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Record W2471297504 · doi:10.1108/aaaj-10-2014-1843

Internal audit quality: a polysemous notion?

2016· article· en· W2471297504 on OpenAlexaffabout
Mélanie Roussy, Marion Brivot

Bibliographic record

VenueAccounting Auditing & Accountability Journal · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsInternal auditAuditOriginalityViewpointsQuality auditExternal auditorAccountingCorporate governanceFraming (construction)BusinessPublic relationsSociologyQualitative researchPolitical scienceEngineeringSocial science

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to characterize how those who perform (internal auditors), mandate (audit committee (AC) members), use (AC members and external auditors) and normalize (the Institute of Internal Auditors (IIA)) internal audit work, respectively make sense of the notion of “internal audit quality” (IAQ). Design/methodology/approach – This study is predicated on the meta-analysis of extant literature on IAQ, 56 interviews with internal auditors and AC members of public or para-public sector organizations in Canada, and archival documents published by the IIA, analyzed in the light of framing theory. Findings – Four interpretative schemes (or frames) emerge from the analysis, called “manager,” “éminence grise,” “professional” and “watchdog.” They respectively correspond to internal auditors’, AC members’, the IIA’s and external auditors’ viewpoints and suggest radically different perspectives on how IAQ should be defined and controlled (via input, throughput, output or professional controls). Research limitations/implications – Empirically, the authors focus on rare research data. Theoretically, the authors delineate four previously undocumented competing frames of IAQ. Practical implications – Practically, the various governance actors involved in assessing IAQ can learn from the study that they should confront their views to better coordinate their quality control efforts. Originality/value – Highlighting the contrast between these frames is important because, so far, extant literature has predominantly focussed on only one perspective on IAQ, that of external auditors. The authors suggest that IAQ is more polysemous and complex than previously acknowledged, which justifies the qualitative and interpretive approach.

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)0.021
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.049
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0030.040
Scholarly communication0.0110.015
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.262
Teacher spread0.246 · 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 designTheoretical or conceptual
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

Citations100
Published2016
Admission routes2
Has abstractyes

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