“Exhaustive but effective”: A multi-site study investigating the profiles of teachers' emotions and emotional labor
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Teachers routinely experience and manage a variety of emotions to meet the requirements of their profession. Previous research has primarily focused on how teachers' emotions or their emotional labor affects their well-being and teaching quality. The present study takes a more holistic, person-centered approach to identify groups of teachers with distinct emotional experiences and emotional labor tendencies. In the first study, 474 Canadian secondary school teachers (female: 72.5%) were categorized into three profiles: emotionally healthy deep actors, emotionally healthy surface actors, and emotionally unhealthy surface actors. The emotionally healthy deep actors reported the highest levels of well-being, while the emotionally unhealthy surface actors reported the lowest. The same profiles were observed in Study 2 with 85 German secondary school teachers (female: 57.6%). Among these teachers, the emotionally healthy surface actors were rated by students as the most supportive ( N students = 1327). Conversely, the emotionally unhealthy surface actors received the least favorable student ratings of teaching quality (cognitive activation, classroom management, student support). In conclusion, our study indicates that emotional labor, specifically surface acting, has a double-edged function, with both positive and negative implications. On the one hand, it is linked to diminished well-being among teachers, while on the other hand, it has the potential to enhance students' perceptions of teacher support.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it