Examining the associations between grit, self-control and sport expertise: A replication study
Bibliographic record
Abstract
To develop expertise, athletes need to amass a high volume of deliberate practice activities over a long duration. Two personality traits that relate to long-term goal pursuits and to achievement within sport are self-control (Tedesqui & Young, 2017a) and grit (Tedesqui & Young, 2017b). We compared the contribution of grit and self-control facets to explain criteria of sport expertise development. Athletes (n = 164, 87 female, Mage = 31.62, SD = 12.45) completed survey items assessing grit (perseverance of effort; consistency of interests) and self-control (self-discipline; impulse control), questions to determine skill group (beginner/intermediate; advanced; expert), and sport-specific practice amounts. We submitted all scale scores to criterion validity tests for group discrimination and associations with practice. Separate MANCOVAs for grit and self-control variables (controlling for age) showed grit variables significantly distinguished higher from lower skill groups, Pillai's Trace = .06, F(4, 314) = 2.48, p < .05, partial eta-squared = .03. Post-hoc tests showed only perseverance of effort distinguished groups, F(2, 157) = 5.08, p < .01, partial eta-squared = .06 (Mbeginner/intermediate = 4.37, Madvanced = 4.25, Mexpert = 4.58). Although we replicated prior effects of perseverance of effort on skill groups, we failed to replicate any associations with practice. The tendency to persevere in long-term goals despite setbacks might enable athletes to achieve higher skill levels in pursuit of expertise development. We problematize the non-significant findings regarding practice.Acknowledgments: This research was supported by a Social Sciences and Humanities Research Council of Canada (SSHRC) funding (430-215-00904) to Bradley W. Young and Joseph Baker.
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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 | 0.002 | 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 | 0.001 | 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".