The Correlation Between Empathy and Perceived Social Support in a College Student Population
Bibliographic record
Abstract
A positive perception of social support and high empathy have been shown together previously to produce better outcomes for college students. The aim of the present study was to further expand on this research and examine whether a relationship exists between perceived social support and empathy in a college student population. The study hypothesised a positive correlation between empathy and perceived social support, a gender difference in empathy level, and a difference in empathy and social support between different college courses. 81 college students completed demographic information, the Interpersonal Support Evaluation List-12, and the Toronto Empathy Questionnaire. Although a small, positive relationship was found, Pearson’s Correlation showed the correlation between empathy and perceived social support was non-significant (p = .306). Further analysis from a t-test and one-way ANOVA found significant differences between male (M = 48.97, SD = 6.09) and female (M = 52.61, SD = 5.45; p = .007) empathy scores, and college course (p = .002) in total empathy level. No significant differences were found for perceived social support between courses (p = .584). Findings suggest that empathy is important for college students. Development of empathy may be necessary to help students maintain positive perceptions of social support.
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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 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".