Impacts of <scp>COVID</scp>‐19 on Women and/or Caregivers in Accounting Academia at Canadian Postsecondary Institutions and Suggestions Moving Forward: A Commentary*
Bibliographic record
Abstract
ABSTRACT This commentary provides insights on the issues faced by women and/or caregivers in accounting academia at Canadian postsecondary institutions during the COVID‐19 pandemic. Personal reflections from 23 contributors across Canada were compiled and analyzed using thematic content analysis. Results show that COVID‐19 has adversely impacted research, teaching, and other areas of work and life for this demographic. Research stopped or slowed, lower productivity was experienced, concerns over academic integrity increased, interactions with students decreased, academics left the profession, mental health was adversely impacted, and academics lost dedicated work time. In addition, the contributors provide suggestions to address these issues moving forward to help equity‐seeking groups. Suggestions include support from postsecondary institutions at all levels, additional funding, adjustments to tenure and promotion criteria, and the option for a reduced workload.
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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 | 0.015 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.027 | 0.015 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.018 | 0.023 |
| Insufficient payload (model declined to judge) | 0.007 | 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".