Plurality

The simplest form of plurality voting, where the candidate or proposal with the highest number of votes is selected. This is common in on-chain governance for binary or multi-choice proposals.

• Mechanism: Each voter selects one option; the top vote-getter wins.
• Example: A DAO uses FPTP to choose between three grant recipients. The proposal with 40% support wins, even though 60% voted for other options.
• Trade-off: Can lead to a 'winner-takes-all' outcome that doesn't reflect broader consensus.

Plurality is often confused with majority rule. It's critical to distinguish between them in governance design.

• Plurality (Relative Majority): The option with the most votes, even if less than 50%.
• Majority (Absolute Majority): Requires more than 50% of the total votes.
• Application: Many blockchain upgrades use a supermajority (e.g., 66% or 75%) threshold to ensure stronger consensus, which is stricter than a simple plurality.

A major weakness of plurality systems where similar options split the vote, allowing a less popular option to win.

• Mechanism: If two proposals A and B appeal to a similar bloc of voters, they divide that bloc's votes. A dissimilar proposal C can then win with a small plurality.
• Blockchain Impact: In protocol parameter votes, multiple similar fee adjustment proposals could split the vote, allowing a status quo or extreme option to pass unexpectedly.
• Mitigation: Some systems use vote aggregation or runoff rounds to consolidate preferences.

Quadratic Voting is a more sophisticated mechanism that can mitigate some drawbacks of simple plurality by accounting for vote intensity.

• Mechanism: Voters allocate a budget of voice credits. The cost to cast n votes for a single option is n² credits, making strong preferences expensive.
• Contrast to Plurality: Unlike one-person-one-vote plurality, QV allows expression of preference strength, which can surface consensus on highly valued options rather than just the most numerous.
• Use Case: Used in some DAOs for funding public goods or prioritizing features, as it reduces the power of simple majority/plurality blocs.

On-chain plurality voting is typically implemented via a smart contract that tallies votes and declares a winner.

• Core Functions: vote(uint proposalId), tallyVotes(), getWinner().
• State Variables: A mapping from proposalId to its vote count.
• Key Consideration: The contract must handle vote delegation and vote weighting (e.g., by token stake) if applicable. A simple implementation might only record the last vote from an address, while more advanced ones use checkpointed balances.

Plurality for governance is distinct from blockchain consensus mechanisms like Proof of Work or Proof of Stake, though both involve collective choice.

• Governance Plurality: Decides on protocol upgrades, treasury spends, or parameter changes. It's a social/political layer.
• Network Consensus: Validators use cryptographic protocols (e.g., Nakamoto Consensus, BFT) to agree on the state of the ledger. It's a technical layer for security and liveness.
• Interplay: A governance vote using plurality might initiate a change that validators then implement via the network's consensus rules.

Plurality voting is the standard for many on-chain governance systems, such as Compound's Governor Bravo. A proposal passes if it receives more 'For' votes than 'Against' votes by the end of the voting period, even if voter turnout is low. This simplicity makes it easy to implement and audit on-chain, though it can lead to outcomes not supported by a majority of the total token supply.

Decentralized Autonomous Organizations (DAOs) often use plurality voting to allocate funds from their treasury. For example, a grant program might present several candidate projects, and the one with the most votes receives funding. This is effective for prioritizing a single option from a list but can suffer from the 'vote splitting' problem where similar proposals split the vote, allowing a less popular option to win.

Protocols use plurality votes to adjust key economic parameters. In a lending protocol, a vote might propose several different values for a loan-to-value (LTV) ratio or a liquidation penalty. The specific numerical value with the most votes is implemented. This allows for precise, incremental changes to system risk and incentives based on tokenholder sentiment.

In representative DAO models like those used by MakerDAO, tokenholders use plurality voting to elect delegates or core unit facilitators. Each voter selects one candidate from a list, and the top N candidates with the most votes are elected to their roles. This creates a smaller, accountable group responsible for day-to-day operations and complex decision-making.

A critical weakness of plurality is the spoiler effect, where two similar options split the vote, allowing a dissimilar, less broadly supported option to win. For example, if a DAO votes on a treasury allocation and two similar DeFi projects receive 30% and 25% support respectively, a third unrelated project with 35% support wins, despite 55% of voters preferring a DeFi project. This often necessitates pre-vote coordination or alternative systems like ranked-choice voting.

Plurality is distinct from majority voting (which requires >50% of votes cast) and systems with quorum requirements (which require a minimum turnout). In plurality, a proposal with 40% support can beat one with 35% and 25%, even with a 60% quorum unmet. Understanding this distinction is crucial for analyzing governance attack vectors and the legitimacy of outcomes.

Plurality enables a permissionless, on-chain governance model where voting power is derived from staked assets. This ensures that protocol upgrades, parameter changes, and treasury allocations are decided by a broad, decentralized set of stakeholders, not a centralized team. Key features include:

• Proposal submission by any qualifying stakeholder.
• Transparent voting with on-chain execution of approved measures.
• Sybil-resistance through economic stake weighting.

By requiring validators and participants to stake native tokens, Plurality creates a cryptoeconomic security model. Malicious actors risk having their staked assets slashed (forfeited) for actions that harm the network, such as double-signing or prolonged downtime. This aligns the cost of attack with the value secured, making attacks economically irrational. The system's security scales with the total value staked (TVS).

Rewards (e.g., block rewards, transaction fees, MEV) are distributed proportionally to stakers based on their contribution and the duration of their stake. This creates a positive feedback loop:

• Stakers earn yield for securing the network.
• Protocol benefits from increased stake, which boosts security and stability.
• Long-term alignment is encouraged through mechanisms like vesting schedules or lock-up bonuses.

A significant portion of the circulating supply is locked in staking contracts, reducing sell-side pressure on the open market. This staking ratio acts as a natural stabilizer for the token's price. Furthermore, the opportunity cost of selling (forfeiting staking rewards) encourages holders to participate in the network's security rather than engage in short-term speculation.

Plurality systems often support delegation, allowing token holders who cannot run infrastructure to delegate their voting power and staking rewards to professional validators. This lowers the barrier to participation and ensures network security is not limited to large, technical entities. Delegators maintain custody of their assets while contributing to decentralization.

Fees and rewards generated by the protocol can be directed to a community treasury governed by Plurality. This treasury can fund public goods, provide protocol-owned liquidity (POL) in decentralized exchanges, or be used for strategic ecosystem grants. This creates a self-sustaining economic flywheel independent of continuous token issuance or venture funding.

In a pluralistic network with multiple block producers (e.g., Proof-of-Stake validators, Proof-of-Work miners), a fundamental challenge is determining which competing block becomes canonical. This creates a forking risk, where the network can temporarily split. Mechanisms like longest-chain rule or GHOST are required to achieve eventual consensus, but they introduce latency and potential for reorgs (block reorganizations).

Plurality in block creation directly enables Maximal Extractable Value (MEV). The competition to propose the next block incentivizes sophisticated actors (searchers, block builders) to optimize transaction ordering for profit. This can lead to:

• Centralization pressure on validators/miners.
• Network congestion and increased fees for users.
• Potential for censorship of specific transactions.

A network with many independent clients (a form of implementation plurality) must maintain a consistent global state. This leads to the state bloat problem, where the size of the blockchain history grows indefinitely, increasing hardware requirements for node operators. A lack of client diversity (e.g., one client dominating) creates systemic risk, as a bug in that client could halt the network.

Distributed decision-making across a plural set of stakeholders (token holders, developers, core teams) can lead to governance paralysis. Achieving consensus on protocol upgrades becomes slow and contentious, as seen in debates over EIP-1559 or The DAO fork. This can stall innovation and create factions, potentially leading to chain splits (e.g., Ethereum/Ethereum Classic).

Increasing the number of participants (node plurality) enhances censorship resistance but often reduces performance. Byzantine Fault Tolerance (BFT) consensus protocols require extensive communication (O(n²) messages) between validators, creating a scalability bottleneck. This forces a trade-off: high plurality for security or higher throughput via more centralized, committee-based designs (e.g., DPoS, BFT with small validator sets).

Designing cryptoeconomic incentives that sustain a healthy, pluralistic network is complex. Without careful calibration, systems tend toward re-centralization. Examples include:

• Pool dominance in Proof-of-Work (e.g., Bitcoin mining pools).
• Staking concentration in Proof-of-Stake due to capital requirements.
• Free-rider problems where users benefit from the network without contributing resources, undermining the pluralistic base.

A governance model proposed by Robin Hanson where voters bet on outcomes to determine policy. Markets are used to discover and execute the most valuable proposals.

• Process: 1) Vote on a measurable goal (e.g., "increase protocol revenue"). 2) Create prediction markets for different policy proposals. 3) The policy predicted to best achieve the goal is implemented.
• Rationale: Harnesses the wisdom of crowds and financial incentives for better decision-making.
• Exploration: Early experiments have been conducted by Gnosis and Augur.

A scalable governance framework that uses futarchy and prediction markets to pre-filter proposals. It enables large communities to govern without requiring everyone to vote on every issue.

• Core Idea: A subset of voters ("boosters") can signal strong belief in a proposal by staking on its passage. If their prediction market indicates high success, the proposal moves to a full vote.
• Benefit: Dramatically increases throughput and focuses attention on high-potential ideas.
• Implementation: A key innovation behind the DAOstack ecosystem and its GEN token.

A system of governance where power is directly proportional to wealth or capital stake. This is the default state of most token-based voting (one-token-one-vote).

• Characteristic: The largest token holders have de facto control over decision-making.
• Critique: Can lead to misaligned incentives, voter apathy, and centralization of power.
• Contrast: Plurality mechanisms like quadratic and conviction voting are explicitly designed to mitigate pure plutocracy.

Systems that attempt to bind governance rights to unique human individuals rather than fungible capital. This is a foundational concept for achieving one-person-one-vote models in decentralized settings.

• Methods: Include biometric verification, social graph analysis, and trusted attestations.
• Purpose: To prevent Sybil attacks (one entity creating many identities) and ensure democratic equality.
• Projects: BrightID, Proof of Humanity, and Worldcoin are exploring different technical approaches to this challenge.

A consensus mechanism where validators are chosen to create new blocks and validate transactions based on the amount of cryptocurrency they stake as collateral. This is a fundamental alternative to Proof of Work (PoW) and is the basis for many modern blockchains like Ethereum 2.0, Cardano, and Solana.

• Key Principle: Security through economic stake, not computational work.
• Advantages: Significantly lower energy consumption and faster transaction finality.
• Related to: Slashing, Delegation, Validator.

An organization represented by rules encoded as a computer program that is transparent, controlled by the organization's members, and not influenced by a central government. DAOs are the primary vehicle for implementing on-chain governance and collective decision-making.

• Governance Tokens: Members use these to vote on proposals.
• Treasury Management: Funds are often held in a multi-signature wallet controlled by the DAO.
• Examples: MakerDAO, Uniswap, Aragon.

A proposed governance model where decisions are made based on prediction markets. Voters don't vote on policies directly; instead, they bet on which policy will achieve a predefined metric (e.g., higher token price). The policy with the most favorable market prediction is implemented.

• Mechanism: Uses market signals to aggregate information and beliefs.
• Proposed by: Economist Robin Hanson.
• Explored in: Blockchain projects like Augur and DXdao.

A voting system designed to capture the intensity of voter preference. The cost of a vote increases quadratically with the number of votes cast on a single option. This helps prevent whale dominance by making it expensive to concentrate many votes.

• Formula: Cost = (Number of Votes)².
• Goal: Better reflects the strength of collective belief.
• Implementation: Used in Gitcoin Grants and proposed for various DAO governance structures.

The protocols that enable distributed computer networks (blockchains) to agree on a single data state. They are the foundation of security and trust in decentralized systems.

• Proof of Work (PoW): Uses computational puzzles (Bitcoin).
• Proof of Stake (PoS): Uses staked capital (Ethereum).
• Delegated Proof of Stake (DPoS): Stake-weighted representative voting (EOS).
• Practical Byzantine Fault Tolerance (PBFT): Used in permissioned networks.

The study of the economic systems and incentive structures designed into a cryptocurrency or blockchain project. Governance tokens are a key component, granting holders the right to participate in protocol decisions.

• Utility: Voting rights, fee sharing, staking rewards.
• Distribution: Often via liquidity mining, airdrops, or public sales.
• Vesting: Schedules to align long-term incentives of team and investors.