A Fractal Funding Model for Small Communities and DAO's

Imagine a village with a single Community Chest - a shared fund where everyone’s contributions go (work credits, taxes, donations). From this Chest, the community decides to support broad areas of village life:

  1. Dedicated Domain Allocation (DDA)

    • The Council meets and agrees how to split the Chest among “domains” such as Infrastructure, Food & Supplies, Health & Safety, Education & Culture, and Transportation.
    • Each domain gets a fixed percentage (e.g., 30% for Infrastructure, 20% for Food & Supplies, etc.), always totaling 100%.
    • If villagers feel a domain needs more or less, they propose adjustments (possibly via conviction voting where the longer and stronger the support, the more sway it carries).
  2. Dependency Graphs & Weights

    • Within each domain, committees further divide their slice among sub-domains or projects - again by simple percentage weights.
    • For example, the Infrastructure allocation might be split 60/40 between “Buildings & Roads” and “Water & Power.”
    • Those sub-slices can then be split further (e.g., “Building Repairs” vs. “New Construction”), using exactly the same weight-based rules.
    • This “fractal” process works identically at every level: percentages always flow down the tree, ensuring clarity and consistency whether you’re at the village level or the smallest working group.
  3. Self-Curated Registries

    • At the leaves of this funding tree sit registries - on-chain rosters of people doing the work.
    • Each registry (say, the Repair Crew) votes internally on who belongs and how to reward them: full-time villagers might get 1× credit, half-timers 0.5×, with multiplier for months of service.
    • This keeps each group accountable to its own standards, while the Chest only needs to know the overall percentage flowing to that registry.

How It All Fits Together

  • Community Chest (DAO Treasury): The single source of truth, holding all funds.
  • DDAs (Domains): Top-level “budget accounts” like in town-ledger accounting - allocate the Chest by domain.
  • Dependency Graphs & Weights: A recursive budgeting rule: every node (domain, sub-domain, project) splits its share by percentage.
  • Self-Curated Registries: Department-level “expense accounts” where members and payments are governed by those doing the work.

By modeling our village’s funding as a nested dependency graph, we achieve:

  • Transparency: Every villager can trace coins from the Chest down to each carpenter or gardener.
  • Flexibility: New committees or projects slot in naturally - just assign weights under the relevant domain.
  • Democracy + Meritocracy: The whole village adjusts domain budgets, and each working group fine-tunes its own rewards.

In short, this fractal funding model turns a simple Community Chest into a scalable, transparent, and self-governed system - perfect for a small village or a global DAO alike.

Potential Weaknesses & Unanswered Questions

As with any governance design, there are areas to watch closely and questions to explore:

  • Cognitive & Administrative Overhead: Tracking and voting on multiple percentage rebalances could overwhelm contributors.
  • Budget Drift & Inertia: Established splits may become entrenched, and conviction voting might reinforce outdated priorities.
  • Registry Fragmentation & Gatekeeping: Self‑curated groups risk becoming closed circles, making it hard for newcomers to join.
  • Adjustment Frequency & Process: How often should domain budgets be rebalanced? What parameters (decay rate, thresholds) govern conviction voting?
  • Registry Onboarding & Exit: What’s the exact on‑chain mechanism for joining, leaving, or dispute resolution within registries?
  • Emergency Fund: Is there a rapid‑response allocation for crises, and how do we prevent its abuse?
  • Tooling & UX: What dashboards or interfaces will make this system accessible to all participants?

We’d love to hear your thoughts:

  • What do you see as the biggest risks or gaps?
  • Which questions matter most to you?
  • How would you tweak the model to address these challenges?
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