Changes in educational leadership: case study of a Hong Kong education centre
Bibliographic record
Abstract
Educational leadership has paid significant attention to educational research over the past two decades. In Hong Kong, education centres are encountering both opportunities and challenges due to the globalisation, knowledge economy, demographic changes, international higher education development, local educational reform and global culture diversity characterising the new millennium. An appropriate leadership style ensures that Hong Kong education centres achieve quality, accountability and market competitiveness. Based on Fullan's (1999) work, in this study, we present a real-world case study of the changes sustained by a Hong Kong education centre. In particular, we focus on the ongoing changes (i.e., initiation, implementation and institutionalisation) in this centre under transformational leadership over a period of about five years to observe and examine the effectiveness and suitability of the leadership model. This study is designed to analyse the centre's management and changes under transformational leadership. The centre achieves sustainable competitive advantages in the new century.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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".