Reflections: Rewarding the Gauss Community

Many Web 3.0 projects use reflection (redistribution) mechanisms in their token economics. They are used almost exclusively for promotional reasons. Similarly, a number of projects use hyperinflation and token burning to generate hype. Gauss will incorporate a reflection system for several reasons. The first – and most important – is to reward our community as it grows. The second reason is to explore the reflection function and study the way it influences behavior in a live ecosystem. After two years, we will aggregate the data from observing the reflection mechanism and publish a paper to share our findings. Reflection minimizes volatility by incentivizing members of the Gauss Ecosystem to maintain a balance of GANG. The system places a higher weighted value for smaller holders, encouraging more people to participate in the ecosystem. To accomplish this, the reflection pool (r) is split into two parts and distributed based on individual holders’ wallet balances (x). This happens multiple times per day. One part of the reflection pool is disbursed directly proportional to x, relative to its portion of all x (c). The rest of the pool is dispersed based on the square of each wallet (y), relative to its portion of all y (s).

To illustrate, imagine an apple pie. Let’s say the pie has ten slices, and there are nine people at the table. Each person gets a slice – this represents their wallet. The remaining slice is the reflection pool. Each person’s slice of pie (x) is an arbitrarily different size, but taken together they would still represent nine of the ten slices (c). The tenth slice is cut in half. The first half is handed out according to how large each person’s first slice is; (x/c)*0.5r. The second half is distributed based on the square of each person’s first slice, adding more ‘weight’ to smaller slices; (y/s)*0.5r. We want to distribute the tenth slice (r) in a manner that provides a bit more pie to each person who has a smaller slice than they would receive if it were split proportionally to the size of their first slice. This way, when a new person joins the Gauss Ecosystem, they are incentivized with reflections even though they may not have significant holdings. Rewards are distributed more evenly, rather than simply accruing to whoever has the largest wallet.