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Record W2884885507 · doi:10.1111/ijau.12126

Why are auditors blamed when something goes wrong? Experimental evidence

2018· article· en· W2884885507 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

VenueInternational Journal of Auditing · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsConcordia University
Fundersnot available
KeywordsBlameAuditAccountingIncentiveBusinessPublic relationsEconomicsPsychologySocial psychologyPolitical scienceMicroeconomics

Abstract

fetched live from OpenAlex

Audit firms claim that they are used as the whipping boy when something goes wrong, either because of the public's poor knowledge of the auditing function or because financial incentives exist to blame the audit firm. An alternative explanation is that audit firms' active communication of their assurance provider role causes blaming behavior. We investigate these different explanations based on a 2 × 2 between‐subjects experiment in which we manipulate financial incentives to blame the audit firm and the audit firm's communication strategy. Three weeks in advance of the experiment we administered an auditing knowledge questionnaire to the participants to include their auditing knowledge levels into our study. We find that audit firms with “deep pockets” and an active assurance provider communication strategy receive significantly higher blame, and that poor knowledge of auditing is associated with higher blame. Furthermore, when a firm uses an assurance provider communication strategy, then it receives higher blame from participants with high (relative to low) auditing knowledge.

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)0.001
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.004
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.274
Teacher spread0.253 · 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