1 · Boundary & Identity

🚧 Draft (core-idea sketch). Part A · Core Ideas. The problem under all the others.

The problem. Almost everything below — voting, consensus, fair pricing, basic income — silently assumes you can tell distinct participants apart. A central identity registry is out (centralization, privacy); a cheap "proof of personhood" is forgeable; a strong one is privacy-destroying. This is the Sybil problem, and it's the precondition for the system to have a well-defined boundary at all.

The core idea. Stop asking "is this a distinct person?" and ask "how much independent information does this participant contribute?" Look at each account's behavioral residuals — forecast errors, transaction timing, verdicts — after conditioning on public information. Honest distinct agents are roughly independent; one controller's puppets stay correlated because they share private state. An effective population n_eff collapses a tightly-correlated cluster of k sock-puppets toward 1, while genuine independents each count fully. Issue all weight (votes, income, influence) per unit n_eff, and the Sybil attack yields nothing. Identity becomes an accumulated signature of real work — faking k identities costs about as much as being k real contributors.

Leans on: nothing — it's the root. Enables: money (6), the resource market (5), the truth machine (7), governance (8) — everything counted or weighted.

⚠️ Where it's thin. It's an arms race: how much behavioral monitoring is "enough" is empirical, estimating the correlation structure at scale is unsolved, and a fresh account is weakest exactly at birth (handled later via local vouching). Spec depth + failure modes: Part B.