СРАВНЕНИЕ РАЗВИТИЯ МЕНТАЛЬНЫХ НАВЫКОВ У СТУДЕНТОВ-СПОРТСМЕНОВ ИНДИВИДУАЛЬНЫХ И КОМАНДНЫХ ВИДОВ СПОРТА
Bibliographic record
Abstract
The purpose of the study was to compare the mental skills of student-athletes based on their involvement in individual and team sports. The research sample consisted of student-athletes with more than 5 years of sports experience and qualifications ranging from the first adult category to international-class masters. A total of 99 student-athletes participated in the study (54 males engaged in individual sports and 45 engaged in team sports), with a mean age of 20.6 years. Mental skills were assessed using the Ottawa Mental Skills Assessment Tool (OMSAT) adapted by K. A. Bochaver (2020). Comparative analysis revealed that in individual sports, student-athletes demonstrated significantly higher scores in Goal Setting (M = 21.30), Activation (M = 19.00), Relaxation (M = 18.62), Planning (M = 18.70), Focusing (M = 19.05), and Imagery (M = 17.72) compared to student-athletes in team sports. No statistically significant differences were found between the two groups in the following parameters: Commitment, Self-Confidence, Stress Reaction, Fear Control, Distractibility, and Imagery (the ability for visual representation). The obtained data indicate differences in the development of mental skills among student-athletes, which should betaken into account in the process of psychological preparation of athletes.Keywords: mental skills, student-athletes, individual sports, team sports.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".