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Record W4306843360 · doi:10.2308/ajpt-2021-139

Always Feeling Behind: Women Auditors' Experiences during COVID-19

2022· article· en· W4306843360 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAuditing A Journal of Practice & Theory · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHabitusAuditScholarshipCoronavirus disease 2019 (COVID-19)FeelingWork (physics)SociologyPublic relationsPsychologySocial psychologyBusinessPolitical scienceAccountingSocial scienceCultural capitalMedicineLaw

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.065
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.065
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.003
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.020
GPT teacher head0.290
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it