Preferences and perceptions on coaching behaviors \nin relation to performance in university and CEGEP \nbaseball players across Canada
Bibliographic record
Abstract
This cross-sectional survey study examined the congruence of player preferences and \nperceptions of leader behaviors on athletic performance among university and CEGEP baseball \nathletes across Canada. In accordance with the Multidimensional Model of Leadership, \ncongruence between preferences and perceptions were hypothesized to positively relate to \nindividual baseball performance. The Leadership Scale for Sport was used to measure athlete \nleadership preferences and perceptions of their coach’s leader behaviors across five behavioral \ndimensions (e.g., training and instruction, democratic, autocratic, social support, positive \nfeedback). Paired t-tests examined differences in athlete preferences and perceptions. \nCorrelations were computed to evaluate the relationships between perceived coaching behavior \nand athlete performance. Participants (n = 51) were instructed to complete a self-administered \nsurvey. Athletes were divided into groups based on their designated baseball position (e.g., \nfielder or pitcher). Hierarchical regressions were used to examine the variance in performance \nrelating to the interaction leader preferences and perceptions. The results found a significant \ninteraction effect for social support on performance. Paired samples t-tests revealed differences \nin training and instruction behavior mean score. Perceptions of training and instruction and \npositive feedback behaviors significantly correlated with fielder and pitcher performance, \nrespectively.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".