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Complex systems often exhibit a \"Robust Yet Fragile\" (RYF) paradox: structures optimized for specific functions are highly resilient to anticipated perturbations but vulnerable to unexpected ones. Concurrently, the prevalence of scale-free architectures with intermediate tail exponents ($2 < \\gamma < 3$) contradicts naive Maximum Entropy (MaxEnt) predictions favoring maximal heterogeneity ($\\gamma \\to 2$). This paper resolves these contradictions by introducing a Duality Theory of Robustness and proving the Principle of Maximal Heterogeneity (PMH), formalized within Majorization Theory. We distinguish between Entropic Robustness (R-I, Schur-concave), resisting stochastic (Type-S) noise, and Structural Robustness (R-II, Schur-convex), resisting targeted (Type-T) stress. We rigorously prove that R-I manifests as a universal, accelerating (convex) information-theoretic force driving $\\gamma \\to 2$. Conversely, R-II drives the system toward order ($\\gamma \\to \\infty$). The observed intermediate $\\gamma^*$ represents an equilibrium optimizing the universal trade-off between these opposing forces. This framework provides a rigorous foundation for the RYF paradox and offers a falsifiable prediction: any deviation from $\\gamma=2$ implies active optimization against Type-T structural constraints.

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