An Analysis of the Explanatory Paragraphs of Auditors’ Going-Concern Reports and Footnotes of Bankrupt Companies Under SAS No. 59
Bibliographic record
Abstract
This paper has two main objectives. The first is to analyze the explanatory paragraphs of the audit opinions and footnotes to the financial statements of 112 US bankrupt companies under SAS No. 59 for the years 2001, 2002 and 2003. The other objective is to present the Going-Concern (GC) conditions and events that were identified under the four categories suggested by SAS No. 59. The sample consists of 36 construction companies and 76 manufacturing companies. The results indicate that the companies in the Non-GC (NGC) group seem to be in a better financial position than the GC group. In terms of timeliness of the audit reports, the GC group comes out better. Also, the GC group discloses more GC conditions and events than the NGC group. Eighty-two companies (73.21%) received a GC opinion while 30 companies (26.79%) received a NGC audit opinion. Seventy-four companies (66.07%) remain active while 38 companies (33.93%) remain inactive. The results suggest that auditors follow the guidelines of SAS No. 59 more closely when issuing a GC opinion.
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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 | 0.005 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".