Perceived collective burnout: a multilevel explanation of burnout
Bibliographic record
Abstract
Building up on the socially induced model of burnout and the job demands-resources model, we examine how burnout can transfer without direct contagion or close contact among employees. Based on the social information processing approach and the conservation of resources theory, we propose that perceived collective burnout emerges as an organizational-level construct (employees' shared perceptions about how burned out are their colleagues) and that it predicts individual burnout over and above indicators of demands and resources. Data were gathered during the first term and again during the last term of the academic year among 555 teachers from 100 schools. The core dimensions of burnout, exhaustion, and cynicism were measured at the individual and collective level. Random coefficient models were computed in a lagged effects design. Results showed that perceived collective burnout at Time 1 was a significant predictor of burnout at Time 2 after considering previous levels of burnout, demands (workload, teacher-student ratio, and absenteeism rates), and resources (quality of school facilities). These findings suggest that perceived collective burnout is an important characteristic of the work environment that can be a significant factor in the development of burnout.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".