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Record W4306842053 · doi:10.2308/ajpt-2020-114

Re-Examining Auditability through Auditors’ Responses to COVID-19: Roles and Limitations of Improvisation on the Production of Auditing Knowledge

2022· article· en· W4306842053 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
TopicAuditing, Earnings Management, Governance
Canadian institutionsQueen's UniversityWestern University
Fundersnot available
KeywordsAuditImprovisationTimelinePandemicCoronavirus disease 2019 (COVID-19)Audit riskBusinessWork (physics)Power (physics)AccountingPsychologyMedicineEngineeringHistory

Abstract

fetched live from OpenAlex

SUMMARY Drawing on Power’s theorization of the logic of auditability as a multidimensional system (Power 1996), we examine the impact of the COVID-19 pandemic on auditors’ year-end work from January to April 2020. Based on 24 semistructured interviews with auditing and accounting professionals located in China, we find that all four dimensions of the logic of auditability were destabilized at once. To restore the conditions of auditability during the pandemic, auditors improvised a deviant system of audit knowledge by rearranging the timeline of audit procedures, altering the substance of audit processes, and designing alternative control mechanisms. As the audit profession continues to evolve and more institutional decomposition (or reconfiguration) of the logic of auditability is expected to occur, this study contributes to our understanding of how auditors improvise in the backstage and produce comfort when they have to operate outside the protective umbrella of legitimate processes during sudden change of circumstances.

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)0.017
metaresearch head score (Gemma)0.532
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.620
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.532
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.301
Teacher spread0.248 · 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