THE THEORY OF PREDICTIVE EMERGENCE: A Geometric Framework for Behavioral Stability

THE THEORY OF PREDICTIVE EMERGENCE: A Geometric Framework for Behavioral Stability Philip Morisky, MBA, Adherence, Long Beach, California, USA philip.morisky@adherence.cc https://www.linkedin.com/in/philip-morisky/ https://orcid.org/0009-0008-3443-9229 A Geometric Framework for Behavioral Stability Sustained behavioral patterns across complex human systems exhibit a persistent paradox: prediction succeeds, while intervention fails to improve population outcomes. In applied domains including medication adherence, validated instruments detect nonadherence with high sensitivity, yet population-level outcomes remain largely unchanged. This gap suggests that prediction and intervention operate under different mathematical rules. This paper proposes the Theory of Predictive Emergence. The theory treats behavioral systems as points in a three-dimensional space defined by Architecture, Execution, and Context. These dimensions multiply together rather than add up. A weakness in one dimension cannot be compensated by strengths in the others. The formula V = (A × E × C)^(1/3) captures this relationship. When V falls below 0.70, behavioral patterns tend to collapse. Above this value, they hold relatively steady. Six testable predictions follow from this framework, each with clear numerical criteria for acceptance or rejection. The theory has not been tested yet. No validation data exist. If the data support this framework, it may explain why we measure accurately but intervene poorly. The problem is not bad measurement. The problem is that we intervene without identifying which structural dimension constrains the system. Keywords: behavioral dynamics, state space models, applied behavioral systems, dimensional necessity, noncompensatory systems The author welcomes methodological critique, theoretical feedback, and collaboration for prospective empirical testing.