Are we failing female and racialized academics? A Canadian national survey examining the impacts of the COVID‐19 pandemic on tenure and tenure‐track faculty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The novel coronavirus 2019 (COVID-19) pandemic caused the abrupt curtailment of on-campus research activities that amplified impacts experienced by female and racialized faculty. In this mixed-method study, we systematically and strategically unpack the impact of the shift of academic work environments to remote settings on tenured and tenure-track faculty in Canada. Our quantitative analysis demonstrated that female and racialized faculty experienced higher levels of stress, social isolation and lower well-being. Fewer women faculty felt support for health and wellness. Our qualitative data highlighted substantial gender inequities reported by female faculty such as increased caregiving burden that affected their research productivity. The most pronounced impacts were felt among pre-tenured female faculty. The present study urges university administration to take further action to support female and racialized faculty through substantial organizational change and reform. Given the disproportionate toll that female and racialized faculty experienced, we suggest a novel approach that include three dimensions of change: (1) establishing quantitative metrics to assess and evaluate pandemic-induced impact on research productivity, health and well-being, (2) coordinating collaborative responses with faculty unions across the nation to mitigate systemic inequities, and (3) strategically implementing a storytelling approach to amplify the experiences of marginalized populations such as women or racialized faculty and include those experiences as part of recommendations for change.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 it