MétaCan
Menu
Back to cohort

Auditing, Ethical Issues In

2015· other· en· W1520245290 on OpenAlexaff
James C. Gaa

Bibliographic record

VenueWiley Encyclopedia of Management · 2015
Typeother
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAuditAccountingBusinessConfidentialityPublic interestObligationGenerally Accepted Auditing StandardsExternal auditorCapital marketInternal auditPublic relationsAccounting information systemFinanceFinancial accountingPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract Audits are examinations of information for the purpose of evaluating its reliability. The information in question may be financial or nonfinancial, and may be intended for users of information who are either internal or external to the organization. The objective of external auditing is to increase the confidence of external stakeholders regarding the quality of the financial information produced by organizations. The globalization of capital markets has had an impact on the ethics of auditing, because cultural diversity presents major issues regarding appropriate international ethical standards, and because of increased attention by capital market regulators to the inter‐jurisdictional aspects of auditing. Auditors have an obligation to make in the interest of external stakeholders and in the public interest. The central problem is that, for auditing to be an important factor in capital markets, auditors must be independent of their clients. However, there are built‐in factors that make solving this conflict of interest difficult. One of the fundamental principles of accounting and auditing is confidentiality. Recent developments internationally involving unethical and illegal acts of companies have caused regulators and ethics standard setters to consider the conditions under which confidentiality may be or should be breached.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.085
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueWiley Encyclopedia of ManagementSame topicAuditing, Earnings Management, GovernanceFrench-language works237,207