How Metrics-Based Voting Changes the Governance Game
summary
A metrics-based voting system assigns funds by combining measurable signals (TVL, token value, active users, developer engagement) with voter-chosen metric weights, then aggregates them by mean/median/quadratic/approval rules. A complexity analysis finds approval voting is most robust against manipulation. Applied to Optimism data (230 projects, 10M OP ≈ $20–25M), caps (min threshold and 500k max) shift top allocations by up to about $1M per project; algorithmic rankings (TVL/users/fees) also diverge from expert rankings for specific tools.
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chapters (9)
- 0:00Metrics-based voting intro
- 1:25Funding challenges now
- 3:27How metrics-based voting works
- 8:25Designing metrics-based voting
- 10:28Robustness against attacks
- 14:47Allocation methods impact
- 19:50Do metrics reflect impact
- 26:25Metrics-based voting potential
- 29:50Conclusion and future
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