How Coaches See Conscientiousness-Related Traits and Their Impact on Athletes’ Training and Expertise Development
Bibliographic record
Abstract
Conscientiousness, grit, and self-control are personality characteristics that have been shown to differentially predict several criteria of expertise development, including athletes’ deliberate practice and higher skill levels. However, little is known about coaches’ views on (a) how these conscientiousness-related traits translate into behaviors within the daily training environment or (b) the relevance of these traits for athletes’ quantity and quality of practice and development toward expert levels of performance. To fill these gaps, semistructured open-ended interviews were conducted with 11 high-performance coaches (nine males and two females) of individual and team sports, and national and international competitive levels. The interviews were analyzed using thematic analysis guidelines. The coaches’ descriptions evidenced some overlap between the investigated traits and a partial view of these constructs. They generally believed that grit, conscientiousness, and self-control play critical roles on athletes’ quality of practice and skill development. Notably, the coaches highlighted that tendencies to persevere despite adversity and mindfully use self-regulated processes seem to be powerful predispositions for athletes’ development toward expert performance levels. The results suggested potential mechanisms to help explain the observed relationship between conscientiousness-related traits and athletes’ quality of practice and skill development.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".