SOSYODEMOGRAFİK FAKTÖRLER İLE EMPATİNİN TOPLUMSAL DUYARLILIĞA ETKİSİ: BAYBURT ÜNİVERSİTESİ ADALET MESLEK YÜKSEKOKULU ÖĞRENCİLERİ ÜZERİNE BİR ARAŞTIRMA
Bibliographic record
Abstract
The aim of this study was to analyze the relationship between the social sensitivity and empathy levels of the students studying at Bayburt University Vocational School of Justice. The effect of some sociodemographic factors such as gender, class, department of education on social sensitivity was also analyzed in the study. In accordance with the purpose of the research, the relational survey model was used. 254 students who volunteered to fill out the questionnaire constituted the sample of the research. 118 (46.5%) male and 136 (53.5%) female students studying in different departments at Bayburt University Vocational School of Justice (Justice, social security, office services and administrative assistant, prison and security department) participated in the research. Toronto Empathy Scale and Social Sensitivity Scale were used to collect data. According to the findings, students have high level of empathy and social sensitivity. While gender and education do not affect social sensitivity, social sensitivity increases as the class level increases. There is a positive relationship between empathy and social sensitivity, and empathy. Hence it can be concluded that as the level of empathy increases, social sensitivity also increases
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".