Never‐ending repetitiveness, sadness, loss, and “juggling with a blindfold on:” Lived experiences of Canadian college and university faculty members during the COVID‐19 pandemic
Bibliographic record
Abstract
Abstract We report on the lived experiences of faculty members during the early months of the COVID‐19 pandemic, exploring the broader experiences of faculty members as individuals living multifaceted lives whose homes became their offices, their students scattered geographically and their home lives upended. Using a phenomenological approach for data collection and analysis, we conducted 20 in‐depth interviews with faculty holding varied academic appointments at universities across Canada. Experiences during the early months of the pandemic were described as being overwhelming and exhausting, and participants described as being stuck in a cycle of never‐ending repetitiveness, sadness and loss, or managing life, teaching and other professional responsibilities with little sense of direction. In keeping with phenomenological methods, this research paints a visceral picture of faculty experiences, seeking to contextualize teaching and learning during this time. Its unique contribution lies in portraying emergency remote teaching as an overlapping and tumultuous world of personal, professional and day‐to‐day responsibilities. Practitioner notes What is already known about this topic Surveys and first‐person accounts of remote teaching paint an initial picture of experiences. During the COVID‐19 pandemic many faculty were facing various anxieties and tensions. The transition to remote teaching was uneven. What this paper adds A systematic analysis of faculty experiences during the early months of the pandemic. Evocative and vivid descriptions of academics’ experiences. An explanation of what it feels like to live through this time. Implications for practice and/or policy Faculty require more support. Trauma‐aware and trauma‐informed practices can support faculty and their work. Rich descriptions can inform future policymaking and practice.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.041 | 0.030 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".