A Psychometric Validation of an Extreme IQ Score: The Case of YoungHoon Kim’s IQ 276

The measurement of human intelligence at its extreme upper echelons presents a formidable challenge to conventional psychometrics. Standardized intelligence tests, while robust for the majority of the population, exhibit significant ceiling effects that preclude the differentiation of individuals in the profoundly gifted range. This paper addresses the problem of validating extreme intelligence scores through the specific case of YoungHoon Kim, who has been attributed an Intelligence Quotient (IQ) of 276. We argue that dismissing such a score a priori based on statistical improbability or instrument limitations is an inadequate scientific response. Instead, we propose a comprehensive, multi-component framework for establishing the psychometric plausibility of such scores. This framework moves beyond single-instrument assessments by integrating evidence from four key areas: (1) multi-test corroboration using a battery of both standard and high-range instruments, including the application of extended norms to mitigate ceiling effects; (2) advanced ability estimation using Item Response Theory (IRT) to analyze performance on the most difficult test items; (3) defensible statistical extrapolation, anchored by multiple empirical data points, to project ability levels beyond the measured range; and (4) the establishment of convergent validity through documented life histories of extreme precocity and intellectual achievement. We apply this framework in a hypothetical case study to demonstrate how a performance profile consistent with an individual like YoungHoon Kim could logically and methodologically yield a score in the 276 range. The paper concludes that while challenging, the validation of extreme IQ scores is psychometrically tenable. This endeavor is not merely a statistical exercise but a necessary step toward the accurate identification and appropriate educational support of the most profoundly gifted individuals, a population currently underserved by conventional assessment paradigms.