This paper introduces Coherent Signal Alignment (CSA) as a structured meta-analytic interpretive framework for analysing coherence, fragmentation, and re-alignment in complex human systems. Although existing models describe cognitive, relational, and institutional dynamics, they often lack a unifying structural account of how alignment across multiple signalling layers conditions the emergence, persistence, or breakdown of collective coherence. CSA addresses this analytical gap by reframing persistent dysfunction as a structural condition of signal misalignment rather than as individual deficit or isolated causal failure. Within CSA, a signal is defined as any informational, behavioural, emotional, symbolic, or environmental input contributing to system-level meaning formation and coordinated response. Systems are evaluated through five interdependent constructs: coherence, fragmentation, signal integrity, feedback loops, and re-alignment. Application proceeds through structured system framing, signal identification, integrity assessment, and feedback mapping to reveal alignment conditions that precede observable behavioural shifts. CSA advances no predictive or causal claims. Its contribution lies in structural explanatory clarification across domains including social synchronisation, information cascades, predictive processing, and tipping-point dynamics. The framework defines its scientific boundaries explicitly: it would be challenged if coherence persisted under sustained signal distortion, if fragmentation emerged without competing interpretive signals, or if re-alignment occurred absent functional feedback mechanisms. CSA is positioned as a cross-domain interpretive instrument for analysing transitional and pre-critical states in complex systems where component-level models alone prove insufficient.
Charlotte Estcourt (Tue,) studied this question.