THE DYNAMIC EPISTEMIC CLASSIFICATION AND TRANSITION ARCHITECTURE (DECTA)

AbstractScientific disciplines are frequently described using labels such as hard science, soft science, formal science, and interpretive inquiry. However, these labels do not arise from a single universally accepted numerical rule. Quantifiability, mathematical formalization, measurement validity, evidential strength, reproducibility, predictive performance, and generalizability are distinct characteristics. A domain may score highly on one dimension while remaining limited on another.Classification becomes more complicated when new theories, claims, measurement techniques, methods, and subdomains enter the knowledge domain. An aggregate measurability percentage may decrease because the domain has expanded, even when its previously evaluated claims have not deteriorated. Conversely, an increase in mathematical formalization does not automatically establish an increase in empirical validity.This manuscript proposes the Dynamic Epistemic Classification and Transition Architecture (DECTA), a multidimensional, systems-theoretic framework for evaluating scientific knowledge domains over time. Its central mechanism is Trigger-Projection-Feedback-System Response. The architecture distinguishes claim-level evaluation from subdomain-level and domain-level classification; separates fixed-scope change from scope expansion; and treats classification transition as a rule-governed outcome rather than an automatic consequence of a single percentage.The framework specifies candidate variables, operational definitions, weighted indices, validity gates, state-transition functions, threshold-calibration procedures, uncertainty-aware prediction, hysteresis as an optional control mechanism, a primary psychological case, cross-domain comparison, falsifiability conditions, simulation scenarios, and a longitudinal validation protocol.DECTA is presented as a formal theoretical proposal rather than an empirically established universal law. Its equations are candidate formalizations whose operational validity, parameterization, comparative performance, and cross-domain applicability must be evaluated through transparent and independently reproducible research.Keywords: scientific classification; hard science; soft science; formal science; quantifiability; measurement validity; epistemic maturity; domain expansion; dynamic systems; state transition; reproducibility; generalizability; threshold calibration; DECTA.