Role of Social Support and Social Interest in Juvenile Delinquency: A Binary Logistic Regression Study from Türkiye
Bibliographic record
Abstract
This study investigated adolescents' involvement in juvenile delinquency in relation to their perceived social support and levels of social interest. Data were collected through face-to-face surveys with 402 adolescents aged 15-17 years in Adana, Türkiye. Among the participants, 118 were classified as having a history of juvenile delinquency, while 284 had no such history. The study utilized two instruments: the Social Relationship Elements Scale, which measures perceived support from family and friends, and the Social Interest Scale, which includes the subdimensions of sense of belonging, coping, helping behavior, and empathic sensitivity. Independent samples t-tests showed that: (1) adolescents involved in delinquency reported significantly lower levels of perceived family and friend support, and (2) non-delinquent adolescents scored higher on empathic sensitivity and helping behavior. Binary logistic regression analyses revealed that (1) higher levels of empathic sensitivity, helping behavior, and family/friend support significantly reduced the likelihood of involvement in delinquency, and (2) paradoxically, a stronger sense of belonging was associated with a higher likelihood of involvement in delinquency. These findings underscore the critical role of social support and social interest in shaping adolescent behavior. In particular, interventions that strengthen familial and friend relationships and promote prosocial tendencies may help prevent juvenile delinquency.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".