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Record W2104764165 · doi:10.1506/ap.6.4.1

What's Wrong with the Current Audit Risk Model?*/QU'EST‐CE QUI NE VA PAS DANS LE MODÈLE ACTUEL DE RISQUE DE VÉRIFICATION?

2007· article· en· W2104764165 on OpenAlexaffvenue
Wally Smieliauskas

Bibliographic record

VenueAccounting Perspectives · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAuditJudgementHumanitiesAccountingPhilosophyBusinessEpistemology

Abstract

fetched live from OpenAlex

ABSTRACT This paper identifies a serious risk anomaly between the accounting and auditing literatures. This anomaly has important consequences for the validity of auditor professional judgement in today's rapidly evolving financial reporting environment. These risk consequences were comprehensively surveyed in a recent forum in this journal (2005, vol. 4, no. 2). I refer to these risk consequences as accounting risks. Accounting risks require an expanded concept of misstatements that incorporates forecast errors. The problem with the current audit risk concept is that it does not incorporate accounting risks. This is shown by reference to accounting and auditing standards and other authoritative literature, including empirical research. To remedy this limitation I propose a new risk model that helps integrate the accounting and auditing perspectives on financial reporting into one combined conceptual framework. Such an approach also addresses the problems of integrating into a conceptual framework the new business risk approaches to auditing. RÉSUMÉ L'auteur relève une sérieuse anomalie relative au risque selon qu'il est abordé à travers le prisme de la comptabilité ou celui de la vérification. Cette anomalie a d'importantes répercussions sur la validité du jugement professionnel du vérificateur dans le contexte actuel de l'information financière qui évolue rapidement. Ces répercussions ont fait l'objet d'une étude approfondie dans un récent forum paru dans la présente publication (vol. 4, n 0 2). L'auteur assimile ces répercussions au risque comptable, qui fait appel à une extension de la notion d'inexactitude incorporant les erreurs prévisionnelles. La notion actuelle de risque de vérification pose problème, car elle n'englobe pas le risque comptable. C'est ce que révèle la consultation des normes de comptabilité et de vérification, ainsi que d'autres textes faisant autorité, notamment ceux qui sont issus de la recherche empirique. Pour résoudre ce problème, l'auteur propose un nouveau modèle de risque qui facilite la conjugaison des points de vue de la comptabilité et de la vérification sur l'information financière dans un cadre conceptuel mixte. Ce modèle s'attaque également à un autre problème: celui d'insérer dans un cadre conceptuel les nouvelles approches de la vérification tenant compte du risque d'entreprise.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.004
Open science0.0010.000
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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2007
Admission routes2
Has abstractyes

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