Flow Fusion: Toward a Science of Algorithmic Governability — A Structural Model for the Stability of Distributed Decision Systems (Version 2.2)

This preprint introduces Flow Fusion, a structural and control-oriented analytical model for assessing the governability of distributed decision systems. The model formalizes the relationship between decision pressure (DP) and effective governance capacity (GCeff), and proposes first-order analytical constructs including the Governability Index (GI) and Governance Buffer (GB). Flow Fusion is not presented as a predictive or certified framework, but as a bounded, falsifiable, and context-relative analytical foundation for studying system stability under conditions of scale, automation, and propagation. Version 2.2 strengthens:- the normalization requirement for variable commensurability,- the first-order interpretation of structural conditions,- the distinction between analytical indices and empirical measurements,- the separation between structural model and descriptive classification,- the articulation of limitations and empirical research pathways. This work aims to contribute to the emerging field of algorithmic governability and distributed decision-system analysis. ⚠️ This document is a conceptual preprint and does not constitute a validated empirical model or regulatory standard.