluated their coach's leadership behaviours. Results of multi-group path analysis indicated adequate model fit (?2 = 112.98, df = 78, p = .006, CFI =.96, TLI = .90, RMSEA = .05, SRMR = .07). Additionally, 21 significant relationships (p's = .05) were found between specific leadership behaviours and specific dimensions of cohesion and performance. Results are discussed in terms how being an under- or over-evaluator of coaching leadership impacts perceptions of the team environment.Acknowledgments: SSHRC
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".