COVID-19 Caregiving Avalanche: The Impact on Emotional Exhaustion on Female Natural Science and Engineering Academics
Bibliographic record
Abstract
Gender disparity persists in the personal caregiving of children and older adults, and in professional caregiving duties, with many workplace policies and cultures favoring the “ideal worker” and presenting significant and continuing barriers to female caregivers’ professional success and well-being. The recent pandemic both highlighted and augmented this disparity as schools, daycares, and adult care facilities closed or implemented restrictions. This study interprets results from the July 2021 Canadian Natural Sciences & Engineering (NSE) Faculty Workplace Climate Survey by empirically assessing the impact on emotional exhaustion of the increased caregiving burden during the COVID-19 pandemic on female academics in the highly masculinized NSE fields. Results indicate that women were more likely to experience emotional exhaustion even when other factors were considered. Collegiality and inclusion were found to be protective factors, illustrating important implications for, and the retention and support of, success and well-being of female NSE academics.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".