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Record W121793713

On IT Control Weaknesses in Auditors’ Reports on Internal Control

2012· article· en· W121793713 on OpenAlexaff
J. Efrim Boritz, Louise Hayes, Jee‐Hae Lim

Bibliographic record

VenueAmericas Conference on Information Systems · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAuditAccountingControl (management)Internal controlBusinessStrengths and weaknessesBig dataPsychologyComputer scienceManagementData miningEconomics
DOInot available

Abstract

fetched live from OpenAlex

By analysing auditors’ SOX 404 reports from 2004 to 2009 we find after 2006 that reporting of information technology control weaknesses (ITWs) decreased significantly, primarily by Big 4 firms. This change appears to reflect Big 4 reporting practices in response to a change in auditing standards rather than the nature of Big 4 clients’ internal control systems, suggesting that SOX 404 auditors’ reports have become less informative. We find associations between ITW reporting and both non-ITW and financial misstatement reporting are moderated by auditor type and time period (2004-2006 vs. 20072009). Based on frequency of reporting, the relative ordering of individual ITWs, while differing over time, is similar over auditor type, company size and industry. We identify a small number of non-ITWs in SOX 404 reporting that may hold practical implications for an auditor’s consideration of IT control testing and an educator’s teaching of IT and non-IT controls.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.091
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.091
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.007
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.002
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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2012
Admission routes1
Has abstractyes

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