Grit and perfectionism in intercollegiate athletes
Bibliographic record
Abstract
Understanding personality characteristics that help and/or hinder competitive success in sport is of great interest to many sport psychology researchers. Two such personality characteristics that have been linked to the achievement-striving process in competitive sport are grit and perfectionism. While grit—as conceptualized by Duckworth, Peterson, Matthews, and Kelly (2007)—is largely associated with adaptive characteristics and outcomes in sport, perfectionism has been labeled as a 'dual effect' characteristic (MacNamara & Collins, 2015) that has been linked to both adaptive and maladaptive outcomes/processes in sport. The purpose of this study was to examine previously unexplored relationships between facets of multidimensional grit and multidimensional perfectionism in sport. A sample of 251 intercollegiate student-athletes (M age = 20.34 years, SD = 2.0) completed measures of domain-specific grit and domain-specific perfectionism in sport. Hierarchical regression analyses revealed that (a) separate facets of perfectionistic concerns negatively predicted grit, and (b) separate facets of perfectionistic strivings positively predicted grit in sport. Canonical correlation analysis produced an adaptive profile of perfectionism (i.e., a canonical variate comprising low perfectionistic concerns and high perfectionistic strivings) that was positively correlated (RC = .61, p < .001) with a grit variate comprising moderate consistency of interests and high perseverance of effort. The results not only reinforce the importance of conceptualizing/measuring grit and perfectionism as multidimensional constructs, but also indicate that the combination of high grit, low perfectionistic concerns, and high perfectionistic strivings may form part of a 'positive personality profile' that might assist athletes in the achievement-striving process in sport.
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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) | 0.001 | 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 | 0.001 |
| 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".