القدرة التنبؤية للذكاء الوجداني في مهارات إدارة الضغوط النفسية لدى طلبة جامعة اليرموك
Bibliographic record
Abstract
This study aimed to reveal the levels of emotional intelligence and stress management skills, as well as to examine the predictive ability of emotional intelligence skills in stress management among Yarmouk University students. The sample consisted of 1,849 male and female students from Yarmouk University, who were selected using a convenience sampling method. The results revealed statistically significant differences in emotional intelligence based on gender, specialization, and academic year. Female students scored higher than male students, and students from the humanities faculties had higher scores than those in the scientific faculties. In terms of academic year, freshmen achieved the highest scores in emotional intelligence. The study also reported no significant differences in the level of stress management skills based on gender. However, statistically significant differences were found in stress management skills due to the variables of faculty and academic year. Students in the humanities faculties had higher scores than their counterparts in the scientific faculties, and freshman students had the highest scores. The results indicated a strong predictive ability of all levels of emotional intelligence and stress management skills, which collectively accounted for 52.1% of the variation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.096 | 0.069 |
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".