Examining the Relationship between Empathy and Subjective Well-Being among University Students
Bibliographic record
Abstract
Empathy is an important aspect of understanding socialization and human nature.Past studies also showed that research findings on empathy are inconsistent in explaining the relationship between empathy and subjective well-being.Hence, this study examines the relationship between empathy and subjective well-being among university students.A total of 272 students were selected as participants, which was retrieved using convenient sampling.Toronto Empathy Questionnaires and the Malaysian version of the Personal Well-Being Index (PWI) were used to measure empathy and subjective well-being.A cross-sectional descriptive correlational design was used in the present study.Statistical Package of Social Sciences (SPSS) is software for data management that is used in analyzing data using descriptive and inferential statistical analysis.The results of the analysis found that there is a significant positive relationship between empathy and subjective well-being score (r = .18,p<.003).The results of the present study verify that empathy is related to the subjective wellbeing of a university student.Future studies have suggested focusing on the influence of empathy on subjective well-being from a larger perspective involves many domains.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".