Teachers' profiles of work engagement and burnout over the course of a school year
Bibliographic record
Abstract
Abstract This research relies on a combination of variable‐ and person‐centered approaches to improve our understanding of the dimensionality of work engagement and burnout. Among 1004 teachers who completed a questionnaire twice over an eight‐month period, our results first revealed that work engagement and burnout ratings simultaneously reflected two global overarching constructs co‐existing with six specific dimensions (vigor, dedication, and absorption as well as emotional exhaustion, cynicism, and professional efficacy). We then examined the profiles taken by these global and specific dimensions, documented their stability and interrelations over time, and tested their associations with theoretically relevant predictors. Three work engagement (Vigorously Engaged, Disengaged, Engaged) and three burnout (Burned‐Out, Adapted, Normative) profiles were identified. Most Disengaged teachers at Time 1 corresponded to the Burned‐Out profile at Time 2, and most Burned‐Out teachers at Time 1 corresponded to the Disengaged profile at Time 2. Workload perceptions increased teachers' likelihood of membership into the Disengaged profile relative to the Engaged one. In contrast, most job resources perceptions (control, rewards, and values) predicted an increased likelihood of membership into the Engaged profile relative to the Disengaged one.
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 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 | 0.000 | 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) | 0.001 | 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 teacher head, 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".