DOI: 10.3390/complexities2030023 ISSN: 3042-6448

Beyond Shannon Entropy in Schelling Segregation: Shape-Weighted Diagnostics of Bimodality, Polarization, and Economic Freezing

George-Rafael Domenikos, Lock Yue Chew

Generalized Schelling models extend the classical relocation framework by introducing additional agent attributes, interaction rules, and mobility constraints. We study four variants within a common lattice formulation: a modified movement-only baseline, a local affiliation-interaction model, a model with local and random long-range interactions, and a monetary model in which movement and communication consume resources. The simulations use a 64×64 lattice and are evaluated over 30 independently seeded runs per scenario, with means and 95% confidence intervals reported throughout. At each step, occupied agents are classified as bound, activated, or, in the monetary scenario, trapped. Their conditional affiliation distributions are evaluated using Shannon entropy and a shape-weighted diagnostic whose fitted components distinguish normal-like, heavy-tailed, and bimodal structures. The diagnostic is interpreted jointly with its fitted weights and the underlying histograms rather than as a unique scalar reconstruction of shape. Validation against the bimodality coefficient, Esteban–Ray polarization, Moran’s I, and sign assortativity separates distributional polarization from spatial segregation. The interaction-driven scenarios develop strongly polarized two-lobed bound-state distributions, while the monetary model additionally produces resource-constrained dynamical arrest. The results are robust across independent initial conditions and random streams; separate extended-horizon checks to 500 steps showed no qualitative reversal. The same regimes persist on 96×96 and 128×128 lattices and under one-factor variations of satisfaction, vacancy, long-range-contact, and monetary-cost parameters. The framework therefore complements Shannon entropy by exposing distributional geometry that uncertainty alone does not encode.