A Development Model of School Administration Towards the Next Normal
Bibliographic record
Abstract
The objectives of this research were: 1) to investigate the current state and problems of school administration in the new normal to prepare the school for the next normal; 2) to analyze success factors and conditions of school administration towards the next normal; 3) to develop a model for school administration towards the next normal, and 4) to propose policy proposals and practical guidelines for school administration towards the next normal. The research was divided into four phases, as follows: 1) investigate the current state and problems in the new normal by using an in-depth interview with 29 administrators; 2) analyze the success factors and conditions by participating in the workshop of 11 informants; 3) develop a model by constructing, verifying, and evaluating it by attending connoisseurship; and 4) propose policy proposals and practical guidelines by conducting brainstorming discussions with 15 experts and a research team. The research results were as follows: 1) the current state and problems in the new normal have seven components: 1) Planning (P), 2) Organizing (O), 3) Staffing (S), 4) Directing (D), 5) Coordinating (C), 6) Reporting (R), and 7) Budgeting (B); 2) the success factors and conditions were administrators, educators, and school boards must work together to ensure the overall academic progress of students, technology, and communications were playing an important role in helping people adapt to the next normal; 3) a model consisted of a principle, objectives, operational approaches, an evaluation, and conditions for achievement; and 4) policy proposal and practical guidelines were the government should implement an entirely new policy to establish strategies for school administration towards the next normal and the Office of the Basic Education Commission (OBEC) and directors of the Educational Service Area should lead the school administrators and affiliate agencies to apply strategies into practices for school administration towards the next normal.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".