This new Working Paper develops the General Framework for Measuring Institutional Cognition (GFMIC), the first comprehensive scientific architecture designed to transform institutional intelligence into an empirically observable and systematically measurable phenomenon.
Building upon the theoretical foundations established throughout the previous Working Papers of Research Line L01, in the study we argue that institutions should be understood as distributed cognitive systems whose intelligence emerges through the interaction of perception, attention, memory, learning, reasoning, decision-making, coordination, adaptation, anticipation and metacognition operating across both human and artificial components.
The paper proposes a multidimensional measurement framework capable of identifying these latent cognitive processes, establishes methodological principles governing empirical investigation, develops cognitive indicators and composite measurement architectures, and explores qualitative, quantitative, experimental and simulation-based research methodologies.
Later, it further examines practical applications in governance assessment, institutional self-reflection, benchmarking, organisational reform and Human–AI governance while outlining the future development of Institutional Cognition as an international empirical research field. Rather than presenting measurement as a static evaluative exercise, the framework positions cognitive observation as the starting point of recursive institutional learning, continuous adaptation and cumulative scientific development.
We conclude that measuring institutional cognition constitutes a foundational step towards the emergence of a global empirical science of institutional intelligence capable of supporting more adaptive, resilient and cognitively mature governance systems throughout the Human–AI era.
