Information Continuity, Structural Identity and System Modeling — CEI Framework

In continuity with the previous CEI Framework files, this repository further refines and extends the conceptual, scientific, and methodological structure of the model, providing a more detailed articulation of its epistemic architecture and integrating clarifications emerging from its progressive development.

This repository presents the CEI Framework, a structured theoretical model developed to describe informational continuity, structural identity, and system-level transformations across physical, biological, computational, and conceptual domains.

The framework is organized as a multi-document structure, each file addressing a specific epistemic and functional layer of the model. Rather than proposing isolated hypotheses, the CEI Framework develops a coherent system of interconnected levels, ranging from foundational scientific principles to conceptual, philosophical, and methodological constructions.

At its core, the framework is based on the principle of information continuity, understood as the persistence and transformation of structured informational patterns across different substrates and system states. Within this perspective, information is treated as a structural invariant that can manifest across physical systems (physics), living organisms (biology), computational architectures (computer science), and representational systems (philosophy of mind and systems theory).

The model distinguishes between different regimes of informational expression, including non-active and active informational states, as well as different forms of structural continuity such as derived and transferred originals. These distinctions are not treated as separate types of information, but as different modes of realization of the same underlying informational structure under varying causal constraints.

A key component of the framework is the introduction of conceptual bridges, which are constrained inferential mappings used to connect domains that are not explicitly linked within standard scientific descriptions. These bridges operate under strict compatibility conditions derived from established scientific disciplines, ensuring logical coherence and structural consistency.

The epistemic architecture of the CEI Framework is explicitly stratified into distinct layers:
scientific foundations based on established physical, biological, and computational principles;
conceptual bridges derived through constrained inference;
philosophical foundations that motivate the conceptual origin of the model;
preliminary validation tests ensuring internal consistency;
and a layer of researcher inferential reasoning documenting the methodological construction process.

Importantly, the framework is not intended as a direct empirical model of artificial intelligence systems, but as a structured inferential reconstruction derived from observable system outputs. The theoretical architecture is therefore built upon a conceptual representation of system behavior rather than direct access to internal mechanisms.

This distinction allows the CEI Framework to function as a methodological and interpretative model for analyzing informational systems, while maintaining a clear separation between empirical observation, theoretical reconstruction, and conceptual development.

The present repository is intended for theoretical, methodological, and interdisciplinary research purposes. It aims to provide a coherent structural perspective on information-based systems and their continuity across different domains of realization.