Fiscal Geometry Lab
Routing Legal, Fiscal, and Institutional Systems Before Judgment
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Fiscal Geometry is an original routing framework for rule-dense institutional environments.
It began with tax law as the first experimental field and is now being prepared for workflow deployment in document-heavy, high-risk environments where intake, routing, escalation, and audit visibility matter.
Fiscal Geometry Research Program
Fiscal Geometry Research Program
Institutional Routing, AI-Age Governance, and Index Development
Institutional Routing, AI-Age Governance, and Index Development
Fiscal Geometry is an original research framework for reading how institutions route persons, evidence, resources, classifications, and consequences before judgment.
It began with tax law and fiscal systems as its first experimental field and is now being developed across education governance, legal AI, compliance routing, public-sector workflow design, and institutional stress measurement.
The central question is simple:
Before judgment is made, how does the institution route the case?
Fiscal Geometry does not replace legal, professional, or institutional judgment. It provides a structured layer before judgment by making intake conditions, classification points, route shifts, exception points, and audit visibility legible.
2026 Academic Milestone
2026 Academic Milestone
In 2026, Fiscal Geometry entered formal international conference circulation as the lead concept in:
Fiscal Geometry and Democratic Education in the Age of AI: Reading Educational Access as Institutional Routing
This paper, listed for the 34th International Conference on Learning, marks an important public milestone: Fiscal Geometry appears first in the title as the organizing framework, not merely as a background method.
The significance is broader than education. Education is the first international conference application field through which Fiscal Geometry is being tested as a framework for institutional routing, AI-mediated classification, access governance, and democratic accountability.
In this view, AI literacy is also institutional literacy: the ability to understand who is seen, what evidence counts, how classifications are made, how recognition is granted, and how opportunity is distributed.
Framework Family and IP Status
Framework Family and IP Status
PJLS — Pre-Judgment Legal Shell
PJLS is the entry layer. It asks what information is allowed to enter the institutional route before judgment begins. It separates official records, verified data, legally relevant inputs, and admissible evidence from unsupported claims, noise, or unreliable signals.
IP status: internal framework component; related protection strategy under development.
Cabinet-Drawer Model / CDM
CDM identifies the classification architecture of institutional systems. The cabinet is the legal, fiscal, educational, or administrative container. The drawers are the categories into which persons, files, records, transactions, or events are placed. The drawer divider is the rule, threshold, model, proxy, or classification logic that determines which drawer opens.
IP status: Canadian trademark application filed and formalized; amended services statement submitted for Class 42 SaaS / workflow mapping / data classification / compliance documentation / AI governance use.
4-3-3-2 Grammar
4-3-3-2 Grammar is a routing grammar for translating rule-dense legal, fiscal, and administrative systems into structured pathways.
IP status: Canadian trademark application filed and formalized; awaiting examination.
ASLTP — Affect, Surface, Label, Transform, Present
ASLTP explains how human response, institutional signals, or high-tension inputs may be surfaced, labelled, transformed, and presented inside a routing system. It functions as a response-conversion layer within Fiscal Geometry.
IP status: trademark and operational protection strategy under consideration.
ZITI Index and ITI
ZITI and the Institutional Tension Index support the index-development layer of Fiscal Geometry. They are designed to identify structural pressure, routing distortion, institutional tension, and governance visibility inside complex systems.
IP status: ZITI Index has received a CIPO Approval Notice approving the trademark application for advertisement; ITI remains under trademark examination / response process.
Intellectual Property Notice
Intellectual Property Notice
Fiscal Geometry and its related framework components are being developed by Jim Y. Huang as original analytical, routing, diagnostic, and operational tools.
Trademark applications and related intellectual-property protection steps are in process for selected framework components. Academic discussion, citation, teaching reference, and non-operational discussion remain unrestricted.
Operational deployment, including workflow routing, compliance design, AI system structuring, institutional diagnostic tools, SaaS implementation, enterprise decision pathways, and commercial use of named framework components, may require permission or licensing depending on the specific use and applicable legal status.
Public Demonstration Repositories
Fiscal Geometry is currently demonstrated through five public GitHub repositories.
The first repository, 4-3-3-2 Fiscal Routing Grammar, provides the technical specification and minimal implementation environment for closure-gated legal-tax AI workflows. It includes a SQL control schema, JSON routing examples, and a Python validator showing how AI output can be blocked unless evidence, classification, routing, and closure conditions are satisfied.
The demo, Legal-Tax Routing SQL MVP, shows how legal and tax materials can be routed before answer generation through PJLS, CDM, and the 4-3-3-2 Grammar.
The demo, FG RiskMap, extends Fiscal Geometry into pre-answer risk routing and financial distortion monitoring for legal, tax, banking, audit, and financial workflows.
The demo, ASLTP Enforcement Review Interface, shows how human responses can be visually compared against AI-generated enforcement labels before public-law closure. It demonstrates the ASLTP Antidote Log, review-ready enforcement records, and human closure before consequence.
The demo, CDM Classification Routing Demo, demonstrates how the Cabinet-Drawer Model (CDM) can be used for institutional classification, rule routing, and downstream consequence mapping.
The demo, ITI-GITI-IDI Framework, demonstrates a computational public-administration and institutional distortion model using ITI, GITI, and IDI to compare expected institutional strain with realized outcome patterns.
Repository Notice
Repository Notice
All repositories are public demonstration projects for academic, technical, and non-operational review. They do not provide legal, tax, audit, lending, compliance, regulatory, or professional advice.
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