Should You Offer a Job to Your External Auditor?
Bibliographic record
Abstract
This article discusses the significance of external auditor. Companies searching for financial and accounting talent to join their senior executive teams often lure partners and other professional staff away from accounting firms that perform their annual audits. Livent Inc., the Toronto-based producer of Broadway shows, recently faced this exact problem when a former professional of its external audit firm joined Livent as a member of the financial executive team, and allegedly became enmeshed in a financial reporting fraud.Although there are risks associated with hiring an individual from the external audit firm's staff, companies routinely hire ex-auditors to fill numerous types of company positions. Most of these employment relationships benefit both the company and the ex-auditor, with no decline in the quality of financial reporting. Clients often prefer to hire former employees of their audit firm because former auditors typically possess numerous attractive attributes. The level of training in an audit firm, and exposure to both numerous types of businesses and to complex accounting and financial transactions provide valuable experience.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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; both teacher heads agree on what is shown here.
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".