Indicators of Innovative Leadership for Secondary School Principals: Developing and Testing the Structural Relationship Model
Bibliographic record
Abstract
The objectives of this research were to test the fitness of the model that developed from theory and research with empirical data and to verify the factor loading value of major components, sub-components, and indicators by using descriptive research methodology. Determine the sample size in proportion between sample unit and numbers of parameter 20:1 and selected 1,020 samples from 2,359 secondary school principals under the jurisdiction of the Office of the Basic Education Commission of Thailand by using proportional random sampling. Collecting data by using a set of rating scale questionnaires with reliability 0.97. Data were analyzed by using AMOS Program. The research was based on the provided research hypotheses including Visionary Measurement Model (VIS), Collaborative Measurement Model (COL), Risk-taking Measurement Model (RISK), Oriented Change Measurement Model (OCH) and Innovative Leadership Model were fit with empirical data. The main components, sub-components, and indicators were in accordance with the criteria.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".