Citizens' House History and Evolution

Experimentation with Citizenship

The Citizens' House has undergone significant evolution since its inception, reflecting Optimism's commitment to iterative improvement and experimental governance. This section traces that journey and provides context for the Season 8 changes.

Origins and Early Vision

When the Citizens' House was first conceived, three core goals guided its development:

1. Reduce concentration of power
2. Counteract potential capture of the Token House
3. Allocate resources effectively (particularly Retro Funding)

Initially, Citizens were selected because they were most likely to meet these goals—rather than because they held an intrinsic right to representation. This pragmatic approach allowed for experimentation with different selection methods and governance structures.

Web of Trust Model

The early Citizens' House used a Web of Trust model for selecting participants:

• Round 1 began with 24 participants selected by the Optimism Foundation
• Round 2 expanded to 71 participants, with existing Citizens inviting new members
• Round 3 grew to 146 participants through continued invitation

This approach allowed for controlled growth while maintaining alignment with the Collective's values. However, it also raised questions about representation and inclusivity.

Key Phases & Lessons

The evolution of the Citizens' House has been marked by several key phases, each yielding important insights that have shaped the Season 8 model.

Round 4: Growing On-Chain Data

During this phase, the focus shifted to building better data infrastructure for governance:

• OP Atlas and the project registry was established to track the projects building value on the Superchain
• By tying registry enrolment to Retro Funding sign-up, the registry grew organically
• This provided signals for identifying potential Citizens and improving the efficiency of Retro Funding

Round 5: Expertise vs. Broader Perspective

This phase tested whether OP Stack experts would better allocate Retro Funding than non-experts:

• Experts made more 'opinionated' (less flat) distributions, which stakeholders saw as more accurate
• A key insight emerged: expertise helps answer "Which projects are most useful?", but value-based questions (e.g., "What types of impact should we prioritize?") require broader stakeholder input
• This highlighted the distinction between technical assessment and expression of preferences

Round 6: Badgeholder vs. Community Analysis

This phase compared the existing badgeholder group with a broader community sample:

• No significant differences were found between badgeholders (selected via the web-of-trust model) and a random community sample
• Both groups tended to represent an "enthusiast" persona—those with time and interest in governance who weren't necessarily Superchain stakeholders
• This revealed an opt-in bias toward "enthusiast" behavior in governance, potentially overshadowing other key stakeholder voices

Season 7: Testing Personas & Organizational Votes

This crucial phase brought in diverse Guest Voters—community members, chains, and past Retro Funding recipients—yielding several important findings:

• Individuals working at chains/protocols appeared to represent personal, rather than organizational preferences
• There was a cluster of voters that consistently favored higher budgets for work less tied to direct Superchain growth. This cluster correlated with lower OP Stack expertise, high funding received in Round 6, and a preference for public goods over Superchain growth
• Most participants, even non-experts, tended to align with budgets proposed by an "expert group".
• Engagement was highest among enthusiasts and community contributors, lower among chains/application developers

Personas Research

Research into governance participants revealed several distinct personas that have informed the Season 8 model:

Enthusiast Persona

• Overrepresented in governance due to opt-in bias—these individuals participate heavily because they find governance intrinsically rewarding
• Tend to be very engaged in forums, Discord, and other governance channels
• Often willing to invest significant time

Bootstrapper Persona

• Builders of tooling and infrastructure who stay close to governance to understand funding opportunities and the Collective's needs
• Motivated by securing sustainable funding for their projects

Superchain Builder Persona

• Typically the core developers of protocols/chains who have a great interest in the Superchain's overall growth
• Underrepresented in current governance structures because they are very busy
• Often lack time for extensive governance engagement

This research highlighted the need to design governance processes that capture input from all these personas, not just those with the most time and intrinsic motivation for governance participation.

Evolving Governance Understanding

Through these experiments, a more nuanced understanding of governance has emerged:

Different Decision Types

• Preferences: No absolute "right" answer (e.g., setting priorities)
• Prediction: There is a correct answer, but only revealed in the future
• Measurement: Best done objectively, ideally by a computer or hired experts

Select for Expertise; Govern for Preferences

• Prediction or measurement are tasks that can be delegated to experts who are held accountable by governance
• Preference-based choices require broad stakeholder input
• This distinction helps clarify that stakeholders must be able to express their preferences while delegating the execution of those preferences

From "One House" to "Decision Modules"

A key insight from these experiments is that not all decisions should be made by the same group. Instead, "Who gets to vote on X?" is the crux of effective governance design.

Different decisions (resource allocation, upgrades, economic parameter setting) need to be owned by the right stakeholder mix. Additionally, proposal and approval rights may go to different entities, with proposals often made by smaller expert groups and ratified, approved, or vetoed by the wider stakeholders.

Future Directions

The inclusion of chains, apps and users in the Citizens' House as of Season 8 represents an important step forward, but not the end of the journey. Future developments may include:

Refined Eligibility Criteria

As we gather more data on participation and outcomes, eligibility criteria may be further refined to achieve optimal representation.

Stratified Random Sampling

For Citizens that are end-users, future seasons may implement stratified random sampling to prevent overrepresentation of specific types of users and prevent capture.

Enhanced Sybil Resistance

Improvements to proof of personhood mechanisms will continue to evolve to support the integrity of the Citizens' House.

Additional Governance Powers

As the Citizens' House matures, it may take on additional governance responsibilities.

Changes to Joint House Voting Thresholds

The precise dynamics around quorum and approval / veto thresholds in Joint House votes are complex and will require further tuning in future Seasons to ensure a balanced representation of stakeholder interests.

The Citizens' House will continue to evolve based on what we learn together, always guided by the core principle of reducing platform risk for those that depend on the Superchain and preventing capture by any one interest group.