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Record W3124601338 · doi:10.2308/aud.2008.27.2.199

Dual-Class Shares and Audit Pricing: Evidence from the Canadian Markets

2008· article· en· W3124601338 on OpenAlexaboutno aff
Samer Khalil, Michel Magnan, Jeffrey R. Cohen

Bibliographic record

VenueAuditing A Journal of Practice & Theory · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessAccountingAuditJoint auditCorporate governanceFinanceInternal audit

Abstract

fetched live from OpenAlex

SUMMARY: This paper investigates whether audit fees vary with the wedge between cash flow rights and control rights arising from the presence of dual-class share structures. Dual-class shares exist in firms having two or more classes of shares with disproportionate voting rights. They affect audit fees through their effect on the supply for audit services. External auditors conduct wider (narrower) scope audits depending on whether dual-class shares increase (decrease) audit risk and/or auditor business risk. Wider (narrower) scope audits are more (less) costly for the auditors and for their clients. This paper documents a positive association between audit fees and the wedge between cash flow rights and control rights in a sample of Canadian firms during 2004. It extends current research by investigating whether dominant shareholdings affect audit pricing, and by examining audit pricing in Canada over a time period that witnessed significant changes in corporate governance.

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)0.002
metaresearch head score (Gemma)0.011
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 score0.025
Threshold uncertainty score0.181

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.031
GPT teacher head0.238
Teacher spread0.207 · 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

Citations57
Published2008
Admission routes1
Has abstractyes

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