Leadership Characteristics of University Students Engaging in Volunteer Activities
Bibliographic record
Abstract
This study aimed to investigate the youth leadership qualities and characteristics of university students who volunteer at the Elazig Youth Center, Turkey. The population of the study consisted of 146 university students, 86 females and 60 males. Youth Leadership Qualities Scale, which was developed by (Cansoy & Turan, 2016), was used as the data collection tool. Within the scope of the study, the Cronbach alpha internal consistency coefficient was determined as 0.91 for the entire youth leadership qualities scale and it was observed that the Cronbach alpha internal consistency coefficients varied between 0.70 and 0.80 calculated for the reliability of the factors. Thus, it was determined that the scale was a valid and reliable measurement tool. In the study, non -parametric tests were used in the data analysis. Additionally, the Mann-Whitney U test was to determine the difference between the groups in binary variables while the Kruskal-Wallis test was used for the variables with more than two groups. In the Kruskal-Wallis test, the MannWhitney U test was used to determine between which groups the difference existed. The analysis of the data was conducted using the licensed SPSS 25 software. In conclusion, it was determined that female students were more reliable in terms of leadership characteristics and their sense of responsibility was higher than male students. Moreover, it was determined that as the age of the students increased, their problem-solving skills also increased. Furthermore, university students who engaged in volunteer activities viewed themselves as successful in the activities they participated in based on youth leadership characteristics.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".