Competencies, Roles and Effective Academic Leadership in World Class University
Bibliographic record
Abstract
How an academic leader can become more effective? This research question is examined in the context of middle level leadership in research universities that includes the Deans and Head of Departments. It is based on a review of literature that focuses on the investigation of effective academic leadership. In the present situation of globalization, academic excellence is often related to being World Class University. Leadership effectiveness is more related to situational leadership style in research universities and in a global context. Hence situational leadership models such as Hersey and Blanchard and Yetton-Vroom are analyzed. It is suggested that effective academic leaders use the four styles proposed by Hersey and Blanchard that includes “telling, selling, participating and delegating”. These styles should be used in relation to ability and willingness of followers to perform the assigned tasks. The review also indicated that to be effective, academic leaders require certain competencies and perform the necessary roles in order to lead. Effective academic leaders need the skills and abilities to lead research universities towards excellence. Roles of academic leaders are examined in relation to Mintzberg leadership roles. The ten roles identified by Mintzberg are categorized into three major roles of interpersonal contact, information processing and decision making. To summarize, effective academic leaders utilized various leadership styles according to certain situations, possessed the required competencies and assumed certain roles when appointed as Deans and Head of Departments in research universities. As such it is important that a systematic leadership development programs should be developed to ensure academic leadership effectiveness.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".