Leadership and Culture Climate: Exploring how School Principals Support Teacher Wellbeing
Bibliographic record
Abstract
If a teacher is stressed out, they risk altering their wellbeing and capacity to teach effectively. Inevitably, this can impact lesson delivery and student engagement. This study explores teacher wellbeing in the context of administrative support from school leaders. As an under researched area in the literature, this study hopes to contribute findings on what effective school leaders do to maintain the wellbeing of their staff. Although stress is a personal matter, this study explores occupational stress in the context of factors that are attributed to the workplace of a school. This qualitative research project examines how two elementary school principals manage their school- and most importantly their teachers- to ensure staff are in the right mental state to be effective teachers. Data was collected via a semi-structured interview protocol. Audio recordings of these interviews were transcribed, coded, and analysed. Results of this study suggest that there are two broad methods to maintain teacher wellbeing and a positive school climate. These are: proactive strategies and reactive strategies. The data suggest that proactive strategies, such as authentic communication, building a foundation of culture management and professional development can aid in maintaining teacher wellbeing in their workplace. The data further supports the notion of reactionary measures, where the participants described methods such as internal school support (such as mentorship) and external school support (such as board-level policy).
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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) | 0.000 | 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".