Regulatory Approval and Biotechnology Product Disclosures*<sup>†</sup>
Bibliographic record
Abstract
ABSTRACT This study examines the effect of regulatory approval on a firm's voluntary product‐level disclosures. We focus on the US biotechnology industry, a setting that allows direct observation of whether firms disclose more information as products proceed through well‐defined—though successively more complex and costly—regulatory hurdles. Consistent with predictions motivated by biotech firms' need to repeatedly raise capital, we find that firms disclose more as their products move to later stages in the development process, both when the products receive regulatory approvals as well as when they receive regulatory denials. In addition, these findings are consistent across phases of development as well as product disclosure categories and are accentuated for firms without internal sources of capital (i.e., lacking product revenue). Collectively, these findings reveal that biotechnology firms respond to the considerable incentives to provide enhanced product disclosure and thus facilitate their ongoing need for capital to proceed through subsequent stages of product development.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".