Are Referred-To Auditors Associated with Lower Audit Quality and Efficiency?
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.
Bibliographic record
Abstract
SUMMARY Inadequate supervision by lead auditors of “other” (component) auditors contributing to audit engagements has been a recent regulatory concern. However, uniquely in the United States, the lead auditor is required to conduct only minimal supervision of the other auditor and refer to the other auditor in its audit report, when it divides responsibility with the latter. Our sample of “referred-to” (RT) firm-years is divided, about equally, between audits of consolidated subsidiaries and equity-method investees. We document two findings. First, supervision challenges drive the use of RT auditors for consolidated subsidiaries while the component’s materiality drives the use of RT auditors in both settings. Second, there is some evidence that RT auditors in both settings are associated with lower audit quality and efficiency compared with control samples, and this negative effect is stronger for consolidated subsidiaries. Our research is relevant to the Public Company Accounting Oversight Board’s proposed changes in auditing standards for other auditors.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.128 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it