Distinguishing Consciousness from Awareness

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Authors: Alison Jane King
Cited by: 0

Abstract

This paper introduces the C–A Framework, a testable, evolutionary model that distinguishes between consciousness (C) as a baseline capacity for experience and awareness (A) as an emergent, organisation-dependent phenomenon. The framework proposes that awareness arises through an evolutionary progression of increasing organisational complexity and integration, forming a structured continuum from non-representational physical systems, through biological organisation, to experiential awareness (A₁) and recursive self-awareness (A₂). Rather than treating consciousness as synonymous with cognition, behaviour, or information processing, the C–A Framework separates the capacity for experience from the structural conditions under which it becomes organised. This distinction addresses longstanding ambiguities in terminology across neuroscience, cognitive science, and philosophy of mind. Drawing on principles from complexity science, information theory, and existing models such as Global Workspace Theory, Integrated Information Theory, and Predictive Processing, the framework situates these approaches as describing mechanisms within awareness, rather than explanations of consciousness itself. The model introduces the concept of an integration threshold, at which sufficient organisational complexity gives rise to experiential awareness, and outlines a testable pathway for identifying transitions between awareness states across biological and artificial systems. By situating awareness within an evolutionary and systems-based context, the C–A Framework provides a structured approach for investigating the relationship between neural organisation and conscious awareness, while generating empirically testable predictions.

Fields of Study & Subjects

Philosophy and Theoretical Science Embodied and Extended Cognition Cognitive Science and Education Research

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
16 March 2026
Language
EN