A Fiscal Epistemology of Information

1. What this paper establishes

This paper defines the epistemic foundation of the Fiscal Geometry framework.

It explains how information becomes valid evidence in the analysis of fiscal systems, institutional design, and educational access. Rather than relying on narrative accounts or demographic proxies, it treats knowledge as grounded in observable, rule-governed fiscal events produced by legally accountable institutions.

In this approach, inequality and access are not stories—they are structural outcomes of constrained events.

2. The core epistemic claim

Not all information has equal evidentiary status.

Public administrative data—such as budgets, statutory rules, eligibility criteria, and audited fiscal records—carry higher epistemic weight than media narratives or anecdotal accounts because they are embedded in formal accountability chains.

Fiscal Geometry operationalizes this distinction by mapping institutional actions as events within an X–Y analytical space, where patterns such as bottlenecks, clusters, and discontinuities become structurally visible.

3. Why this matters now

This event-based epistemology is particularly compatible with AI-assisted verification.

AI systems can reliably check logical consistency, definitions, citations, boundary conditions, and computational reproducibility. As a result, framework-based theories—those articulated through axioms, rules, and generative structures—become AI-verifiable without replacing human interpretation or ethical judgment.

This paper explains why Fiscal Geometry can be validated structurally before explaining how its indices are computed.

Working Paper

A Fiscal Epistemology of Information
SSRN Working Paper No. 5817962👉

4. How this framework structures subsequent work

This paper functions as a foundational epistemic layer rather than a complete analytical system.

It establishes the conditions under which information becomes structurally valid—prior to measurement, modeling, or index construction. Subsequent Fiscal Geometry papers, including axis-based diagnostics, institutional tension indices, and computational implementations, operate downstream from this epistemic specification.

In this sense, A Fiscal Epistemology of Information defines what counts as admissible structure, while later work addresses how those structures are rendered, measured, or simulated.

This separation ensures that methodological debates about indicators, models, or applications do not collapse into disputes over interpretation, narrative framing, or ethical positioning. Structural validity is resolved first; operational design follows.

ASLTP serves as a real-world anchor: it demonstrates how public rule texts and administrative records can be treated as admissible structural evidence and translated into observable institutional patterns.

Applied illustration: Emotion as Field: The Axiomatic and Structural Basis of the Emotional Tension Index (ETI) (Zenodo):

https://zenodo.org/records/17968282

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