A Measure of Management’s Withholding of Bad News
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We develop a measure of management's withholding of bad news (NBF -net bad flows) based on the relative lumpiness of negative daily abnormal stock returns in the fiscal period.We present an extensive set of tests that support the construct validity of NBF as a measure of management's bad news withholding.Being calculable for listed companies using daily stock return data, NBF can complement direct scores of corporate disclosures when assessing the overall quality of corporate financial communication.We also compare the properties of NBF with the properties of measures of stock price crash risk.We find that NBF outperforms traditional crash risk measures in capturing bad news withholding.Re-estimating the crash risk measures using daily instead of weekly stock returns yields more powerful proxies for bad news withholding that are more closely related to NBF.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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