Segmentation and Indexing of Structural Clusters: A Phenomenology of Verbalization in Abstraction-Biased Cognition

This paper presents a phenomenological case study, based on self-observation, of a cognitive style in which sensory and structural understanding arises prior to formal terminology and explicit definition. In educational settings and common evaluative frameworks, understanding is often identified with verbal explanation and sequential output. However, in some cognitive structures, understanding first emerges in compressed, spatial, relational, and experiential form, and only later becomes translatable into socially shareable language. Through examples drawn from image reading, Zeno’s paradox, and multiplication tables, this paper describes the characteristics of such understanding-first cognition. It focuses in particular on the fact that, in abstraction-biased cognition, the many images and knowledge candidates that arise in the mind are not merely irrelevant excess, but rather simultaneously present as connected Structural Clusters without stable labels or boundaries. External tasks demand that relevant elements be selected and presented in an orderly form; yet this requires first assigning labels, identifying conceptual units, and transforming them into operable indices. The paper reinterprets this difficulty not as a deficit of understanding, but as the cost of segmenting, indexing, and verbalizing unlabeled Structural Clusters so that they become compatible with external forms. It also argues that the cross-disciplinary character of the author’s paper corpus reflects the fact that structural relations spanning multiple domains are originally apprehended as a single connected whole.