Beyond Mindfulness: Principal Preparation Programmes, Professional Learning and Innovative Supports to Promote Effective Emotional Regulation
Bibliographic record
Abstract
Abstract School-level leaders should not be expected to be mired in emotional turmoil and sacrifice their own health, happiness and well-being to do their jobs effectively. While the emotional aspects of school-level leadership have continued to evolve and become increasingly complex since the turn of the twenty-first century, the supports available to these individuals remain outdated, ineffective, and moribund. If mentoring, anonymous telephone support lines and other ‘old school’ approaches for supporting school leaders were still effective, they would not be struggling to deal with the emotional aspects of their work and workload. Further, there is a need to provide ‘just-in-time’ supports that are available to school-level leaders when concerns arise. Absent structural changes, isolated and individualized approaches to self-care cannot mitigate the challenges principals face or the physical, mental and emotional toll associated with their work and workload. Communal strategies and policy levers are recommended in an effort to go beyond mindfulness and other (potentially) individualistic and neoliberal approaches to self-care. This chapter also explores how principal preparation programmes and other formal professional learning opportunities are an untapped resource in terms of strengthening school-level leaders' emotional regulation capacity and building a general appreciation for the emotional aspects of school-level leadership.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".