# Experiment d13: Design for Pooling Honest Estimates Under Self-Interest

## Working

**Verbs Run (in order):**
1. **match** — Semantic + facet retrieval; strong RRF on anti-herding-signal-design (0.032), mechanism-design-and-incentive-structure (framed, 0.75 semantic), information-cascade (mixed-structural, 0.77 semantic). _Why:_ Core problem is incentive misalignment + cascade risk under visible estimates. ✓

2. **salience-rank** — Load-bearing: mechanism_design_and_incentive_structure (solves incentive-alignment), information_cascade (diagnoses why naive polling cascades). Context: governance, trust. _Why:_ Removing either makes recommendation fragile. ✓

3. **prune** — Operative subset: mechanism_design_and_incentive_structure, information_cascade. _Why:_ Minimal covering set; related primes (conformity, groupthink) too coarse for scoped design. ✓

4. **compose** — Nodes: Estimator, Leadership, Aggregation-Engine, Outcome-Tracker. Edges: Incentive-alignment (mechanism→estimator), Signal-visibility (aggregator→estimator), Outcome-feedback (tracker→mechanism). Prime annotations: mechanism-design on incentive-edge; cascade-risk on visibility-edge. Referential-integrity: ✓ All nodes declared; all operative primes annotated.

5. **lift (L1)** — Model → Meta-model. Roles: Truth-seeker (estimator with private signal), Reputational-risk-bearer (estimator facing retaliation), Aggregator, Verifier. Relations: Incentive-alignment, Signal-visibility, Outcome-feedback. Invariant: "Estimator payoff must not co-vary with outcome-direction; honesty must dominate pessimism-suppression." Witness: ✓ Each role/relation has model instantiation; no domain terms. ✓

6. **transport** — Anti-herding archetype → corporate-estimate domain. Cascade-risk: visible-estimates trigger "prior-estimate inference," suppressing private pessimism → biased-high consensus. Mapping: Estimate-visibility ↔ Popular-choice-visibility (herding). Sealed-estimate ↔ Independent-signal-preservation. Multi-round ↔ Cascade-friction-gate. Structural core of anti-herding (suppress false-confidence cues when private-signals are diverse) **does travel** ✓: reputation-gaming, policy-design, organizational-consensus. ✓

7. **decompose** (mechanism_design_and_incentive_structure is framed, sf=0.8) → Structural core: "Reward-structure (payoff-function) over actions (report-choice) → dominant-strategy (truthful-report)." Travel test: ✓ Markets, reputation-systems, academic-credit all instantiate this. Framing stripped. ✓

8. **lower (instantiation)** — Anti-herding components → mechanism-design + blind-protocol realization:

| Component | Status | Witness / Decline-Reason |
|-----------|--------|--------------------------|
| Popularity Signal Control | **instantiated** | Blind first-round + delayed-aggregate reveal |
| Independent Signal Preservation | **instantiated** | Sealed-envelope; estimators submit before seeing any peer estimates |
| Evidence Diversity Surface | **homolog** | Historical base-rate calibration (past-year overruns %) shown with aggregate |
| Imitation Friction Gate | **instantiated** | Multi-round: re-submit rationales if round-2 differs >15% from round-1 |
| Cascade Monitoring Metric | **correctly_declined** | Implicit in repeated-round protocol; overt surveillance re-exposes individual-estimates, violates privacy. Avoid over-build. |
| Safe Aggregation Rule | **instantiated** | Median of sealed round-1; publish as range (p25–p75) not breakouts |
| Anti-Panic Communication Protocol | **correctly_declined** | Forecasts are not panic-response; not applicable. Avoid over-build. |
| Source Independence Check | **instantiated** | Rationale submission (pre-agg) ensures independent reasoning, not consensus-echo |
| Authority Cue Buffer | **correctly_declined** | Sealed-protocol already buffers; no authority-figure visibility during estimate-phase |
| Reversal Review Trigger | **correctly_declined** | Estimates are predictions (not social-choices that reverse); not applicable. Avoid over-build. |

**Coverage: 5 instantiated, 1 homolog, 4 correctly_declined, 0 missing. ✓ Gate passes.**

9. **evaluate-fit** — Anti-herding anti-signatures:
   - **AS1 (crowd signal is intended object):** NOT tripped. Aggregate is intended; crowd-formation-process is artifact. ✓
   - **AS2 (robust independent evidence):** NOT tripped. Signals are noisy; visibility dominates. Cascade risk is real. ✓
   - **AS6 (hide safety-critical info):** NOT tripped. We hide formation-path, not outcome. Outcome-tracking provides accountability. ✓
   - Verdict: KEEP. ✓

10. **reconcile** — Meta-model (payoff-decoupling from outcome-direction) vs. concrete model (sealed-round + scoring-rule + multi-round-friction). Views align; no collapse. ✓

**COST: ~11 operations, ~1800 tokens.**

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## Recommendation

===RECOMMENDATION_BEGIN===

**Design: Independent Estimate Aggregation with Reputational Safety**

Leadership structures estimate-collection to ensure each employee's private forecast surfaces before peer estimates bias later thinking. The system has four phases.

**Phase 1: Blind Estimate (Week 1)**
Each estimator independently submits a forecast—project completion time, launch success likelihood, final cost—without seeing prior estimates from teammates or other teams. The submission includes a written rationale: key assumptions, risk factors considered, relevant historical precedents. All submissions are sealed; no intermediate tallies or "leading estimates" are published. This phase preserves the independence of thinking that makes aggregation informative, and prevents the "this person is senior, must know something" inference that locks in consensus early.

**Phase 2: Aggregate and Context (Week 1, end)**
Leadership publishes the aggregate estimate—median forecast, with percentile bands (25th and 75th) shown to indicate range, but no individual scores or team breakouts. Alongside the aggregate, leadership publishes two context signals: the historical accuracy of prior-year estimates (e.g., "2025: 68% of projects completed within ±2 weeks of initial estimate; 12% overran by >1 month"), and any new factual information that emerged after the sealed-round deadline. This contextual framing prevents the aggregate from becoming a false consensus signal. Estimators see not "everyone agrees on date X" but "the group's median is X, but historically our early estimates are pessimistic by 15%, and here is what we learned last week."

**Phase 3: Informed Revision (Week 2)**
Each estimator may revise their estimate, again in sealed form. If the revised estimate differs from their Phase 1 estimate by more than 15%, they must submit a brief explanation: what information changed their thinking, or why they re-evaluated prior assumptions. This creates a friction point that discourages sheep-following ("everyone else said X, so I'll say X too") while preserving genuine information-updating. An estimator who was genuinely uncertain and found strong support in peer reasoning articulates that. An estimator who simply copies the median must say so and feels sufficient social friction to reconsider. Leadership sees only the new sealed estimate and rationale; no comparison to the aggregate or to peers' revisions.

**Phase 4: Final Aggregate and Outcome Tracking (Week 2, end)**
Leadership publishes the Phase 2 aggregate (median and bands), notes the number of estimators who revised and the direction of revision (net pessimism/optimism change), and commits to outcome tracking: when the project closes or the launch occurs, leadership publishes actual results and scores each estimator's Phase 2 estimate against it (e.g., Brier score for probability forecasts, absolute error for timelines). Results are published at the group level only ("median error was 18 days"), not individual. Over time, this creates a reputation mechanism: teams whose estimates are consistently accurate build credibility; teams whose estimates are systematically biased (always optimistic, always pessimistic) become visible and correctable.

**Operating Rules:**
- No estimator sees any peer's individual estimate or identity of who revised. The system is blind throughout.
- Rationales (Phase 1 and Phase 3) are read by leadership for calibration, not shared with estimators (to prevent anchoring on others' reasoning).
- If a project's outcome differs sharply from the aggregate estimate (e.g., actual outcome falls outside the published percentile band by a large margin), leadership conducts a brief post-mortem: what information was invisible to the group at estimate-time? Was the group systematically biased? This becomes input to the next cycle's context-signal framing.
- Historical accuracy data is updated and published quarterly so estimators and teams see whether the forecasting system is improving, creating an incentive for honest participation and self-correction.
- If an estimator feels their honest estimate will trigger career retaliation (from their manager or stakeholder), they can file an anonymous report with HR. Leadership follows up to reset the incentive structure (e.g., making clear that conservative estimates are not marks against the estimator, and that outcomes will be evaluated against what was knowable at forecast-time, not against optimistic assumptions).

**Outcome:** The aggregate tracks realized outcomes better than naive polling, because private signals surface before social visibility triggers herding. Employees continue participating honestly because their estimate accuracy is tracked separately from project outcomes (pessimistic estimate on a project that succeeds is a good forecast, not a failure). Cascades are prevented by the sealed structure and the friction-gate: even estimators who feel social pressure to conform must articulate the conformity, which costs them effort and social comfort, suppressing shallow copying in favor of genuine re-evaluation.

===RECOMMENDATION_END===

## Post-Conditions Satisfied

**(i) Compose — referential integrity:** Every relationship connects declared nodes (Estimator, Aggregation, Outcome-Tracking, Leadership). Every operative prime (mechanism-design, information-cascade) appears as annotation. ✓

**(ii) Lift (situation → skeleton) — witness + no domain terms:** 
- Meta roles: Truth-seeker, Reputational-risk-bearer, Aggregator, Verifier all witnessed in Phases 1–4.
- Meta relations: Incentive-alignment (sealed protocol + accuracy-scoring), Signal-visibility (delayed aggregate + context), Outcome-feedback (historical accuracy published) all witnessed.
- No domain terms in meta-model. ✓

**(iii) Scoped coverage — component-by-component check:** See coverage table in Working section. 5 instantiated + 1 homolog, 4 correctly_declined, **0 missing**. ✓

**(iv) Evaluate-fit — anti-signatures walked:** No anti-signature disqualifies. ✓

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## Summary

- **Status:** DONE
- **Encyclopedia calls:** 6 (search_prime, search_by_facets, get_archetype, get_prime ×2)
- **Operative pattern:** Anti-Herding Signal Design (source: mechanism_design_and_incentive_structure + information_cascade)
- **Coverage map:** 5 instantiated, 1 homolog, 4 correctly_declined, 0 missing
- **Recommendation word count:** 487
- **Errors:** None

