MindArc: An Integrative Mind Architecture — A Theoretical and Methodological Proposal
Year: 2026
Type: preprint
Abstract: Assessment of people at work can conflate three things: the state a person is in during a single episode, the competency displayed in that episode, and the enduring structure that recurs across episodes. This article presents MindArc, an integrative mind architecture that reads all three from one structure of three layers, eight depths, 24 components, and 17 resultants (R) computed from the components. The Experience and Action layer (L1) codes an episode's action and consequence, cue, mental image, and drive with dimensions of two to four values. The Meaning and Regulation layer (L2) pairs four understanding tasks with four regulation tasks into four lines; every task has two poles, and competency has two sides, Understanding (R4–5) and Management (R4–6), read from which lines carry a number in the code, in the domain set by the drive (R4a). The Structure and Constraint layer (L3) is read only across many real episodes and yields five resultants, including Core Values and Needs (R7a), Conditional Attachment (R8a), Condition State (R8), and the cross-depth Need Approach (R7–8). Relations among components are recorded in a 301-record registry with evidence levels; the article cites 325 checked works and separates direct support from related work. It is a conceptual synthesis built on a model-driven integrative review, not a systematic review, and the model has not yet been tested empirically. It proposes a method in which respondents answer each part from a real event in their own lives that matches it, a plan for checking its reliability, and 26 testable hypotheses. This record holds the article in Thai and English with Supplementary Materials S1 (master architecture, public edition) and S2 (relationship registry, 301 records, public edition), each in Thai and English. Four part articles, published as separate records, give each pair of depths in detail.
Author: Jirakankorn, Akira
Language: English
Subfield: Applied Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7225464171