GM-03: Trustful - Verifiable Reputation Aggregator #11
jackhack00
announced in
R&D Backlog
Replies: 0 comments
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
-
Title
Trustful - Verifiable Reputation Aggregator
Abstract
A reputation system that values effort over economic power, fostering collaboration and neutral credibility.
Motivation
The current approach of relying on token ownership for voting and participation has led to decreased community engagement among members who are passionate about their communities. Additionally, individuals are less motivated to join new communities, fearing the time and effort it would take to establish their reputation from the ground up.
Introducing Trustful, a verifiable and interoperable reputation layer that addresses these challenges by establishing a framework where your contributions are acknowledged across different organizations and ecosystems. This system empowers you to influence the community you are dedicated to, not based on economic power or tokens you possess but on the level of your commitment and efforts towards the community's future (Valocracy).
Problem Statement
Absence of an equitable community currency: A community coin can be created by taking reputation into account; economic value may be considered, but reputation can be part of the governance equation.
Potential Applications
Similarly, voters in the grant process can have reputation badges. Community voters with higher reputation and active participation in the ecosystem can better recognize the ecosystem's needs and thus wield more voting power when making decisions.
This approach not only ensures a fairer resource allocation but also generates additional benefits:
For example, a user with 400 tokens would typically have more voting power than someone with fewer tokens. However, if another user with only 200 tokens has earned multiple reputation badges, the modular system could allow the DAO to define a reputation multiplier. For instance, if the DAO sets a multiplier of 5% for users with more than 50 reputation points, the voting power would increase accordingly.
Calculation Example:
For User B, the reputation multiplier would add 10 tokens worth of voting power (5% of 200 tokens), resulting in a total of 210 tokens in voting power.
In this scenario, while User A has a higher base token count, User B's accumulated reputation allows them to close the gap, ensuring that their contributions and commitment to the ecosystem are recognized and rewarded in the governance process. This approach promotes a more equitable and inclusive decision-making process within the DAO.
Copyright
tbd
R&D
Requirements
Add Requirements here. Requirements are concrete needs and constraints that the proposed GM needs to fulfill to be considered succesful.
List of prior implementations and links to prior research
This reputation aggregator also has an EVM version that aims to be cross-organization, providing seamless interoperability across various chains and different DAOs or/and organizations.
The Trustful contract created initially for ZuVillage Georgia allows users to receive and manage attestations (using EAS), contributing to a verifiable reputation system. The contract integrates with various on-chain and off-chain data sources to ensure accurate and trustworthy reputation metrics.
Key Features
Decision on acceptable solution (space) with rationale
Describe the what an acceptable (or non-acceptable) solution looks like and why this decision was made. Closely related to requirements, this section argues for a particular solution space.
Development
Specification
Provide a specification for the GM. The specification describes the GM, how it functions and how it fulfills its objectives and requirements.
Implementation Instructions
Describe the steps needed to implement the GM, such as decisions that need to be made (parameters, parts, etc) or any related interfaces or data sources the GM might need.
Tuning Guidelines (list of tuneable params and associated understanding)
Describe the various parameters that can be set for the GM and describe what they do.
Description for simulations (or reference implementation, for example in python)
Describe how the GM can be validated, such as through a provided reference implementation, a toy model, or similar.
Beta Was this translation helpful? Give feedback.
All reactions