The Development of an Effective Private School Management Model in the Northeastern Region of Thailand
Bibliographic record
Abstract
The aim of this mixed-methods research is to create a model for developing effective private schools in the northeast of Thailand. Seven experts examine and affirm the key components for school effectiveness as suitable with priorities of needs for development as follows: 1) school curriculum management comprising instructional leadership, teaching and learning management, academic planning system, and information and technology; 2) learning community building consisting of learning network, collaboration, and learning climate and environment; 3) management of the school administrators comprising principal leadership, expertise in academic management, expertise in school personnel management, expertise in management of general affairs, and expertise in budget management. The research team creates the model; 15 experts determine and affirm it as suitable, feasible, and useful at the highest level; and the results of the experimentation for 3 months at one purposively selected school in Bookeo District, Chaiyaphum Province are found effective at the highest level. The model can be used as a framework in both elementary and secondary schools to go to quality schools.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".