"Continue as Normal but in a Pandemic": A Mixed-Methods Study of Faculty Experiences in Canadian Academia
Bibliographic record
Abstract
In March of 2020, in response to the rapid spread of the SARS-CoV-2 virus, the Ontario government declared a state of emergency and implemented public health measures to close in-person services and public events. To minimize disruptions to teaching, universities quickly pivoted to online learning. This policy response had significant and widespread impacts on the work and lives of university faculty across the province. The purpose of this research was to explore how this disruption and transition to remote work impacted faculty members’ working conditions, work-life balance, and health and well-being during the pandemic. Informed by feminist political economy and interpretative phenomenology, my study explored the diverse experiences, perspectives, and needs of faculty members during the COVID-19 pandemic at a public research university in Ontario. My study used a sequential mixed-methods approach consisting of a critical analysis of COVID-19 university policy communications, an online survey, and semi-structured interviews. Qualitative and quantitative data were collected and triangulated to reveal the social and structural conditions that shape health disparities in academia along the lines of class, gender, and race. My research revealed tensions between the university policy communication discourse and the lived experiences of faculty members during the pandemic. Firstly, the corporatization of universities, in response to neoliberal governmental practices of cost-cutting and underfunding of post-secondary education in Ontario, has promoted the precarity of contract teaching labour. Expectations from university management that faculty would provide flexibility and accommodations to support students’ needs greatly exacerbated faculty workloads. This had financial implications for precariously employed contract faculty who had to work beyond their contract hours, resulting in more unpaid work. Further, full-time faculty, especially women, reported an increase in service work and emotional labour for students and colleagues that went unpaid by the institution. Lastly, in the university communications, the dominant discourse surrounding family care responsibilities focused on challenges with childcare, with little to no acknowledgement of other forms of care work such as elder care. These findings have health and equity implications for university faculty members and highlight the need to re-examine institutional practices that impact the working conditions of faculty in Canadian academia.
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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 | 0.018 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.034 | 0.017 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".