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 This paper studies managers' preferences among information acquisition and disclosure policies when their firms are required to engage in “real‐time” or “continuous” financial reporting. The paper predicts that for many, but not all, processes describing the distribution of their firms' cash flows, when subject to such reporting requirements, managers will engage in disclosure “bunching,” that is, they will bunch the discretionary component of the information they acquire and disclose into a single point in time rather than spread the acquisition and disclosure of that information over time. We show that managers' preferred bunching period depends on managers' strategy for trading in their firms' shares, managers' risk aversion, the risk premium the capital market attaches to firms' shares, and the size of managers' initial ownership stakes in their firms. We also study and characterize how the equilibrium prices of firms' shares vary over time and also how managers' optimal trading strategies vary with their most preferred “bunching” strategies. Several extensions confirm the robustness of the optimality of disclosure “bunching.”
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.032 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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