On the edge of chaos: how the deans at one Canadian university have managed to lead in the face of the pandemic and other sources of uncertainty and complexity
Bibliographic record
Abstract
There is a growing body of literature on the roles that deans play in challenging times; however, what is often missing are deans’ own voices as they reflect on their experiences trying to manage the dilemmas and crises inherent in their work. This is particularly true of the past few years when deans have managed unprecedented levels of complexity and uncertainty. Using complexity theory as a conceptual framework and case study methodology, the author shines a light on the lives of deans at a large Canadian university as they grappled with issues related to the pandemic and others such as a protracted strike by academic staff. The findings suggest that complexity theory can serve as a useful theoretical lens for better understanding issues such as structural tensions, resistance and non-compliance, the multiple roles of deans, toxic faculty cultures, and trust and mistrust in higher education.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".