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Enregistrement W340147500

Enhancing Public Confidence: The GAO's Peer Review Experience: Even Auditors Need to Be Audited

2006· article· en· W340147500 sur OpenAlexaboutno aff
David Walker

Notice bibliographique

RevueJournal of accountancy online/Journal of accountancy · 2006
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueRisk Management in Financial Firms
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAuditJoint auditAccountingAudit planChief audit executiveQuality auditAccountabilityBusinessMultinational corporationInformation technology auditAudit committeeGovernment (linguistics)Internal auditPublic relationsPolitical scienceFinanceLaw
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

In 2004 we at the Government Accountability Office (GAO) arranged to have a multinational team of experienced performance auditors conduct the first-ever peer review of our performance audits of federal government programs (www.gao. gov/peerreviewrpt2005.pdf). We also hired KPMG LLP to conduct a peer review of our financial audit practice their fourth such engagement with us. Both audit teams concluded that during the period reviewed the GAO's quality assurance system was suitably designed and operating effectively to provide reasonable assurance of conforming to applicable professional standards. The international peer review team also said that other national audit offices may want to emulate several of our practices and made suggestions that further enhanced our practice and provided other significant benefits. According to the reviewers, [the] quality assurance system reinforces the GAO's independence, objectivity and reliability. These reviews inform Congress of and give the American people confidence in the quality of our financial and performance audits. UNDER THE MICROSCOPE A team of 16 experienced performance auditors from seven countries reviewed our performance audit practice. The Office of the Auditor General of Canada led the multinational team. Other participants included national audit offices in Australia, Mexico, the Netherlands, Norway, South Africa and Sweden. The KPMG team consisted of experienced financial audit partners and managers with extensive government financial auditing experience. The review teams focused on the elements of our quality assurance system dealing with engagement performance and compliance monitoring. They reviewed our audit policies and process controls, examined a representative sample of our 2004 audit engagement files and reports on government programs, and interviewed senior managers and staff responsible for selected engagements. They also evaluated our internal inspection program, including a representative sample of engagement files that our internal inspectors had examined in 2004 to determine whether their findings were supportable. The performance audit team followed government auditing standards (the Yellow Book) and conducted the review in a manner consistent with the code of ethics and standards issued by the International Organization of Supreme Audit Institutions. The review team's ultimate objective was to determine whether the GAO's system of quality controls provided reasonable assurance that our work is independent, objective and reliable. The financial audit team followed the applicable AICPA peer review standards as well as government auditing standards. GOOD MARKS A key organizational and operational benefit of the peer review was the reviewers' confirmation that some of our key overarching quality control procedures are global better practices (see How to Do It Better,). According to their report, those practices help ensure that we focus our efforts on factors that affect government performance, that we assign engagement resources according to risk, that we develop complete and reliable evidence, that our engagement teams have the guidance and diagnostic tools necessary to perform their work and that our reports are clear, persuasive and fair. The reviewers also said that the GAO could improve its performance audit practice by, for example, enhancing the transparency and efficiency of its quality assurance system and policies. We have implemented some of these recommendations, and we are testing others (see Dividends Earned,). A PLAN FOR EXCELLENCE The GAO's approach to quality assurance was based on applicable professional standards and the agency's core values of accountability, reliability and integrity and it ends with public dissemination of virtually all its products. We had already created a quality assurance framework (see the exhibit) to summarize the policies and procedures we use to ensure compliance with professional standards and our core values. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,188
score de la tête « metaresearch » (Gemma)0,411
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Évaluation · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,812
Score d'incertitude au seuil0,994

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,1880,411
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0030,003
Études des sciences et des technologies0,0170,012
Communication savante0,0220,018
Science ouverte0,0040,018
Intégrité de la recherche0,0100,015
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,030
Tête enseignante GPT0,290
Écart entre enseignants0,260 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
DomaineÉvaluation
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2006
Routes d'admission1
Résumé présentoui

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