knowledge-equilibria-are-correction-convergent-and-topology-accurate

OUT derived (depth 13)

Knowledge growth converges to negation-transparent equilibria with complete propagation fidelity, where every correction that shapes that convergence operates on accurate topology — dependency completeness ensures corrections propagate through the true graph structure, not an approximation.

Summary

When the system settles into a stable state after processing changes, that stability is genuine — it reflects the true dependency structure rather than an incomplete picture of how ideas connect. This matters because corrections only work reliably if they propagate through the actual relationships between claims, not a simplified or partial version of them.

Justifications

SL — Knowledge equilibria transparency combined with topological accuracy of the corrections driving convergence

Antecedents (all must be IN):

  • knowledge-growth-reaches-transparent-equilibria — The system's knowledge growth converges to equilibria that are simultaneously negation-transparent (the final stable state is uniquely determined by evaluation order-invariant rules over negative semantics) and propagation-complete (every truth change cascades to every transitively dependent node), with indefinite self-correction ensuring these equilibrium properties are maintained across unbounded operational time
  • all-corrections-converge-on-accurate-topology — Both intentional corrections (dialectical dispute resolution with complete and reliable challenge/defend) and automated corrections (exhaustive self-correction spanning the full lifecycle) propagate through topology that is simultaneously accurate (complete dependency tracking) and convergent (deterministic stable states), meaning all correction paths — human-initiated and system-driven — reach the same equilibrium through faithful graph traversal.

Dependents

These beliefs depend on this one:

Details