Enter quadratic voting

In this latest round, we aimed to not only make the experience better by increasing the amount of bounties and time available, but also tried out a new judging mechanism for our Open Track bounties. Specifically, we experimented with quadratic voting.

This article is a retrospective on the quadratic voting process as a hackathon judging mechanism. We dive into:

Codeless Conduct is a no-code hackathon series aimed to onboard non-technical contributors into web3. Our mission is to be top-of-funnel for fresh talent to discover opportunities and make their first contributions to existing projects in the industry.

The event offers workshops by industry mentors in the fields of design, community building, marketing, data/analytics, tokenomics, and governance. These were then paired with related bounties for participants to tackle.

There are 2 types of bounties:

Within each track, we limited the variability of submissions by providing options of tasks participants can work on.

Since Open Track bounties are more open ended in terms of scope, and required comparing apples to oranges, we looked for a way to ensure that judging was somewhat decentralized, representing more voices than just the Codeless Conduct team.

In the first edition of Codeless Conduct, we allowed everyone in the community to vote using Discord reacts. With this mechanism, each participant was allowed to vote on any number of projects once (including their own). The prize pool was split evenly among 5 submissions which received the highest number of “votes”.

This method, though community-driven, had several shortcomings:

So we looked for ways to improve the judging process for open track bounties…

Each participant is given a number of “voice credits” that can be used to vote for a submission. The first vote costs 1 credit, but each additional vote incurs a quadratically increasing cost. For example, the second vote costs 4 credits, the third vote 9 credits, and so on following this formula:

Cost to the vote = (number of votes)²

QV addressed the above issues for Open Track judging by:

For each Open Track (7 in total), we had a judging panel consisting of 3 members of the Codeless Conduct team and 2 community members — making up 35 judges overall.

Community judges were volunteers, with the only criteria being that they must not have had a submission for the track they were judging for.

Each judge was allocated 99 vote credits that they can assign to submissions they deemed to be best per the judging guidelines.

After all judges have submitted their votes, the QV tool produced a results breakdown ordered by number of votes received.

We imported results into a spreadsheet and performed the following calculation:

The prize pool was then split amongst winners pro-rata to the amount of votes they received.

While QV is still a relatively niche mechanism, it offers a way in which community members can express how they feel about an issue in addition to the strength of their preferences. The concept takes a bit of time to grasp, but once understood, can encourage community members to be more engaged in the decision making process as they can express their preferences in a more meaningful way.

Thank you again to all those who participated this round of Codeless Conduct. We certainly learned a lot from the organising side and can’t wait to deliver a better experience this time. If you’re interested in helping put on the next edition of Codeless Conduct, please reach out!

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