Examination of preschool teachers' compassion and fear of compassion
Bibliographic record
Abstract
This study aims to examine preschool teachers' compassion and fear of compassion. The sample of this survey study consisted of 274 preschool teachers. Personal Information Form, Adult Compassion Scale, and Fear of Compassion Scale were used as data collection tools. Data analysis showed that the compassion level of the preschool teachers was high whereas their fear of compassion level was low. It was also found that the compassion of preschool teachers did not differ significantly based on their gender, age, marital status, educational level, having children, having a pet, having someone to care for at home other than children and their place of residence. Emotional compassion level of preschool teachers who were married and had children was higher than the emotional compassion level of their colleagues who were single and did not have any children. Compassion level of teachers who had 6 to 10 year-professional seniority was significantly higher than their colleagues who had 0 to 5 year-professional seniority. It was found that the fear of compassion level of the preschool teachers did not differ significantly based on their demographic characteristics. Also, a negative significant relationship was found between preschool teachers’ compassion and their fear of compassion. Based on the research findings, it can be suggested that, preschool teachers can be trained on compassion-based activities and compassion can be integrated into daily activities in preschool classrooms. Transfering their knowledege on compassion as a behavior to their classroom activities will help children to take those acts as a role model.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".