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Record W4255804907 · doi:10.1506/mhp9-523e-q25v-vjvx

Did Houston Clients of Arthur Andersen Recognize Publicly Available Bad News in a Timely Fashion?

2005· article· en· W4255804907 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueContemporary Accounting Research · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicComputational and Text Analysis Methods
Canadian institutionsnot available
Fundersnot available
KeywordsAdvertisingPsychologyBusiness

Abstract

fetched live from OpenAlex

Despite the allegations of audit failure and the enormous publicity surrounding Arthur Andersen's indictment, there is no systematic empirical evidence on characteristics of accounting information of clients of Arthur Andersen vis-à-vis other Big 6 auditors. I examine whether earnings of Andersen's Houston-based clients are timely in reporting bad news about future cash flows. I find that relative to a control group consisting of Houston-based clients audited by other Big 6 auditors, earnings of Andersen clients are less timely in reporting bad news. Further, it appears that operating accruals of Andersen clients are less effective in accelerating the timely recognition of bad news than operating accruals of non-Andersen clients. The findings suggest that the clients of Andersen's Houston office engaged in aggressive accounting practices, including delayed recognition of publicly available bad news.

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.

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)0.012
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.821
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.169
GPT teacher head0.431
Teacher spread0.262 · 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