Beyond the Dataset: Why SignalRupture Cannot Be Locally Validated — and How It Is Structurally Constrained

This paper defines the epistemic boundaries, evaluative conditions, and structural limitations of the SignalRupture (SR) framework. It clarifies why SR cannot be validated or invalidated through isolated datasets, bounded institutional studies, or local contradictions operating at the population layer. As the paper states, SR “operates at the system layer, modeling the generative dynamics that produce local variation rather than the variation itself.” Local observations therefore represent outputs of systemic processes, not direct tests of the generative structures SR models. At the same time, SR is not insulated from empirical reality. The framework is structurally constrained by the large‑scale, longitudinal, and cross‑domain patterns that emerge across institutions over time. The paper formalizes these constraints, distinguishing between population‑layer metrics (caseloads, performance indicators, throughput measures) and system‑layer dynamics (infrastructural drift, fragmentation, compensatory adaptation, coordination strain). It establishes the analytical altitude at which SR operates, the conditions under which critique is meaningful, and the operational boundaries necessary to prevent explanatory overextension. The paper concludes that SR should be evaluated through cross‑domain recurrence, longitudinal structural alignment, infrastructural pattern convergence, and systemic explanatory coherence, rather than isolated population‑level observations.