More Drama in School Leadership: Developing Creative and Ethical Capacities in the Next Generation of School Leaders.
Bibliographic record
Abstract
This paper shares the outcomes derived from research conducted with the participants of an interdisciplinary workshop entitled “The Drama in School Leadership” that employs applied drama processes and analysis in order to understand educational ethics. Participants explore high-stakes scenarios in school leadership by taking on roles in scripted cases with an ensemble. Findings from previous research on a similar workshop had shown that these methods help develop a felt or embodied understanding of ethical decision making. The findings generated from data generated from this second, different group of participants indicated new insights about leadership style and some increased facility with actual application of ethical frameworks to cases as a result of these methods. Participants also acknowledged the parallels between creative risk-taking in applied drama and real school leadership. Finally, participants articulated that while there is indeed ambiguity associated with ethical decision making, this approach allowed them to better understand the complex, even paradoxical dynamics between stakeholders in schools.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".