Decentralized Contribution Reward Network (DCRN)


What? & Why?


The foundational principle behind creating the Decentralized Contribution Reward Network (DCRN) is to encourage high-quality involvement in Uniswap Improvement.

The primary way to do that is to facilitate both part-time and full-time quality voluntary engagement of contributors through an Open Network.

This initiative’s main goal is to create an infrastructure that fosters building and to grow the Community of Uniswap builders.

If successful, DCRN could function as a magnet for active Uniswap contributors who are eager to collaborate. If it does, it could become a giant help center for everything Uniswap related, from development to adoption.

Once functional, DCRN can:

  1. Help Uniswap Community with Proposal development from start to finish
  2. Incentivize deliberation in Governance forum discussions
  3. Hire a set of professional auditor teams to verify that Proposals are safe
  4. Hire professionals from outside to consult on, improve, and help execute the Community’s suggestions.
  5. Provide feedback on contributors activity, including microgrant rewards for sporadic contributions
  6. Distribute reward grants to successful pro bono projects on top of Uniswap
  7. Create and support an Auditors Network to check token contracts added to Uniswap, identify scammers, and warn the Community.
  8. Etc.




1. DCRN Internal Reward Procedure.

First and foremost, DCRN is an Open Network: everyone can become part of it.

At the end of each month, all contributors submit a reward application. This application summarizes their input they deem valuable and provides links to prove it.

The Reviewers Network examines the applications and assigns the rewards: UNI + Voting power in DCRN’s decisions.

The idea is: Quality contributions rule the Network.

There is one principle, though, that needs to be universally accepted by the applicants:

Participants make their contributions voluntarily and agree to receive no rewards if that is the Reviewers Network’s decision.

There is a cap on how much UNI + Voting power an individual contributor can receive. It is defined in relation to the benchmark reward.

100% of the benchmark reward is what Reviewers receive for their work.

As a result of their contribution’s evaluation, participants can receive between 0% and 300% of the benchmark reward. The reward system allows for composability. For example, a reviewer can also develop an app and provide consultations in the developer network’s channel.

Example: Alice

Alice has been active in Uniswap Discord community chat support and posts her application:

'Last month, I was providing chat support full-time, correctly answering 1000+ questions on Uniswap Discord + I’ve helped to update the FAQs.

My self-proposed reward is 1500 UNI.’

Three Reviewers are randomly chosen to review Alice’s application. They verify the quality and relevance and that according to the guidelines, 1500 UNI is the right reward for this type of activity.

Alice receives her UNI when one of DCRN’s multisig addresses distributes monthly rewards. Benchmark was set at 3000 UNI, so she is also granted 50% voting power in DCRNs decisions for the next month

DCRN needs to be inclusive, so voting power resets every month.

Participants can still mention their previous contributions to get cumulative effects, but it will be up to Reviewers to decide the weight of those.

We also need to introduce a minimum threshold to qualify for a reward. Otherwise, the Network can get spammed with applications for small contributions from multi-accounts.


II. DCRN’s Governance


The Network functions appropriately if its members participate actively in DCRN’s governance processes. This applies both to internal and external reward distribution processes.

Internally, the guidelines for the Reviewers Network need to be set and refined continuously. It is also helpful to define what directions of contributors’ work are considered more promising.

Both internal policies and external fund distributions need to be approved by the overwhelming majority of the Network’s voting power.

The vote is anonymous, and the results are hidden before the procedure is over. No additional token is needed.

When a proposal reaches the stage of voting, DCRN participants have four options to choose from:

a) YES

b) NO



The system’s key feature is that the minority has the right to veto and delay the decision. If we define the consensus as 70% approval, and more than 30% of the voting power rejects the proposal, the request is denied.

‘Not Sure’ means that voters have not formed a strong opinion yet. It signals that there is a need for an additional discussion.

‘Neutral’ means that the voters have formed an opinion and decided to abstain from voting actively. It brings an entirely different signal to the table than not voting: it approves all three possible scenarios.


DCRN is a distribution network that encourages the collaboration of participants with different views. It is not a political party, and its treasury funds should never be used to vote.

DCRN has a watchman: it’s the Uniswap Governance. If the Network transforms into something it’s not intended to be, UNI holders can cease its funding.

Having a watchman allows the opportunity for the Network to be somewhat decentralized from day 1.


Thank you for reading.

I will follow up with specifics on the Reviewers Network processes, the benchmark reward, and on the way to bootstrap DCRN soon.

If you find the ideas interesting, please share (retweet, medium it).


Do you approve the creation of DCRN?
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  • No
  • Neutral
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Would you like to participate in the Testnet phase?
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uygun olabılır sankı

New reward model for DCRN

I’d like to introduce a new model for DCRN’s rewards.

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.