Development of Risk Management System in Private School General Education
Bibliographic record
Abstract
The study aimed to; study current situations and problem, develop the appropriated system, and evaluate the outputs of risk management in/for private school, general education, Thailand. The research designed into three phases based on the objectives of the study and research and development (R&D) was employed. The questionnaires, semi-structured interview forms, and evaluation forms were used as research tools and percentage, means, and standard deviation (SD) were selected for statistical analysis tools. Moreover, Multi-Attribute Consensus Reading (MACR) was employed for pre-system implementation. The research finding showed that—the current situations and problems in risk management in private school today Thailand viewed by four aspects included strategic, operational, financial, and compliance. In the risk management processes divided into five steps consisted of determining the objectives, investigation, assessment, administration, and monitoring and evaluation. The appropriated risk management system was developed with five major factors and 22 sub-factors for inputs. The feedbacks of the developed risk management system implementation showed that the private school administrators and teachers comprehensive aware of risk management in high level. The developed system help to decrease and be able to manage the risks. This results of implementation of the developed risk management system was satisfied by school administration and teachers in high satisfaction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".