Always Feeling Behind: Women Auditors' Experiences during COVID-19
Bibliographic record
Abstract
SUMMARY This paper examines women auditors' experiences during the COVID-19 pandemic using interviews and personal reflections. Drawing on Pierre Bourdieu's scholarship, we observe that COVID-19 was a destabilizing event for women auditors. Women's default gender role was brought to the fore both at work and at home. One of the key impressions we developed when analyzing the data is that positive changes that foster gender equality were nowhere near significant enough to offset the audit firms' strategies to boost their economic capital and the return of previous patriarchal roles. In short, COVID-19 most often exacerbated prior tensions in women's “work” habitus and “home” habitus, therefore further subjugating women to the power of dominant gender norms. Ultimately, this paper contributes to a better understanding of the implications of COVID-19 on women in audit firms by highlighting women auditors' fragile positions in balancing multiple demands at work and at home.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.014 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".