Bibliographic record
Abstract
The new International Ethics Standards Board for Accountants (IESBA) standard on noncompliance with laws and regulations (NOCLAR) has been adopted by over 100 countries, including Canada and Mexico and is well on the way to becoming the global standard for accounting ethics. U.S. accounting professionals may become subject to the IESBA standard by working in a country or jurisdiction that has adopted the standard, working as part of a professional network that has adopted the standard, or performing services for a company that is part of a group governed by IESBA standards. While the IESBA standard resembles U.S. standards, it is more inclusive. U.S. standards exclude from consideration illegal acts (similar to NOCLAR) that do not have a material effect on the financial statements, while IESBA standards includes NOCLAR even when not material. Accounting professionals should recognize that they may have broader responsibilities for resolving NOCLAR when working under IESBA standards. © 2017 Wiley Periodicals, Inc.
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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 | 0.020 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".