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The aim is to develop a diagnostic framework for understanding structural regimes in dynamics of majority-minority fields using hierarchy metrics.

May 20, 2026Open Access

A Diagnostic Framework for Structural Regimes in Majority-Minority Field Dynamics

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Randomized trial uncovers distinct structural regimes in majority-minority dynamics, suggesting improved diagnosis methods.

The aim is to develop a diagnostic framework for understanding structural regimes in dynamics of majority-minority fields using hierarchy metrics.
Introduced hierarchy vector (C, A, D) for characterizing field configurations.
Evaluated the framework over a 500-step trajectory with 100-node fields under varying conditions and methods.
Validated findings across different models to ensure robustness and accuracy of structural regime identification.
Identified three distinct structural phases with 93-97% agreement across methods and parameter variations.
Proved that no weighted scalar can replace the hierarchy vector, with H conflating 110 timesteps.
C–A anti-correlation (r=−0.677±0.032) and D near-independence under ±10% perturbation.

Justin D. Gallant (2026) studied this question.

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May 20, 2026Open Access

View Full Paper

Ask AI

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Authors

Randomized trial uncovers distinct structural regimes in majority-minority dynamics, suggesting improved diagnosis methods.

The aim is to develop a diagnostic framework for understanding structural regimes in dynamics of majority-minority fields using hierarchy metrics.
Introduced hierarchy vector (C, A, D) for characterizing field configurations.
Evaluated the framework over a 500-step trajectory with 100-node fields under varying conditions and methods.
Validated findings across different models to ensure robustness and accuracy of structural regime identification.
Identified three distinct structural phases with 93-97% agreement across methods and parameter variations.
Proved that no weighted scalar can replace the hierarchy vector, with H conflating 110 timesteps.
C–A anti-correlation (r=−0.677±0.032) and D near-independence under ±10% perturbation.

Justin D. Gallant (2026) studied this question.

View Full Paper

Ask AI

Bookmark