Bibliographic record
Abstract
Abstract Prior literature and anecdotal evidence, most recently provided by allegations relative to Enron, Global Crossing, and WorldCom, suggest that failing firms (defined here as prebankruptcy firms) may be motivated to engage in fraudulent financial reporting to conceal their distress. I examine two research questions: (1) Are failing firms' prebankruptcy financial statements more likely to exhibit signs of material income increasing earnings manipulation than those of nonfailing firms? (2) Do auditors detect the overstatements in firms that they perceive to be failing? I predict and find that as (ex post) bankrupt firms that do not (ex ante) appear to be distressed approach bankruptcy, their financial statements reflect significantly greater material income‐increasing accrual magnitudes in nongoing‐concern years than do control firms. The accrual behavior of these firms resembles that of bankrupt firms that the Securities and Exchange Commission (SEC) has sanctioned for fraud. Like sanctioned firms, the nonstressed bankrupt firms display significantly greater (material) increases in receivables; inventory; property, plant, and equipment; sales; net working capital, current, and discretionary accruals in prebankruptcy nongoing‐concern years than do control firms. They also display significantly more negative changes in cash flows from operations and net cash and a greater disparity between accrual‐based net income and operating cash flows than do control firms, consistent with Lee, Ingram, and Howard 1999. Finally, I predict and find that these firms' going‐concern years reflect evidence consistent with auditor‐prompted reversal of previous overstatements. These results are based on parametric and nonparametric tests for various subsample combinations drawn from a sample of 293 bankrupt firms representing approximately 2,500 observations.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".