A longitudinal investigation of teachers’ emotional labor, well-being, and perceived student engagement
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
Despite existing studies on teachers’ emotional labour having been primarily correlational in nature, most researchers to date have assumed teachers’ emotional labour to predict well-being outcomes (e.g. job satisfaction, burnout). Moreover, although it is commonly understood that teachers strategically manipulate their expressions of emotions (e.g. intentional displays of anger or disappointment) as effective classroom management strategies, the predictive relationship between their emotional labour and student engagement lacks empirical investigation. The present short-term longitudinal study addresses these research gaps by evaluating the directionality of relationships between teachers’ emotional labour, psychological well-being, and perceived student engagement in 1,086 Canadian practicing teachers. Structural equation modelling analyses showed both teachers’ well-being and perceived student engagement to directly predict their use of emotional labour strategies rather than vice versa. Further theoretical and pedagogical development implications are discussed.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.004 | 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