Investors' Interpretations of Imprecise Standards and Their Perceptions of Earnings Management by Reputable Companies
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Standards with imprecise guidelines require interpretation by users. In this study we investigate how investors' perceptions of earnings management vary with their interpretations of imprecise standards and the type of company reputation. We design a quasi-experiment that exploits the role of the press as a “watchdog” of corporate activities to focus the attention of investors on the financial reporting practices of companies. The results show that both factors interact to influence investors' perceptions. Investors, whose interpretations of the imprecise standard are inconsistent with that of the company, are more likely to suspect earnings management when the company has a financial rather than non-financial reputation. Investors in the inconsistent/financial reputation condition are also more likely to sell their investments than those in the inconsistent/non-financial reputation condition. The type of reputation does not show a significant effect on investors' perceptions when investors' interpretations are consistent with that of the company. JEL Classifications: M40; M41.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it