Flow Shaping Principle — Correspondence-Calibrated Pathway-Specific Updating

Abstract

Adaptive systems can assign persistent change to configurations through which consequential episodes pass. This paper formulates the Flow Shaping Principle (FSP) as a falsifiable claim about veridical consequence-configuration correspondence. FSP concerns active updating only. Foundational meanings are imported from Connection Theory and exhaustively registered in a version-bound appendix. For a pre-specified boundary, resolution, property set, and primary partition Π, the system must first demonstrate Π-specific updating. A_corr(Π) is measured from update-available substrate through a pre-registered readout capacity-matched to, but distinct from, the system's attribution computation. A separate diagnostic reads the system-generated attribution signal. S_corr(Π) measures persistent change in the correct configuration aligned with consequence-warranted direction or content; localization alone is insufficient. FSP predicts that A_corr prospectively predicts held-out S_corr and that calibration transfers across two pre-specified correspondence-degradation classes. The zero-information boundary and information upper bound follow from data processing; they are analytic constraints, not claimed discoveries or empirical wagers. The primary canonical target is an instrumentable artificial adaptive system; neural and human organizations remain candidate extensions. Entry conditions, independent measurements, controls, and failure criteria are specified, but no complete canonical test has been reported. This manuscript is a preprint and has not undergone peer review. Correction notice: The PDF was corrected on 1 August 2026 to replace an incorrect DOI cited for Connection Theory v4.6. The correct version DOI is 10.5281/zenodo.21714702. No definition, prediction, failure criterion, figure, or other substantive content was changed.