Leadership in a Complex Adaptive System: An Exploratory Case Study of One Faculty at a Canadian Post-Secondary Educational Organization
Bibliographic record
Abstract
The research study examined leadership in one post-secondary educational organization through the lens of complexity theory. The post-secondary educational organization in this study is a complex adaptive system that is entangled in uncertainty, non-linearity, and interconnectivity, where the system is under constant change and predictions based on past practice are not always possible. Leaders in this context do not have the luxury to rely primarily on history, best practices, or simplistic linear solutions in response to their challenges. This dissertation focuses on providing a connection between educational leadership and complexity theory, so that the latter can strengthen investigation of the former, within a complex adaptive system.\nThis research project used an exploratory qualitative case study methodology grounded in the interpretive paradigm. The dataset was comprised of 11 semi-structured interviews and an examination of organizational documents bounded by the case. Thematic analysis of the dataset provided insight into leadership within complexity. The findings in this research study make a contribution to the literature by exploring how leadership can nurture the adaptive space found in the complex contexts. Specifically, these findings demonstrate that educational leaders, all educational leaders in formal, informal, and emergent roles, are positioned to enable this adaptive space, with which they are a part of. Implications to practice and recommendations for future research are discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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".