The Effect of Temperament on Emotion Regulation among Chinese Adolescents: the Role of Teacher Emotional Empathy
Bibliographic record
Abstract
Hierarchical linear modeling techniques were used to explored individual and contextual factors of emotion regulation in a sample of 2074 adolescents from grade 7 through grade 12 and 54 head teachers in China mainland. Emotion Regulation Questionnaire (ERQ) and Early Adolescent Temperament Questionnaire-Revised (EATQ-R) were administered among students and Multi-Dimensional Emotional Empathy Scale (MDEES) among head teachers. Results showed that at the student level, Effortful Control and Affiliativeness were positively related to adolescents’ reappraisal whereas Surgency was inversely correlated with reappraisal after gender, grade level and parent’s education were controlled. And Negative Affect (NA) positively predicted suppression. At the teacher level, teachers’ Emotional Contagion promoted the impact of adolescent Surgency on reappraisal after teaching age was controlled. In addition, Responsive Crying, Emotional Attention and Feeling for Others enhanced the influence of NA upon Suppression among teachers. However, Positive Sharing weakened the negative association between NA and Suppression. These findings expand the understanding of the role of teacher empathy in adolescents’ emotional development, and have important implications for classroom management and teacher empathy training.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".