Effect of Teachers' Work-Related Burnout on Emotional Empathy at the Higher Education Level
Bibliographic record
Abstract
Teachers’ burnout is a contributing factor to many teachers leaving the field of education early in their careers and emotional empathy is also related to teachers’ burnout. The factors of emotional empathy are interpersonal emotional empathy and intrapersonal emotional empathy. The objectives of the study were to examine teachers’ work-related burnout and emotional empathy at higher education levels and to investigate the effect of teachers’ work-related burnout on emotional empathy at higher education levels. The research design is based on causal-comparative. The population of the study includes teachers’ of social sciences and humanities from different public and private universities in Lahore. 100 teachers were selected by using a multi-stage sampling method. Maslach Burnout Inventory (MBI) and Toronto Empathy Questionnaire were used to conduct the study. The results show that teachers’ work-related burnout hurts teachers’ emotional empathy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".