The guidelines for raising up and developing effective educational organization in small schools’ spread to students’ education asylum and schools’ dissolution of local schools’ crisis in Thailand
Bibliographic record
Abstract
This study was to investigate the guidelines for raising up the quality enhancement to synthesis the Office of Bueng Kan Primary Education Service Area in 122 small schools with the 500 officers/personnel educators' (OPS) perceptions from 9 Districts with the participators were administered.Designing the correlation variables with the 42-item Factors on Efficient Public Sector Management (FEPSM) Questionnaire on 7 scales were assessed the officials' efficient public sector administrative management organizations.The Thai education failure and small school crisis of Thai government policy reforms to spread of students' asylums and dissolutions were assessed with the 35-item Questionnaire on Thai Education Policy (QTAP), and the 10-item Teacher-Student Creative Thinking Abilities (TSCTA) that was violence against teachers and students' instructional skills were analyzed with the inference statistic.The three instruments are valid and reliability with the Cronbach alpha coefficient, intercorrelation circumplex, and factor loading analysis.Learning and teaching management of small schools alone, lonely, and abandoned under the failure of educational administration and management according to the policy of the The guidelines….T. Pengchan & T. T. Santiboon.
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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 | 0.012 | 0.025 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".