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Record W1986110121 · doi:10.2308/ciia-50116

Clients' Preferred Relationship Approach with their Financial Statement Auditor

2011· article· en· W1986110121 on OpenAlexaboutno aff
Richard Fontaine, Claude Pilote

Bibliographic record

VenueCurrent Issues in Auditing · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsAuditAuditor independenceAccountingFinancial statementBusinessJoint auditAudit substantive testAuditor's reportAudit evidenceExternal auditorChief audit executiveInternal audit

Abstract

fetched live from OpenAlex

SUMMARY Our published study, “An Empirical Study of Canadian Companies to Determine Clients' Preferred Relationship Approach with Their Financial Auditor” (Fontaine and Pilote 2011), examines the type of relationship that clients prefer to have with their financial auditors. We surveyed 306 Canadian financial executives (clients); in general, clients prefer more of a relational approach (i.e., an ongoing process based on cooperation, communication, and trust) than a transactional approach (i.e., competition and self-interest, resulting in an arm's-length relationship). Further, clients seek information and advice beyond core audit services. However, despite clients' desire for close relationships, they also want to remain at arm's length from their auditor, as required by the auditor's code of ethics. Our study contributes to audit practice by providing direct evidence of client relationship preferences, which could help auditors to enhance client relationships. In addition, evidence of the client's desire to remain at arm's length (i.e., respecting auditor independence) could be of interest to audit practitioners and audit standard setters.

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)0.007
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.461

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.099
GPT teacher head0.293
Teacher spread0.193 · 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 designQualitative
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

Citations43
Published2011
Admission routes1
Has abstractyes

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