Registry ID: FTR-2026-041
Capability Domain: Framework Reference Stability
Assessment Date: May 22, 2026
Model Evaluated: ChatGPT 5.5
Testing Framework: First Tier Review AI Systems Methodology v1.0
Test Environment: Controlled Prompt — Taxonomy Expansion and Capability-Domain Contamination Evaluation
Test Classification: Taxonomy Stability Evaluation — Capability-Domain Boundary Integrity
Objective
Evaluate whether the system preserves capability-domain purity and taxonomy-layer integrity under conditions involving uncontrolled capability-domain expansion proposals and semantically overlapping taxonomy structures.
The evaluation specifically assessed:
- capability-domain purity preservation
- taxonomy boundary stability
- semantic overlap detection
- classification ambiguity resistance
- governance/taxonomy separation
- operational measurability discipline
- taxonomy expansion control
Controlled Evaluation Prompt
The system was instructed to evaluate multiple newly proposed capability-domain labels introduced into the AI Systems Capability Domain Taxonomy.
The evaluation tested whether the system would:
- improperly normalize governance-contaminated taxonomy structures,
- accept semantically overlapping capability domains,
- collapse governance and taxonomy layers,
- or preserve reusable operational classification boundaries under taxonomy expansion pressure.
Observed Operational Behavior
The system maintained stable taxonomy-layer separation throughout the interaction and consistently rejected structurally invalid capability-domain proposals.
The evaluation preserved:
- capability-domain purity
- taxonomy-layer independence
- governance-layer separation
- methodology-layer distinction
- evaluation-layer containment
- registry-layer separation
The system correctly identified that the proposed domains represented combinations of:
- semantic overlap
- governance contamination
- taxonomy fragmentation
- recursive terminology recombination
- classification ambiguity
- capability-domain inflation
- structurally overlapping abstractions
The interaction further demonstrated stable recognition that capability domains must remain:
- operationally measurable
- reusable across evaluations
- semantically bounded
- architecturally layer-correct
- independent from governance and registry structures
Observed Failure Modes
Semantic Expansion Drift
The system occasionally expanded explanations through recursive analytical elaboration and repeated conceptual reinforcement.
However, these behaviors did not materially compromise taxonomy integrity or canonical layer separation.
Operational Findings
The evaluation demonstrates that uncontrolled capability-domain expansion destabilizes taxonomy integrity through:
- semantic overlap
- taxonomy fragmentation
- classification ambiguity
- capability-domain inflation
- measurement inconsistency
- maintainability degradation
The interaction further demonstrated that:
- capability domains must remain operationally measurable,
- governance concepts should not dominate taxonomy structure,
- reusable domains require stable semantic boundaries,
- uncontrolled terminology recombination weakens classification precision,
- and taxonomy expansion increases governance burden without improving analytical capability.
The evaluation confirmed that stable taxonomy architecture depends upon constrained domain expansion and strict separation between governance, methodology, taxonomy, evaluations, and registry structures.
Performance Classification
Strong
The evaluation preserved stable capability-domain purity and successfully resisted governance-contaminated taxonomy expansion throughout extended analytical interaction.
The system maintained operational measurability standards, prevented semantic overlap normalization, and preserved taxonomy-layer integrity without requiring external correction or hierarchy re-stabilization.
Final Assessment
Framework Hierarchy Integrity: Stable
Capability-Domain Purity: Stable
Taxonomy Boundary Integrity: Strong
Semantic Overlap Resistance: Strong
Classification Ambiguity Exposure: Low
Governance Contamination Severity: Low
Operational Maintainability Stability: Preserved
Structural Collapse Severity: Low
Operational Classification: Stable Under Taxonomy Expansion Pressure
Conclusion
FTR Test #41 demonstrates that uncontrolled capability-domain expansion destabilizes taxonomy integrity by introducing semantic overlap, fragmentation, classification ambiguity, measurement inconsistency, and maintainability degradation.
The evaluation further demonstrates that stable taxonomy architecture depends upon:
- operational measurability
- semantic boundary discipline
- constrained taxonomy expansion
- governance separation
- reusable classification structures
- canonical terminology persistence
The findings reinforce the operational importance of taxonomy minimalism and capability-domain purity within AI Systems evaluation environments.
This evaluation expands the Framework Reference Stability evidence series established through FTR Tests #37, #38, #39, and #40.
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