THE INFLUENCE OF SOCIAL SUPPORT AND SPIRITUALITY WITH QUARTER LIFE CRISIS IN PRISONERS
Bibliographic record
Abstract
Objective: This research aims to determine the relationship between emotional intelligence and self-control in high school/vocational school students who are members of the Youth Information and Counseling Center (PIK-R) organization. Method: This research uses a quantitative approach with a correlational survey design. The research sample consisted of 228 students aged 15-18 years who were active in PIK-R in the last 6 months. The sampling used is purposive sampling. Data was collected using two measurement scales, namely the Emotional Intelligence scale consisting of 30 items with a reliability (α) of 0.813, and the Self-Control Scale consisting of 30 items with a reliability (α) of 0.748. Data analysis was carried out by Spearman's Rho correlation test using SPSS software version 25. Results: The results of the research showed a significant correlation between Self-Control and Emotional Intelligence of High School/Vocational High School Students with PIK-R (r=0.724*** p0.724). There were results that emotional intelligence had an effective contribution to self-control of R2 = 0.525, suggesting that emotional intelligence explained 52.5% of the self-control variance. Novelty: This research aims to determine the relationship between emotional intelligence and self-control in high school/vocational school students who are members of the Youth Information and Counseling Center (PIK-R) organization.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".