The Challenges Faced and Strategies Used by University Administrators Before and During COVID-19
Bibliographic record
Abstract
This study undertook a systematic literature review corresponding to challenges faced and strategies used by university administrators in Ontario (Canada) and internationally before and during the COVID-19 pandemic. As leaders who act as the interface between academic institutions and faculty, staff, and students, the study sought to identify university deans’ and department chairs’ specific roles and responsibilities in response to such adversity. The study adopted Bronfenbrenner’s (1999) bioecological model of development and Mukaram et al.’s (2021) adaptive leadership framework to understand the complex demands placed upon and the responses of university administrators navigating the pandemic. Findings reveal that during emergency situations like the COVID-19 pandemic, university administrators act as change agents who redefine their complex roles through a holistic leadership framework that fosters flexibility, empathy, resilience, and adaptability in their practice while developing sustainable, inclusive, and interconnected learning communities.
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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 | 0.043 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".