# jeff
## 1. control for team!
**Current H3 (Ξ²β):** `Vagueness Γ SeriesB Γ High_Integration_Cost` β tests if reversal is stronger in hardware vs software.
**Jeff's alternative (not in your model):** `Vagueness Γ SeriesB Γ Founder_Credibility` β tests if reversal only works for credible founders.
These are **different mechanisms**:
- **Your H3**: Reversal depends on technical uncertainty (hardware = high discovery cost)
- **Jeff's idea**: Reversal depends on social capital (prior exits = trust to be vague)
Your file already has `Founder_Prior_Exit` as a **control**, not a **moderator**. Jeff suggests it should be tested as a moderator instead of (or in addition to) integration cost.
You could test both:
- Model 2A: `Γ High_Integration_Cost` (your current H3)
- Model 2B: `Γ Founder_Prior_Exit` (Jeff's suggestion)![[Jeff empirical guru guidance on hidden commitment cost_otter_ai (1).txt]]
**Core Guidance:**
- **Mechanism**: Vagueness = flexibility (no rigid expectations). Founders with **credibility signals** can be strategically vague, forcing investors to bet on the team, not the idea.
- **Data**: Use existing certitude score from org science paper. Pitchbook fine.
- **Model**: Simple logistic regression:
- DV: `Funding_Success` (0/1)
- IV: `Vagueness` (100 - certitude)
- Interaction: `Vagueness Γ SeriesB`
- Controls: founder experience, team size, industry FE
- **Tables**: Show progression (vagueness-only β + controls) to prove robustness
**Implemented:**
- β
Logistic framework
- β
Panel structure (A β B)
- β
Interaction term
- β
Pitchbook data
**Not Yet Addressed:**
- β οΈ Certitude measure (need to verify org science paper = LIWC)
- β Credibility as mechanism (Jeff emphasizes this; we test integration cost instead)
- β Table progression (only final models, not intermediate)
- β Endogeneity ("why choose vagueness?" - selection bias unaddressed)
**Key Quote:**
> "Strategic mechanism in being vague...force investors to invest in the team, not the idea. Lowers likelihood of getting funded, but conditional on funding, increases likelihood of delivery."
**Actions:**
1. Check org science vagueness measure vs our LIWC
2. Add: `Vagueness Γ SeriesB Γ Founder_Track_Record`
3. Build: Model 1 (vagueness) β Model 2 (+ controls) β Model 3 (+ interaction)
---
## #scott (Hart Posen - Paper Structure Advisor)
**Implemented:**
- β
Formatting (no subsections in intro)
- β
Simplified game (2-player: entrepreneur + customer)
- β
One idea focus (strategic ambiguity)
- β
Mean/variance separation
**Not Yet Addressed:**
- β οΈ "Explain to your mom" simplicity (still technical)
- β οΈ Remove exogenous probability critique (deleted Section 1.2 but philosophy persists)
- β Actual intro (hypothesis.md β paper intro)
**Quote:**
> "A paper is an argument for ONE thing, not 10."
**Action:** Lead intro with "vague promises paradox", not Bayesian machinery.
---
## #unknown_speaker (from document 8 - YC/CDL pitch deck mining suggestion)
**Core Guidance:**
- Sample 20-30 firms from one domain (clean energy, AI drug discovery)
- Mine pitch decks, code vagueness via LLM
- Track Series A β B with CrunchBase
- Model: Strip to 1/3 symbols, derive optimum, explain deviations (agency/bounded rationality)
**Status:** Partially implemented (Pitchbook replaces YC/CDL, but same logic)
---
## Combined Gaps
**Critical:**
1. Jeff + Unknown both want **credibility** tested, not just integration cost
2. Model too complex (9 variables) - contradicts "proof of concept" guidance
3. No table progression (vagueness β + controls β + interaction)
**MVP Priority:**
1. Verify vagueness measure consistency
2. Test credibility alongside integration cost
3. Simplify variable count (drop less critical controls)