Leadership Development for Contemporary Post-Secondary Academic Leaders: Challenges, Content and Approach
Bibliographic record
Abstract
In the dynamic landscape of contemporary higher education, the demand for leaders well-versed in the intricacies of its challenges has become paramount. Despite the availability of leadership fellowships and retreats globally, there is a notable dearth of institution-specific leadership development programs tailored for post-secondary education leaders. This deficiency leaves a substantial number of higher education leaders ill-equipped with the fundamental competencies needed for effective leadership. This review underscores the pressing necessity to establish institution-based leadership development initiatives explicitly crafted for academic leaders and faculty members. The exploration encompasses diverse platforms and methodologies for delivering such programs, drawing insights from empirical studies that underscore the advantages of leadership development. Also, the review discusses the content of leadership development curricula. Focusing on academic leaders and faculty, these curricula cover competencies such as strategic planning, interpersonal communication, talent management, and adaptive leadership. The outcomes underscore the significance of institutions integrating leadership development efforts within their academic domains. The discussion delves into the manifold benefits of instituting leadership development programs, not only as a cost-effective alternative to external fellowship courses but as a strategic move with multifaceted advantages. These advantages encompass streamlining competitive succession planning, magnetizing and retaining talent, cultivating expansive networking opportunities, and augmenting the capacity to confront contemporary challenges in higher education. By prioritizing the nurturing of academic leaders, institutions can effectively bridge the gap between current leadership skills and the evolving demands of the higher education landscape.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".