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Theorems — Dynamic Semiotics

Every theorem derives from Axiom-0. Classical results emerge as degenerate limits.

10 theorems across 1 modules

Catalog

IDNameModule
T-S-1Tier-1 Kernel Identities Hold for All 30 Sign Systems.semiotic_theorems
T-S-2Symbolic Recursion and Interpretant Depth Jointly Anchor IC.semiotic_theorems
T-S-3Dead Languages Preserve Coherence Through Frozen Channels.semiotic_theorems
T-S-4Formal Systems Have Extreme Channel Profiles.semiotic_theorems
T-S-5Iconic Persistence and Symbolic Recursion Are Inversely Related.semiotic_theorems
T-S-6Natural Languages Are Balanced but Mediocre.semiotic_theorems
T-S-7Animal Communication Systems Have High Drift.semiotic_theorems
T-S-8High Semiotic Density Correlates with Higher Fidelity.semiotic_theorems
T-S-9Formal > Chemical > Natural in Ground Stability Contribution.semiotic_theorems
T-S-10Semiotic Categories Form a Drift Hierarchy.semiotic_theorems

Semiotic Theorems

Source: closures/dynamic_semiotics/semiotic_theorems.py

T-S-1: Tier-1 Kernel Identities Hold for All 30 Sign Systems.

T-S-2: Symbolic Recursion and Interpretant Depth Jointly Anchor IC.

T-S-3: Dead Languages Preserve Coherence Through Frozen Channels.

T-S-4: Formal Systems Have Extreme Channel Profiles.

T-S-6: Natural Languages Are Balanced but Mediocre.

T-S-7: Animal Communication Systems Have High Drift.

T-S-8: High Semiotic Density Correlates with Higher Fidelity.

T-S-9: Formal > Chemical > Natural in Ground Stability Contribution.

T-S-10: Semiotic Categories Form a Drift Hierarchy.


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