Effects of the Sports on the Personality Traits and the Domains of Creativity
Bibliographic record
Abstract
The present study investigated the correlation between the personality traits of the university students who wereengaged in sports and the ones who were not engaged in sports, and their domains of creativity. A total number of593 students studying in the faculty of sports sciences and in other departments were included the study. As the datacollection tools, “Revised/Shortened Form Eysenck Personality Questionnaire (EPQ-RS)” and “Kaufman Domainsof Creativity Scale” (K-DOCS) were used in the present study. When the creativity and personality traits of thefemale and male students were compared, it was found out that the neuroticism points of female students were foundto be higher comparing to the male students. While the male students had higher points in in the domains of scholarlycreativity, mechanical/scientific creativity, artistic and psychoticism, the female students were found to have scoredhigher points in the other domains. When the creativity and personality traits of the students who were engaged insports and those of the students who were not engaged in sports were compared, the extroverted characteristics werefound higher and psychoticism characteristics were lower of the individuals engaged in sports, while no differencewas found in other domains. Consequently, it could be said that female students were more neurotic, that theindividuals engaged in sports were more extroverted compared to the ones not engaged in sports, and that malestudents have higher points compared to the female students in the domains of scholarly, mechanical/scientific,artistic and psychoticism.
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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 | 0.000 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".