Rights get averaged away
Aggregate benefit can conceal protected losses to specific people, groups, species, or future stakeholders.
MathGov Core v11.4 + SGP v6.4
Govern decisions by grounding reality, protecting rights, bounding ruin, preserving structure, and only then scoring ripples.
RippleLogic is the decision architecture inside MathGov for reality-grounded, rights-constrained, tail-risk-aware, structurally viable governance. It helps people and systems see what is known, who is affected, where rights set hard floors, which risks are non-maskable, whether the structure can hold, and which options remain selectable.
Plainly: this is a public source/framework release you can read, audit, teach, test, and build around. It is not a black-box app, not a certification badge, not empirical validation, not ProofPack readiness, and not a replacement for lawful human authority.
§01 - The failure
Modern systems can look rational while losing contact with reality.
Dashboards, policies, models, reports, and approvals can create confidence while hiding rights exposure, uncertainty, catastrophic tail risk, and larger-system harm.
Catastrophe becomes a cell
Expected-value thinking can underweight low-probability, high-severity, irreversible, or lock-in risks.
Local wins damage wider systems
An organization can optimize its own target while degrading families, communities, institutions, ecosystems, or future resilience.
Metrics become masks
When indicators become targets, systems can optimize the proxy while degrading the outcome the proxy was meant to protect.
Authority replaces evidence
Institutional status, model confidence, consensus, or compliance language can be mistaken for verified reality-contact.
Unknown becomes zero
Missing evidence about rights, risk, sentience, stakeholders, or downstream harm must be recorded as unknown, not erased.
The constraint everything else serves
A high score cannot buy back a rights breach, a catastrophic-risk failure, or a CSV failure.
§02 - Core logic
Ethics made inspectable.
RippleLogic keeps the decision path visible: what was known, what remained uncertain, what was rejected, what survived, and why the final ranking was allowed.
Input: all candidate options
Output: admissible set, then ranked
RGLevel 1
Reality Grounding
Declare the reality surface, evidence trace, material unknowns, action boundary, consequence pathways, and claim boundary before any rights, risk, CSV, or scoring claim.
Blocks ungrounded or over-bounded claims
RFLevel 2
Rights Floor
Remove or redesign options that violate the Rights Floor. The Rights Floor is non-compensatory; protected interests are not traded for aggregate gain.
Rejects rights violations
TRCLevel 3
Tail-Risk Bound
Reject options with unacceptable catastrophic, irreversible, lock-in, or uncontrolled downside.
Rejects unbounded tail risk
CSVLevel 4
CSV / Structural Viability
Test whether claimed gains can stand without uncontained harm, structural hollowing, brittle dependencies, or larger-system degradation.
Rejects structural-viability failures
RLSLevel 5
Ripple Score
Rank the surviving options across multi-level union scopes and welfare dimensions. Scoring is downstream of admissibility.
Ranks only survivors
Sequence matters: the cascade is reality-grounded, lexicographic, and non-compensatory. A failed grounding, rights, tail-risk, or CSV layer cannot be bought back by a stronger downstream score.
§03 - Governance matrix
The ripple field, made visible.
Seven multi-level union scopes are mapped across seven welfare dimensions so consequences can be located, reviewed, and audited instead of collapsed into one flat number.
Full governance matrix: seven union scopes mapped across seven welfare dimensions.
Tip: click the matrix to open a large in-page viewer. Use Fit, 125%, or 150% to inspect the table without leaving the landing page.
Sequence matters: the matrix supports welfare mapping and auditability after Reality Grounding and the admissibility gates are respected. Rights floors, catastrophic tail-risk constraints, and CSV checks remain non-maskable. A high matrix score cannot override them.
Why this matters: the matrix makes ripple effects visible without pretending that scoring comes first. Reality Grounding declares the surface; RF, TRC, and CSV determine admissibility; RLS ranks only what survives.
Try the Navigator
§04 - Library
The synchronized core files.
These are the human-readable and implementation-facing artifacts for the current public release. GitHub remains the canonical record for version history, hashes, and verification context.
GitHub - canonical folder
MathGov Core v11.4 July 2 Release Folder
↗Canonical GitHub folder containing the synchronized Canon, SGP, Agent System, ripple.md Standard, Primer, Aligners Sheet, release notes, verification instructions, hashes, and source files.
DOCX - governing coreRippleLogic Canon v11.4
↓The governing decision architecture: Reality Grounding, Rights Floor, TRC, CSV, RLS, tiers, Appendix AD, and claim boundaries.
DOCX - moral statusSGP v6.4
↓The Sentience Gradient Protocol for protection-relevant moral-patient evidence across biological, ecological, and possible digital contexts.
DOCX - assurance wrapperripple.md Standard v4.4
↓The portable assurance wrapper for Decision Notes, evidence, reconstructability, falsifiers, refusal conditions, and scoped alignment claims.
DOCX - agent governanceAgent System v11.4
↓Platform-neutral control architecture for AI and hybrid agents governed by RippleLogic.
DOCX - human doorwayFoundations Primer v3.4
↓The clearest first read for teams, reviewers, educators, implementers, and non-specialist readers.
XLSX - worked exampleAligners Sheet v4.4
↓Worked-run/training companion for review and implementation preparation. Not a reference calculator, validator, certification, or ProofPack.
PNG - visual explainerGovernance Matrix
↓The visual 7 × 7 matrix showing multi-level union scopes mapped across seven welfare dimensions.
§05 - Release boundary
Strong enough to publish. Honest enough to bound.
The release is claimable as a Tier 1-3 source/framework specification and synchronized public package. It is not empirical validation, not legal certification, not deployment certification, not reference-calculator status, and not ProofPack readiness.
MathGov / RippleLogic Core Release v11.4 (2026-07-02)
Stable public documentation/source release anchored by RippleLogic Canon v11.4 and SGP v6.4. Ready for public review, education, tooling development, bounded pilots, shadow-mode testing, and independent critique.
Release tag: v11.4_2026_07_02
Release folder: releases/v11.4_2026_07_02/
Lead architect: James McGaughran · ORCID 0009-0005-3324-7290
Check the package before treating it as final.
$ release/VERIFY_RELEASE.md $ release/SHA256SUMS.txt
Use the SHA-256 manifest and verification instructions from the exact release package. The release files are designed for hash checking, container integrity review, version synchronization, workbook formula-error-token absence, and claim-boundary discipline.
- ✓Tier 1-3 source/framework specification and synchronized companion package.
- ✓Governing RippleLogic Canon v11.4 and SGP v6.4 core pair.
- ✓Auditable release package with SHA-256 manifest and verification instructions.
- ✓Public review, controlled external review, teaching, implementation study, and validation study design.
- ×Empirical validation across domains.
- ×Tier 4 readiness, ProofPack readiness, or reference-calculator status.
- ×Legal certification, deployment certification, or public-authority approval.
- ×Legal certification, deployment certification, policy authorization, solved AI alignment, or automated moral truth.
§06 - How to use it
Read, test, replay, improve.
Start with understanding before automating. Treat RippleLogic as a transparent decision record and governance discipline, not as a magic scoring machine.
Recommended path
- Start with the Foundations Primer for orientation.
- Read the Canon for the governing decision architecture.
- Read SGP for moral-status and protection handling.
- Use ripple.md when writing Decision Notes or assurance wrappers.
- Use the Agent System when building or evaluating AI and hybrid agents.
- Use the Aligners Sheet as a worked-run exemplar, not certification.
Best first applications
- →Policy analysis where rights, long-term risk, and externalities must be visible.
- →AI governance and agent runtime controls where logs, boundaries, and refusal behavior matter.
- →Institutional decisions involving multiple stakeholders, public trust, and hard tradeoffs.
- →Education and training for systems thinking, ethical reasoning, and transparent decision design.
MathGov RippleLogic Governance MatrixUse Fit, 125%, or 150%. Scroll inside the viewer when zoomed.
