Empirical Application of SignalRupture: A System-Level Analysis of Technology Companies

Empirical Application of SignalRupture: A System‑Level Analysis of Technology Companies — Field Paper IV applies the SignalRupture framework to large‑scale technology firms, including platform ecosystems and AI‑driven organizations. Unlike public institutions, technology companies operate with high adaptability, substantial resources, and rapid iteration cycles, making them a critical boundary test for SR’s generality. The analysis evaluates six SR signatures—latency persistence, policy churn, buffer compression, automation under strain, downward regulation, and fragmentation—across a decade of extreme scaling complexity. While traditional signals such as latency and buffer collapse are partially mitigated through computational optimization and resource flexibility, the system exhibits strong policy churn, compensatory automation, ecosystem fragmentation, and pronounced downward regulation onto users, developers, and creators. With an SRI score of 15/18, the findings demonstrate that SR signatures persist even in adaptive, high‑resource environments, indicating that SR describes not only institutional failure under constraint but structural reorganization under scale.