THE KHÁNH INTELLIGENCE MATRIX (TKI MATRIX) A Bottom-Up Interdisciplinary Research Framework for Intelligence Recognition in Biological and Social Systems

Intelligence is commonly investigated through cognitive abilities, learning performance, adaptation, problem-solving and measurable behavioural outcomes. However, an additional question deserves systematic investigation: how do biological and social systems recognize, evaluate and respond to intelligence? The recognition of intelligence may influence whom individuals learn from, whose knowledge they trust, how knowledge is distributed and whether a system rewards genuine competence or merely the appearance of competence. This paper introduces the Khánh Intelligence Matrix (TKI Matrix), an interdisciplinary research framework designed to investigate intelligence recognition through a bottom-up approach. Rather than beginning with a universal definition or a predetermined classification of intelligence, the framework begins with observable mechanisms and measurable interactions at biological, individual, interpersonal and collective levels. The framework distinguishes actual competence, self-assessed competence, recognition received from others, reputation, recognition motivation and subsequent learning behaviour. It proposes twelve initial research variables, ten research questions and six falsifiable hypotheses. Three complementary research programmes are outlined: controlled human experiments, comparative animal social-learning studies and agent-based computational simulations. The central proposition is that recognition and competence are related but not necessarily identical. When recognition becomes detached from demonstrated competence, systems may develop feedback loops that favour reputation, status or performance displays over learning and error correction. This proposition remains an empirical research question rather than an established universal law. The TKI Matrix aims to provide a revisable research architecture for understanding how intelligence is recognized and how recognition mechanisms influence the development of knowledge across biological and social systems.