The Development of Indicators and Approaches for Developing Innovative Leadership of World-Class Standard School Administrators
Bibliographic record
Abstract
This research aimed to develop indicators and approaches for developing innovative leadership of world-class standard school administrators. The research methodology used was a multi-phase mixed method. The research was divided into 4 phases: Phase 1: Development of innovative leadership indicators by studying documents and research related to innovative leadership principles and theories and interviewing experts, and Phase 2: Testing the consistency of the developed innovative leadership structural relationship model with empirical data. The samples consisted of 500 administrators, 500 academic department heads, and 500 teachers, totaling 1,500 people, from 500 world-class international standard schools nationwide using confirmatory factor analysis (CFA), Phase 3: Creating and developing approaches and manuals for using innovative leadership development approaches, using a synthesis of research results from phases 1 and 2 and interviewing experts, and Phase 4: Evaluating the approaches and manuals for using innovative leadership development approaches, using Stufflebeam’s evaluation framework for propriety, feasibility, and utility. The research results found that 1) the innovative leadership indicators of world-class standard school administrators consisted of 5 main components, 17 sub-components, and 75 indicators, namely (1) the innovative vision, with 3 sub-components and 9 indicators; (2) innovative risk-taking, with 3 sub-components and 14 indicators; (3) Creating an Innovative Network, with 4 sub-components and 19 indicators; (4) innovative creativity, with 4 components and 18 indicators; and (5) Innovative change, with 3 sub-components and 15 indicators, 2) The structural relationship model of innovative leadership indicators has statistical values consistent with empirical data (Chi-square = 108.31, df = 95, P-value = 0.16561, c2/df = 1.14, RMSEA = 0.034), 3) The innovative leadership development approaches consist of 5 dimensions, 81 practices and the manual for using the innovative leadership development consists of 4 sections, and 4) The results of the evaluation of the approaches and the manual for using the approaches according to the evaluation standards were found to be at the highest level in all 3 aspects: propriety (x= 4.94, SD =0.23), feasibility (x= 4.92, SD =0.28), and utility (x= 4.89, SD =0.32).
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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 | 0.061 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".