Aura is a countermeasure against Sybil attacks, but the only other weakness of Quadratic Funding, resistance to collusion, is currently Pairwise coordination subsidies by Vitalik.
Others, such as How to Attack and Defend Quadratic Funding There is also a pattern of using data science, led by BlockScience, as shown in , but I propose a new layer.
We have published a draft of a white paper on a protocol called DeCartography that outputs data from the Plurality social graph as an oracle.
A longer version can be read here
Here is a summary
This prevents collusion, or perhaps it would be better to call it "Plurality Quadratic Funding.
Precisely, it reduces voting power from similar clusters.
This ideology is based on “Plurality” which coordinates across the following differences
- How Soulbound Tokens Can Make Gitcoin Grants More Pluralistic
- 50 actually independent thinkers are worth more than 1000 NPCs who all consume the same media and vote the same way
- Regenerative Society
- Why I Am a Pluralist - RadicalxChange
I don’t know if the concept of “distance” is used in the current Gitcoin Grants for Pairwise coordination subsidies, but by establishing a contrasting position with “services that automatically create social graphs from transactions,” the Gitcoin FDD team is able to create a social graph that is more personalized, more relevant to the needs of the community, and more effective. I think we can provide data to Gitcoin’s FDD team.
service that automatically creates social graphs from transactions
- Gitcoin(BlockScience)
- Bubblemaps
- Breadcrumbs
- LensProtocol(?)
Simply put, we ask people to answer “Is this wallet address similar?” by comparing two transactions or .
To draw this into a two-dimensional map like a social graph, when n people vote on each simple question, each opinion is tied to an n-dimensional value. By clustering them, the Assumpution can be dropped into a single social graph.
Generate the coordinates of the consensus on the Assumption.
Assumption" here refers to the decision "Is this wallet similar (similar community)?
In this case, there are only two options, Yes or No, but I think this alone will prevent some degree of collusion.
The image is an earlier prototype, with the tags as choices. This is how the two addresses are lined up, with the question, “Are these two similar?” would be a good question to ask.
If more than 51% of the respondents give the same answer, we will simply use that answer as the decision. Actual adjustments would need to be made. For Civil Attack, we of course recommend using Gitcoin Passport.
This is because, as you may know if you are familiar with consensus systems as well as PoS, I believe it will settle at Schelling Point.
In this case, I expect that the Assumpution will settle on “roughly like this” and when they are separated, we can create coordinates with some accuracy
- Nash Equilibria and Schelling Points
- SchellingCoin: A Minimal-Trust Universal Data Feed | Ethereum Foundation Blog
As for aggregation, I wonder if Pol.is could adopt a method to help find consensus.
- The Computational Democracy Project | The Computational Democracy Project
- https://blog.pol.is/pol-is-in-taiwan-da7570d372b5
- If n people interpret an opinion, n dimensional values are tied to the opinion (clustering with dimensionality reduction)
-
The machine learning that’s done, in pol.is, is done in real-time, and we do clustering, just like you would have in a recommender engine, Except that pol.is visualizes the groups
The data that DeCartography can provide as Oracle should look something like this!
As for what attributes people are donating with Gitcoin Grants, Towards a Pluralism Passport Built from DeSoc Legos, but we may be able to map this.
Then we could incorporate the concept of Social Distance.
This may be a promise of Quadratic Land, but I think many people may not understand this Plurality Quadratic Funding at first, so it would be good to have an educational site like this.
Concepts like this Relation Oracle, and Weight Oracle could become the new Plurality identity.
Thanks to DisruptionJoe, _sgtn for their reviews.