More Pivots than a Centipede on Ice Skates: Reflections on Shared Leadership in a Post-Secondary Institution During COVID-19
Bibliographic record
Abstract
This article is a case study describing the University College of the North’s (UCN) response to the COVID-19 pandemic, outlining pandemic planning and management processes at UCN from March 11, 2020, to September 30, 2021. UCN’s planning processes evolved from a top-down approach led by administration to an approach that saw greater shared leadership in the crisis. Shared leadership included senior leaders, middle management, faculty, and staff who both addressed the immediate crisis and engaged in post-pandemic planning. Lessons learned may help post-secondary institutions gain greater resiliency and sustainability as the post-COVID environment emerges.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.066 | 0.039 |
| Scholarly communication | 0.019 | 0.007 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.005 | 0.019 |
| Insufficient payload (model declined to judge) | 0.008 | 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".