Express Yourself: Why Managers' Disclosure Tone Varies Across Time and What Investors Learn from It
Bibliographic record
Abstract
ABSTRACT We argue that volatility in a manager's disclosure tone across time should be a function of two components: (i) the firm's innate operating risk and (ii) the extent to which the manager's disclosure transparently reflects that risk. Consistent with this argument, we find that both operating risk and disclosure transparency are important determinants of disclosure tone volatility. We then examine whether investors incorporate the incremental information provided by disclosure tone volatility into their assessments of firm risk. If disclosure tone volatility primarily provides investors with incremental information about a firm's operating risk, we should find a positive association between tone volatility and market‐based assessments of risk. On the other hand, if disclosure tone volatility primarily provides investors with incremental information about a manager's disclosure transparency, we should find a negative association between tone volatility and market‐based assessments of risk. Consistent with an operating risk explanation, we find a positive association between disclosure tone volatility and market‐based assessments of firm risk after controlling for a comprehensive set of proxies for operating risk and transparency. We find little support for an information risk explanation, even when we examine multiple measures specifically designed to capture information risk. Taken together, our results suggest that although disclosure tone volatility is a function of both a firm's operating risk and a manager's disclosure transparency, investors appear to respond as if disclosure tone volatility only provides incremental information about a firm's operating risk.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.015 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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; both teacher heads agree on what is shown here.
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".