Participation Motivation in University Students Who Engage in Different Team Sports
Bibliographic record
Abstract
The aim of this study was to examine the motives for university students who engage in different team sportsmutually. The cross-sectional method was used in the study. The study sample consisted of 280 university studentsfrom Dumlupinar University School of Physical Education and Sports. The participants were chosen according tostratified random sampling method and participated in the study voluntarily. In the study in order to collect dataTurkish version of Gill and colleagues’ Sports Participation Questionnaire was used. In the evaluation of the data inaddition to descriptive statistical methods, MANOVA was used as the hypothesis test. According to MANOVAresults, there were significant differences between the motives for university students in achievement, physicalfitness, skills development and movement/being active factors. The findings of this study can assist intercollegiatecoaches and athletic administrators to understand the motivational patterns of university students for participating insports and allow them to develop strategies which can prevent students from quitting sports participation andexercise.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".