I’d like to introduce a new model for DCRN’s rewards. This article expands the ideas laid out in the previous post.
In the initial model, the initiative for rewards comes from Contributors.
In the new model, Reviewers propose a method to reward Contributors and then execute it with DCRN’s approval.
DCRN’s governance decides if a particular type of contribution should be rewarded and to what extent.
Here’s the list of major changes and some reasoning behind them.
1. Abandoning the application model.
== From ‘Contributors invite themselves’ to ‘Reviewers invite Contributors’
The main problem with the application model is that it creates an entry barrier to DCRN:
Contributors have to ‘invite themselves’ to the Network and assess themselves.
A much more viable model, in my opinion, would be the one where Reviewers Network invites Contributors to join DCRN by assigning rewards to them.
The less effort is required from Contributors, the larger and more decentralized the Network can be.
With the new model, Contributors’ activity as part of DCRN mostly comes down to voting on important strategic decisions:
- on approving reward methods and execution of these methods
- on defining specific amounts of UNI and voting power to reward
== From application-first to method-first.
With the application model, input Reviewers Network has to assess can get quite heterogeneous. In practice, it would mean that the quality of reviews would suffer.
An alternative approach to application-first is method-first.
This way, Reviewers begin with developing a method to assess a particular type of contribution. And only DCRN’s approval of the method unlocks the Reviewers Network’s ability to use it.
== From monthly unified rewards to DCRN’s programs
Abandoning the application model allows for much more flexibility when it comes to different types of contributions.
Instead of combining all contributions into one metric, it occurs to be better to develop various programs with different reward criteria and allocate a set budget for each of them.
2. The new role of the Reviewers Network.
== All strategic decisions are made by DCRN’s governance
In the initial model, DCRN was an open network, and the Reviewers Network was invitational. In the new model, these roles reverse.
Anyone can become a Reviewer now, propose a method, and execute it.
And by doing so, the Reviewer helps to reward Contributors and invites new voting power to the DCRN.
In the initial model, Reviewers were similar to the jury. And the Reviewers Network had the power to assign both the rewards and the voting power.
In the new model, all strategic decisions are made by DCRN.
This means that Reviewers are now functioning more as:
a) Recruiters. They provide a method and execute it, bringing new members to the Network.
b) Mediators between DCRN and rewarded contributors. DCRN decides which group of contributors to reward, and the Reviewers Network provides the expertise to do it appropriately.
3. Changes to voting power.
== From monthly voting power resets to Cumulative voting power
The idea behind monthly voting power resets in the initial model was to mitigate the disproportional weight early network participants would get if DCRN would start from scratch, with a low number of participants.
As there seems to be a way to bootstrap DCRN as a decentralized entity with a higher number of participants from day 1, this mechanic is no longer needed.
In the cumulative voting power model, all the voting power participants get over time sums up. This model still incentivizes continuous participation but doesn’t disenfranchise past contributors.
== Assigning various amounts of voting power.
It also makes sense to deviate from the model where the voting power is tied 1:1 with the UNI contributors receive. So that DCRN could assign the UNI reward and the voting power that comes with it separately. This could be handy with grant distributions when the Network wants to reward Contributors with more UNI than voting power.
Another thing DCRN could do is to invite potentially valuable Contributors who are known as good actors by sharing voting power with them. And then to reward these Contributors as they provide the expertise the Network lacks.
A good example of this practice would be to invite people from Ethereum Foundation.
== Deciding the specific amounts of UNI to reward by using median results.
When there is no set reward amount, DCRN can decide it by voting, when all the Network participants enter the amount they find appropriate.
A good example of that would be a vote to reward the Reviewers’ labor or retroactive rewards in general.
Using median results of this type of vote instead of average results seems more promising.
When we use an average of the numbers suggested, votes for extreme results gain more weight. Using the median allows everyone to vote for the preferred outcome without additional considerations.
==
The most efficient way of bootstrapping DCRN I can currently think of is through the Uniswap Governance forum. I will expand on it later.
Cheers.
