Structural Grammar
Bias Interaction Archetypes
What are Bias Interaction Archetypes?
Paradigm Dynamics presents a core conceptual framework for structurally modeling cognitive distortion. Currently under internal refinement, this work is positioned as a foundational theoretical anchor for modeling persistent bias through system-level feedback. Developed as a central module within the Cognitive System Dynamics (CSD) framework, BIAs bring mid-layer granularity to structural cognition modeling.
Significance
Cognitive science has long documented individual biases, yet struggles to explain why some distortions intensify and persist while others fade. Bias Interaction Archetypes (BIAs) address this structural blind spot. Rather than catalog discrete heuristics, BIAs model recursive interactions between biases and indicates how they reinforce or modulate each other through feedback loops. This meso-level grammar bridges cognitive psychology and system dynamics, offering a new lens to understand belief rigidity, correction resistance, and systemic distortion.
Foundations
Rooted in Feedback Realism, BIAs advance a paradigm where distortions are not isolated deviations but dynamic feedback phenomena. This perspective aligns with the CSD framework’s layered approach to cognitive modeling. Instead of modeling cognition as bounded rationality or probabilistic inference alone, BIAs depict cognitive distortion as an evolving system state shaped by self-reinforcing loops and delayed correction. In this view, BIAs are not merely descriptive, but provide formal scaffolding to ground both feedback realism and the structural logic of belief entrenchment.
Architecture
BIAs formalize how two or more cognitive biases form structurally valid feedback loops, generating persistent cognitive distortions. Each archetype is defined by closed-loop interaction, directional influence, identifiable triggers, and observable distortion outcomes. As an architectural layer of the CSD framework, BIAs shift the ontological focus from individual flaws to system-level dynamics by treating belief persistence as an emergent property of recursive cognitive architecture. This mid-layer formalism expands the explanatory power of CSD by modeling how internal structures reinforce or neutralize distortion across contexts.
Modeling Bias in Complex Systems
Though foundational, the BIA framework is deeply applicable. From simulating echo chambers on social platforms to mapping feedback inertia in public policy, BIAs provide a modular and portable grammar for distortion modeling. Their composability enables diagnostic layering, intervention modeling, and feedback detection in real-world systems. Whether simulating epistemic collapse, modeling trust drift, or stress-testing correction mechanisms, BIAs inform both academic simulations and applied analytics in domains such as misinformation, governance, and cognitive resilience.