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EIP-13: Vouching Recalibration

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Written by node
Updated over 3 weeks ago

EIP-13 was implemented on the 5th of November 2025.


🎯 Motivation & Purpose

Some users have discovered that getting lots of 0.01 ETH vouches from many people can “speed-run” their Ethos score.

While broad community support should matter, this created a vulnerability: anyone with a large group of small backers can inflate credibility.

This update reduces artificial score inflation from fragmented, minimal vouches while preserving legitimate community support.

It aligns voucher count with economic substance (skin-in-the-game).

Outcomes

• Lower marginal gains from minimal vouches

• Scores better reflect real vouched ETH and commitment

• Acceleration from vouched ETH is slightly dampened

• Number-of-Vouchers impact now scales by backing quality, not raw count

⚙️ Specification

1️⃣ Vouched ETH Curve Hardening

• Element: Vouched Ethereum Impact (range [0 – 270])

• Inputs:

 – ETH-days = amountETH × min(daysActive, 180)

 – totalEthDays = sum across active vouches

• Parameters:

 – accumulationMultiplier = 2.0

 – pace = 45

 – maxVouchedEthDays = 180 (unchanged)

• Mapping:

 – effectiveEthDays = totalEthDays ÷ 2.0

 – score = sigmoid(effectiveEthDays, pace = 45) → [0, 270]

• Effect:

 – Slower early growth and delayed saturation → smaller gains from low, short vouches.

2️⃣ Voucher Ratio Sigmoid

• Element: Number of Vouchers Impact (range [0 – 270])

• Inputs:

 – stakedEth = total active vouched ETH

 – vouches = count of active vouches

 – multiplier = population-calibrated ratio factor

  ↳ Rises when ETH-per-voucher is strong; falls when many vouches are weak.

• Parameters:

 – pace = 25 (fast pace)

• Mapping:

 – effectiveVouchers = vouches × multiplier

 – score = sigmoid(effectiveVouchers, pace = 25) → [0, 270]

• Effect:

 – Raw voucher count is tempered by economic substance — many weak vouches contribute less.

🧭 Rationale

This is part of Ethos’ ongoing calibration cycle.

Vouched ETH and voucher mechanics will continue evolving as users find new ways to optimize reputation.

This adjustment reflects lessons learned over the past 9 months — it strengthens credibility integrity without penalizing genuine, high-conviction support.

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