Revisiting Auditors Liability for their reports in light of Jetiva and Livent
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
When someone wants information about a company the primary place to go is the annual report. This contains a wealth of data (both financial and non-financial) regarding the performance of a business. One guarantee of accuracy is the statutory audit that must be performed. However, those seeking information may be disappointed. In some cases this is due to a misunderstanding of the nature of audit, which is based on samples and materiality, meaning that an audit does not provide a check on every number in the accounts, and is not a perfect policeman against fraud. In other cases this is due to a failure of auditors to act in accordance with accepted practice, but in such cases tort law may not provide the disappointed party with a remedy. The liability of auditors is a constant battleground. Whilst liability to third parties is relatively settled, both by the decision of the House of Lords in Caparo v Dickman and the liberal use of exclusion notices on the face of the audit report, liability to the audited company and its shareholders is more disputed, particularly in cases of fraud by directing minds. The decision in Stone & Rolls v Moore Stephens provides an unclear basis for refusing compensation to a company damaged by fraud perpetrated by its director, and similar issues have recently arisen in both the UK (Jetivia v Bilta) and Canada (Livent Inc v Deloitte & Touche). Drawing on an examination of case law, accountancy practice and financial statements, this paper seeks to reanalyse the auditors’ duty of care, particularly in fraud cases, in the light of the challenges faced by auditors, financial statement users and the courts.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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