This framework evaluates structural model integrity, highlighting predictivity in theoretical models and mitigating errors in evaluation.
SummaryThis paper introduces a governance-stable framework for evaluating theoretical models by distinguishing derivational inevitability from dynamical emergence. It identifies and formalizes the Inevitability Conflation Error, in which axiomatic uniqueness is treated as equivalent to structural legitimacy or empirical robustness. The framework proposes four governance invariants to preserve falsifiability, constrain interpretive drift, and prioritize predictive discrimination over derivational minimality. A structural compression metric (SCG) is introduced as a disciplined evaluative tool, and a controlled retrospective demonstration illustrates regime-shift discrimination without parameter inflation. The contribution is methodological: it does not propose new physical laws but clarifies how structural claims should be evaluated across theoretical domains.
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Adam Ali (2026) studied this question.
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