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Record W3123562585 · doi:10.1506/0l0u-c5v6-3ftm-5dtj

Audit Qualifications of Income‐Decreasing Accounting Choices*

2006· article· en· W3123562585 on OpenAlexvenueno aff
Frank D. Hodge, Roger D. Martin, Jamie Pratt

Bibliographic record

VenueContemporary Accounting Research · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAccountingAuditBusinessFinancial accountingNet incomeAccounting information systemActuarial scienceEconomics

Abstract

fetched live from OpenAlex

Abstract In this study we conduct an experiment to examine how qualifying an income‐decreasing accounting change in years of strong financial performance affects financial report users' assessments of strategic reporting, current financial performance, and future financial performance (performance over the next three years). We find that without the qualification, users viewed the income‐decreasing accounting change as relatively nonstrategic and that user assessments of current and future performance were not different. In the presence of the qualification, users believed that the accounting change was relatively strategic, and they discounted the income effect of the accounting change. We find further that their assessments of future performance were below their assessments of current performance but no different from the assessments of future performance in the absence of the qualification. Although our findings suggest that audit qualifications encourage users to be skeptical of income‐decreasing accounting changes, we find no evidence that they impose negative consequences on management in terms of lower assessments of financial performance.

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)0.056
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 score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.056
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.044
GPT teacher head0.309
Teacher spread0.266 · 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

Citations6
Published2006
Admission routes1
Has abstractyes

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