The Regulation of Public Auditing in Canada and the United States: Self-Regulation or Government Regulation?
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
Auditors play an important role as gatekeepers to public capital markets. By attesting to the accuracy of a company’s financial statements, the auditor lends its credibility to that company and its financial health. Both market and legal mechanisms play a role in ensuring that auditors perform high quality audits. Reputation is critical in the market for auditors. In addition, potential legal liability to issuers and investors arising from contract, tort, and statutory securities laws creates incentives for auditors to conduct high quality audits. Potential discipline by professional self-regulatory bodies also plays a part. Striking the appropriate balance among market-based, legal, and self-regulatory mechanisms is a delicate task. Canada and the US have both established oversight bodies for the auditors of public companies in an effort to enhance the quality of audits for those companies: the Canadian Public Accountability Board (CPAB) and the Public Company Accounting Oversight Board (PCAOB) in the United States. The two countries deviate, however, in their allocation of regulatory responsibility in relation to the accounting profession, with Canada continuing to rely on a largely self-regulatory model and the US relying almost exclusively on government regulation. This study compares these two approaches to the regulation of public auditors in Canada and the US and offers concrete suggestions for improvement. In particular, this study analyzes and compares the CPAB and the PCAOB, looking at the structure, operation, and governance of the two boards, and analyzing their effectiveness and making recommendations for how they might be improved.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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