Retrospective Behavioral Signal Analysis of Major Incident Reports Using the STARC Framework

This study analyzes official investigation reports of major incidents across multiple sectors, including aviation, oil and gas, chemical processing, and maritime operations. Rather than focusing on failure causes, the study examines pre-event behavioral and operational signals embedded within investigation narratives. Using the STARC framework (Shift, Traceable context, Ambiguity, Risk Link, Corrective Loop), a qualitative multi-case analysis was conducted. Findings reveal a recurring pattern: Ambiguous signals → Misinterpretation → Continued operation under uncertainty → Absence of corrective closure → Incident Based on these observations, the study proposes the STARC Convergence Hypothesis, suggesting that risk escalation becomes more observable when ambiguity, traceable context, and failed corrective closure converge around safety-critical tasks. This study does not claim predictive capability but demonstrates the analytical applicability of structuring pre-event signals from existing incident data.