Model Development for Adaptive Leadership of Division Heads in Technical Colleges under the Office of the Vocational Education Commission
Bibliographic record
Abstract
The objectives of this research were 1) to study components and indicators for adaptive leadership of the division heads in technical colleges, 2) to study the current conditions, desirable conditions, and needs to develop adaptive leadership of the division heads in technical colleges, 3) to create and develop the model development for adaptive leadership of the division heads in technical colleges, and 4) to study the results of using the adaptive leadership of the division heads in technical colleges. The methodology was research and development conducted in 4 Phases as follows according to the objectives. The results of the research found that 1) the components and indicators of adaptive leadership consist of 7 components and 25 indicators, the results of assessing the suitability of the components and indicators overall are at the highest level. 2) The current conditions of the adaptive leadership of the division heads in technical colleges overall are at a high level, the desirable conditions overall are at the highest level, and the overall need for developing the division heads in technical colleges, the PNI modified mean is 0.23. 3) The model development for adaptive leadership of the division heads in technical colleges consists of 1) Principles, 2) Objectives, 3) Contents of activities, 4) Method of Leadership Development, and 5) Evaluation. The results of the model evaluation overall are appropriate at a high level, and the possibility, and utility overall are at the highest level. And the evaluation results of the manual for using the format as a whole are appropriate at the highest level. 4) The results of a study of the use of the model development for adaptive leadership of the division heads in technical colleges found that 1) the adaptive leadership behavior of the division heads in technical colleges before using the model overall average mean is at a moderate level, and after overall mean is at the highest level that higher than average before are statistically significant at the .05 level, and 2) The results of the division head’s satisfaction assessment as a whole is 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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".