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๐Ÿ”„ Alternative Systems: Beyond 1T1V

Explore reputation-based, conviction, and time-weighted voting

Understand how voting power is calculated

๐Ÿ”„ Alternative Voting Systems: Beyond Simple Token Weighting

Recognizing that one-token-one-vote creates plutocracy, some DAOs experiment with alternative weighting systems. The goal: maintain Sybil resistance (you need tokens to vote) while reducing whale dominance. Three main approaches: quadratic voting (votes = square root of tokens), conviction voting (voting power grows over time), and reputation systems (earn voting power through participation). Each has trade-offs between fairness, complexity, and attack resistance.

๐ŸŽฎ Interactive: Voting System Comparison

Compare three voting systems with the same 5 voters. See how power distribution changes dramatically based on the weighting formula.

Linear (Standard)

votes = tokens

One token = one vote. Simple, but concentrates power.

Voter 1 (100 tokens)0.6%
100 votes (1:1)
Voter 2 (500 tokens)3.0%
500 votes (1:1)
Voter 3 (1,000 tokens)6.0%
1000 votes (1:1)
Voter 4 (5,000 tokens)30.1%
5000 votes (1:1)
Voter 5 (10,000 tokens)60.2%
10000 votes (1:1)
Largest Holder Power
60.2%
Power Concentration
High

Standard system: Voter 5 has 100x power of Voter 1 because they have 100x more tokens.

๐Ÿ“ Quadratic Voting: Mathematical Fairness

Votes = โˆš(tokens). If you have 100 tokens, you get 10 votes. Someone with 10,000 tokens gets 100 votes (not 10,000). The whale has only 10x power despite 100x tokens. This dramatically reduces concentration while maintaining Sybil resistance (still need tokens to vote).

โœ… Advantages
  • โ€ข Reduces whale dominance significantly
  • โ€ข Encourages broader participation
  • โ€ข Still Sybil-resistant (need tokens)
  • โ€ข Used in Gitcoin Grants (funded $50M+)
โŒ Disadvantages
  • โ€ข Complex to explain to users
  • โ€ข Whales can split tokens across wallets
  • โ€ข Reduces economic alignment incentive
  • โ€ข Rare in major DAOs (implementation complexity)

โณ Conviction Voting: Time-Weighted Power

Used by 1Hive and Commons Stack. Your voting power grows the longer you commit to a proposal. Support a proposal for 30 days? Your votes count more than someone who voted last minute. Aligns governance with long-term thinking and prevents mercenary voting (buy tokens, vote, dump).

How It Works
  1. 1. Stake tokens on a proposal (continuous, no deadline)
  2. 2. Voting power = tokens ร— time decay function (exponential growth)
  3. 3. Can change vote anytime, but conviction resets to zero
  4. 4. Proposal passes when conviction exceeds threshold (dynamic based on funding request size)
  5. 5. No single "vote close" timeโ€”decisions emerge organically
Trade-off: Slower decision-making (takes weeks for conviction to build) but prevents rushed/manipulated votes.

๐Ÿ† Reputation Systems: Earn Your Voice

Some DAOs experiment with non-transferable voting power earned through contributions. Complete a task? Earn reputation points. Reputation = votes. Can't be bought, only earned. Meritocracy instead of plutocracy.

DXdao (Reputation-based)

Earn REP tokens through work. REP = voting power. Can't buy REP, only earn it. Result: contributors control governance, not investors.

Issues with Reputation

Who decides what earns reputation? How to prevent gaming? Hard to bootstrap (no reputation = no participation initially). Most DAOs stick to tokens.

๐Ÿ’ก Key Insight

Alternative voting systems attempt to solve the plutocracy problem but face a trilemma: you can have two of (1) Sybil resistance, (2) equal voting power, (3) economic alignmentโ€”but not all three. Token weighting = strong Sybil resistance + economic alignment, but unequal power. Quadratic voting = Sybil resistance + more equal power, but weaker economic alignment. Reputation = equal power + economic alignment (contributors decide), but weak Sybil resistance (reputation can be gamed). Most DAOs choose simple token weighting because it's the easiest to implement and hardest to game, accepting plutocracy as a tolerable cost. Alternatives exist but remain experimental and complex. Next: real-world case studies of how weighting systems shape DAO outcomes.

โ† Power Dynamics