Redressing the fundamental conflict of interest in public company audits
Bibliographic record
Abstract
The goal of various audit industry reforms is to better align the interests of the auditor with external stakeholders. These proposed reforms ignore the fundamental conflict of interest—‘the client’ hires, fires and determines the compensation for the auditor. This problem is fundamental in that ‘the client’ is normally the management or board of the firm who, on occasion, have reason to want to take advantage of the inherent imprecision in accounting for their benefit and subtlety pressure the auditor to achieve this. My evidence‐based proposal takes advantage of the well‐known aversion of managers and boards to government intervention. It incentivizes management and boards to demand rigorous audits by requiring regulatory bodies impose their choice of auditor on public companies that meet well‐specified criteria that indicate poor‐quality reporting (e.g., restatement of financial statements). This proposed reform retains the ‘on average’ benefits that extant research shows the current system of private sector auditing provides while stimulating greater managerial and director self‐interest in high‐quality financial reporting.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.167 | 0.305 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.022 | 0.015 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".