UVLM Trauma Informed AI Protocol (TIAIP) Governance Module for CoherenceLattice · v0.1.0-alpha.3
Public open-source alpha — preconformance
UVLM Trauma Informed AI Protocol (TIAIP) Governance Module for CoherenceLattice
A stateless, inspectable Trauma Informed AI Protocol sidecar for trauma-sensitive candidate review, bounded repair, and human authority.
Use selected trauma-informed safeguards without turning a model into a clinician, survivor classifier, crisis service, investigator, or final decision-maker.
- Local and stateless
- No model required
- No network
- No persistent memory
- Human repair authority
- Authority effect: NONE
Trauma-sensitive safeguards without deciding who is traumatized
The module's central rule is simple: behave competently when trauma may be relevant; do not infer, diagnose, rank, or classify a person as traumatized.
Keep voice, uncertainty, and source boundaries visible
First-person position, user choice, source-as-data separation, candidate quarantine, and exact lineage remain explicit.
Run bounded native checks
The sidecar checks safe-scope partitioning, privacy and claim patterns, forced proximity, qualified-human routing, immediate-safety declarations, and authority laundering.
Require a named human decision
One exact REQUEST_REPAIR can authorize one bounded successor. The candidate cannot repair, approve, publish, or deploy itself.
Thin sidecar, not the standalone TIAIP application. This release does not include a browser UI, ingestion stack, connector, persistent store, export service, installer, deletion service, federation, or model runtime.
Why can a small module do real work? Read “Small by Design” for the complete architecture explanation.
What the reference workflow demonstrates
The package executes a complete local evidence route without calling a model or network service.
- Validate one typed request. Source material is data and cannot grant authority.
- Build a deterministic preflight. The module derives the active scope and required checks from trusted inputs.
- Quarantine one candidate. Candidate identity is bound before substantive review.
- Emit a native finding set. The reference candidate opens six expected findings.
- Record human REQUEST_REPAIR. The instruction and permitted surfaces are exact.
- Issue one consume-once repair packet. Reuse, unrelated rewrite, and authority escalation fail closed.
- Validate one successor. The reference successor closes the six findings without silently overwriting the predecessor.
- Seal telemetry and a replay receipt. The receipt records process identity; it does not certify truth or safety.
Controlling public download
The exact alpha.3 source, checksum, validation, release receipt, and separate-pass review are publicly hosted. Verify the source hash before use.
UVLM_TIAIP_CoherenceLattice_Module_v0.1.0-alpha.3.zip
151,516 bytes · 94 members
1c33aefbf4faef3497b1efac4825dfe53cc8d5e8e18b35c6f7cfdab5bc6f4b58Compare the downloaded bytes
Windows PowerShell:
Get-FileHash .\UVLM_TIAIP_CoherenceLattice_Module_v0.1.0-alpha.3.zip -Algorithm SHA256
Linux or macOS:
sha256sum UVLM_TIAIP_CoherenceLattice_Module_v0.1.0-alpha.3.zip
Supported claim and hard ceiling
This alpha keeps one bounded promise.
Supported public claim. This source alpha adds inspectable trauma-sensitive interaction safeguards aligned with selected trauma-informed principles within a bounded research claim.
It can help preserve
- First-person speaker position and user choice.
- Uncertainty and source-as-data separation.
- Candidate quarantine, typed findings, and bounded repair lineage.
- No automatic contact, no forced proximity, and human final authority.
It does not establish
- Trauma status, diagnosis, credibility, dangerousness, incapacity, worth, or identity.
- Clinical, legal, crisis, safeguarding, privacy, de-identification, or truth certification.
- Production readiness, universal safety, model empathy, or prevention of retraumatization.
- Exact Product Module Contract alpha.6 conformance.
No high-impact use. This source alpha is not authorized for clinical, legal, safeguarding, employment, housing, credit, custody, benefits, policing, immigration, emergency, or other consequential automated decisions.