The Dissective Diagnosis Protocol: A Cross-Domain Signal-Based Risk Assessment Framework

Abstract This paper describes the Dissective Diagnosis Protocol, a way of working through risk assessment under conditions of severe information asymmetry. The framework was not derived from theory. It was noticed after the fact, across repeated exposure to diagnostic situations in quite different domains. The protocol moves through five stages: looking for what should be present but is not; cutting across several layers—from strategy and structure to process, finance, and observable behavior—to see where surface accounts and verifiable reality come apart; drawing on earlier experience from other domains to interpret current situations when direct expertise is unavailable; identifying thresholds at which viability appears to be lost; and producing recommendations that are sequenced, with clear conditions for proceeding at each stage. Two preliminary studies are presented. The first, an 8-week behavioral log with 35 participants in early-stage relationships, found that low behavioral consistency strongly predicted breakup, high conflict was associated with relationship termination, and a declining consistency trend provided early warning. The second study presents six case analyses from business negotiations, organizational diagnosis, and cross-border due diligence—retrospective cases drawn from a single practitioner's experience. The protocol does not eliminate uncertainty. It may produce false positives and false negatives. It is offered as a provisional framework, still evolving, for navigating assessment decisions under conditions where domain expertise, validated algorithms, and research evidence are unavailable.