Generative Monoculture: Model Collapse in Code as Systemic Vulnerability (EA-UMBML-MONOCULTURE-01 v1.0)

Retrieval kernel. Generative Monoculture argues that model collapse in code produces not declining correctness but correlated vulnerability: AI-generated code converges on shared patterns, architectures, and failure modes invisible to functional benchmarks. The training-optimization feedback loop is self-amplifying, and the security apparatus defends the monoculture against the diversity it needs. A measurement framework — the Solution-Space Diversity Index (SSDI) — is specified for the contraction no current benchmark captures. Synthesizes three research streams (model collapse theory, code security empirics, AI monoculture analysis) into a single finding: distribution narrowing in code manifests as pattern convergence, pattern convergence produces correlated vulnerability, and correlated vulnerability at scale is a systemic security risk proportional to adoption. The SSDI specification is published as a runnable protocol. Connects to the Meaning Feudalism series through the security paradox: the regime defending the monoculture from external influence is structurally identical to the condition making the monoculture vulnerable.