Executive Team Incentive Heterogeneity and Information Suppression
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
ABSTRACT We examine whether the equity incentive heterogeneity of the executive team engenders a positive externality by curtailing stock price crash risk. Supporting this prediction, we find a negative relation between the equity incentive heterogeneity of the executive team and stock price crash risk. Our strong, robust evidence implies that this equity incentive heterogeneity plays a major internal governance role in preempting corporate bad news hoarding activities. In additional analysis, we show that the relation between equity incentive heterogeneity and crash risk is stronger for firms experiencing severe agency conflicts and poor governance. Collectively, our results lend empirical support for the importance of developing a heterogeneous equity incentive structure to deter corporate misbehavior, which, in turn, constrains stock price crash risk.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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