Meaning Preserving Error Correction - A Symbolic Framework for Semantic Communication

Classical communication theory treats information as sequences of bits whose correctness is defined by exact identity. Yet human communication, cognitive systems, and semantic technologies do not operate under such rigid constraints. Meaning can survive distortion, omission, or substitution, provided the core semantic structure remains intact. This paper develops a symbolic theory of error correction in which the fundamental units of transmission are semantic or symbolic entities rather than binary digits. Drawing on a symbolic finite‑field construction and a meaning‑weighted extension of Reed–Solomon coding, I argue that communication systems should be evaluated by semantic fidelity rather than bit‑level accuracy. The resulting architecture preserves meaning under noise, degrades gracefully, and provides a formal foundation for symbolic communication, AI inference, and human‑machine interaction. Meaning‑preserving error correction constitutes a new paradigm for the philosophy of information, formal semantics, and cognitive science.