Proportionate Liability Under the CBCA in the Context of Recent Corporate Governance Reform: Canadian Auditors in the Wrong Place at the Wrong Time?
Bibliographic record
Abstract
In the recent Canada Business Corporations Act amendments implementing a proportionate liability scheme, auditors appear to be winners. This is consistent with the trend in the past several years as a result of which Canadian auditors have been successful in narrowing the scope of their liability both through legislation and through common law. Going forward, however, it is fair to say that auditors will be losers unless the accounting profession re-evaluates its role and responsibilities to its stakeholders. Given the accounting and corporate governance scandals North America has witnessed in the past few years, as well as the actual and anticipated regulatory response in Canada, the scope of auditor liability is bound to expand once again.
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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 | 0.014 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.018 | 0.022 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".