ELEMENTS IN SCHOOL PRINCIPALSHIP: THE CHANGING ROLE OF PEDAGOGY AND THE GROWING RECOGNITION OF EMOTIONAL LITERACY
Bibliographic record
Abstract
This paper examines the changing role of pedagogy and the growing recognition of emotional literacy as an element in school principalship, as perceived by school principals. A model of the “principal’s toolkit” based on three “pillars” of leadership, management, and pedagogy was used, but with the addition of a fourth pillar, emotional literacy. Here we report on a survey of 63 principals and educational executives that was designed to examine principals’ views regarding which tools are required for school principalship, the way they prioritize those tools, and the weight accorded to each. The survey, which took place from September 2009 to July 2010, was conducted through a questionnaire and interviews. Quantitative processing of the questionnaire results was performed, as was content analysis of the open questions and the interviews. The findings clearly define and rate the components of the essential toolkit for principalship as perceived by the principals. Leadership and emotional literacy were rated highest and pedagogy and management lower, which is at odds with the prevailing attempt by the Israeli Ministry of Education to establish pedagogical leadership as the central element in principalship. This paper will explore and explain the phenomenon of change in principalship elements that entails the changing role of pedagogy and the increasing importance of emotional literacy as an element in school principalship.
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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 | 0.005 | 0.012 |
| 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 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".