Examining the relationship between perfectionism and trait anger in competitive sport
Bibliographic record
Abstract
The purpose of this study was to examine the relationship between athletes’ perfectionist orientations and their dispositional tendencies to experience anger in sport. A sample of 138 male teenage high‐performance Canadian Football players (M age = 18.27 years, SD = .71) completed multidimensional domain‐specific measures of perfectionism and anger in sport. Canonical correlation (R C) results revealed a profile of maladaptive perfectionism (i.e., high personal standards combined with high concern over mistakes and high perceived coach pressure) that was significantly correlated with competitive trait anger (R C = .56) and the tendency to experience anger when playing poorly (R C = .47). That is, as athletes’ levels on three perfectionism dimensions increased (i.e., personal standards, concern over mistakes, and perceived coach pressure), so did their dispositional tendencies to experience anger in sport. The benefits of conceptualizing perfectionism as a domain‐specific construct, and the importance of considering all dimensions of perfectionism simultaneously when examining the functional nature of the construct in sport are discussed
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".