THE DOMAIN-GENERAL RELATIONAL TRANSFORMATION PRINCIPLE (DGRTP)

Relational dependence appears in many scientific and analytical settings, including physical measurement, subjective experience, information processing, system behavior, statistical evaluation, and decision-making. However, these settings do not share a single output type, measurement scale, transformation family, or causal mechanism. A general account must therefore distinguish a reusable formal architecture from the domain-specific models instantiated within it.The paper proposes the Domain-General Relational Transformation Principle (DGRTP), a candidate meta-theoretical framework for representing the dependence of an outcome on a target state and a relevant relational configuration. Each domain is represented by a typed mathematical model containing a state space, a condition space, an output space, an outcome map, an admissible transformation family, a comparability structure, and model parameters. A proposed operational procedure, the Relational Configuration-Outcome Transformation Mechanism (RCOTM), organizes model construction, transformation analysis, comparability assessment, causal scrutiny, and validation.The framework distinguishes numerical difference from structural change, empirical association from causal influence, and formal generality from demonstrated universality. It also distinguishes invariance from covariance and prohibits cross-domain transfer without a justified structure-preserving mapping. A proposed primary case, Cross-Reference Temporal Experience Divergence (CTED), examines the difference between physical duration, experienced passage, duration estimation, and retrospective temporal judgment. This case illustrates how the framework may be operationalized without making time the universal medium of the theory.The manuscript specifies a provisional axiomatic vocabulary, mathematical architecture, research modules, testable hypotheses, falsification criteria, and a staged research protocol. DGRTP is presented as a research proposal rather than an empirically established universal law. Its scientific contribution remains contingent on formal consistency, literature comparison, empirical validation, and successful demonstrations of structural transfer across independently investigated domains.Keywords: relational transformation; domain-general framework; measurement theory; reference dependence; invariance; covariance; comparability; formal modeling; systems theory; cross-domain generalization.