Sustainable Leadership Development Strategies of School Administrators under the Secondary Educational Service Area Office Nakhon Phanom
Bibliographic record
Abstract
The objectives of this mixed-method study were to develop strategies for sustainable leadership of school administrators under the Secondary Educational Service Area Office Nakhon Phanom. There were 4 research methods: phase I) identify the components of sustainable leadership of school administrators by interviewing 5 experts and confirming factors by 5 experts, phase II) develop strategies for sustainable leadership in a focus group including 7 people, phase III) validate the appropriateness, feasibility and utility of sustainable leadership development by collected of data which comprised 84 school administrators using multi-stage random sampling, and phase IV) produce a user manual of strategies by 5 experts for validate the appropriateness of user manual. The findings were as follows: I) There were four main components in the sustainable leadership of school administrators, namely 1) depth 2) breadth 3) vision, and 4) media literacy. All of the components have appropriateness at the highest level and feasibility at the high. II) The strategies for the development of sustainable leadership of school administrators comprised a vision, 6 missions, 6 objectives, 7 strategies, 61 operational approaches, and 25 indicators. III) The appropriateness, feasibility, and utility of the strategies for the development of sustainable leadership of school administrators were at the highest level. IV) The user manual of the strategies for the development of sustainable leadership of school administrators obtained the overall appropriateness at the highest level.
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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 | 0.005 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".