Structural Fiscalistics : An Executable Epistemology for Reading Institutional Systems
Abstract
This paper develops Structural Fiscalistics as an executable epistemology for reading rule-dense institutional systems. Across tax, legal compliance, disclosure–audit interfaces, and AI-mediated decision workflows, “understanding” is often expressed as narrative explanation or interpretive commentary. The paper argues that narrative commonly substitutes for structure: it cannot be reliably replayed, audited, or transferred, and it enables conclusions to appear without a verifiable chain of institutional operations. Against this tendency, the paper reframes institutional understanding as a pre-analytical constraint problem: before judgment or prediction, an admissibility regime must determine what counts as decision-grade knowledge. Structural Fiscalistics An Exe… The framework integrates three components: Fiscal Epistemology (FE) as a constraint protocol for admissible signals; Fiscal Geometry (FG) as a rendering mechanism that converts institutional operations into auditable objects; and a 4-3-3-2 executable grammar that enforces structure-first routing. These components are implemented through a one-way pipeline—Evidence → Structure → Readout—designed to block “narrative replacing structure” and to produce replayable, inspectable outputs (evidence chains, node tables, routing maps, and typed failure logs). Under this protocol, institutional tension is re-specified as a structural readout—diagnosable as evidence non-closure, routing error, threshold mismatch, or sequencing violation. The paper clarifies boundary conditions (no moral theory, no causal claims, no policy prescriptions) and provides a minimal demonstration of what executable institutional reading looks like in practice.
Fields of Study & Subjects
Legal and Constitutional Studies
Economic Theory and Institutions
Taxation and Compliance Studies
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 28 January 2026