Teacher stress and burnout in Australia: examining the role of intrapersonal and environmental factors
Bibliographic record
Abstract
Concerns regarding high rates of teacher stress and burnout are present globally. Yet there is limited current data regarding the severity of stress, or the role of intrapersonal and environmental factors in relation to teacher stress and burnout within the Australian context. The present study, conducted over an 18-month period, prior to the COVID pandemic, surveyed 749 Australian teachers to explore their experience of work-related stress and burnout; differences in stress and burnout across different demographic groups within the profession; as well as the contributing role of intrapersonal and environmental factors, particularly, emotion regulation, subjective well-being, and workload. Results showed over half of the sample reported being very or extremely stressed and were considering leaving the profession, with early career teachers, primary teachers, and teachers working in rural and remote areas reporting the highest stress and burnout levels. Conditional process analyses highlighted the importance of emotion regulation, workload and subjective well-being in the development of teacher stress and some forms of burnout. Implications for educational practice are discussed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".