Programs for school principal preparation in East Europe
Bibliographic record
Abstract
Purpose This paper is intended to provide an overview of trends in European education and to offer a framework for considering the elements of school management. Design/methodology/approach This paper reports elements of the planning and implementation of a graduate‐level leadership development initiative in Bulgaria. Findings Several lessons learned were garnered from this project. First, models of leadership development must be adaptable to local organizational and system cultures. Second, international leadership development programs should expose participants to different approaches to learning and promote reflective analysis of the various approaches. Expansion of train‐the‐trainer models should be planned from the beginning of projects and consider status differences between trainers‐of‐trainers and trainees who become trainers. Finally, sustainability must be included in planning. Research limitations/implications The international leadership development program is reported from the perceptions of those who participated in the delivery and in the accreditation process. Others may perceive the program differently. Practical implications Management training needs to be practiced so program participants should have opportunities to practice, receive feedback, and dialogue. Experiential learning is essential. New educational ideas may need long incubation periods in the settings where they are introduced. Originality/value Leadership development program in East Europe are a relatively recent phenomenon and lessons learned will resonate with providers of leadership preparation programs in other settings.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".