You are Known by the Directors You Keep: Reputable Directors as a Signaling Mechanism for Young Firms
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we develop an analytical model of outside directors' signaling role—a role that is especially important for entrepreneurial firms. We formally demonstrate that in the face of a market failure in which stakeholders refuse to align themselves with new firms, high-quality new ventures may be able to credibly signal their type by appointing reputable directors to their boards. However, this option is not universally feasible. Both directors' reputations and the quality of their information determine the effectiveness of this strategy. In contrast to earlier adverse selection models, we demonstrate that when the middlemen (directors) have incomplete information on firm quality, bad and good firms can coexist in equilibrium. In this equilibrium, the quality of the directors' information determines the mix of good and bad firms in the population of surviving firms. Avenues for future research and normative implications for practitioners are discussed.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| 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