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Stratified Normative Design for the Integration of Behavioral EvidenceWithin Digital Market Regulation
Abstract
Competition law has traditionally relied on full rationality, whose descriptive validity has been challenged by behavioral economics, creating tension between empirical realism and institutional stability. This article examines the conceptual viability of a stratified normative architecture to integrate behavioral evidence in digital markets. The findings advance a two-level model, a presumption of rationality and a behavioral modulator, incorporating cognitive biases through graduated evidentiary thresholds and explaining defaults, dark patterns, and algorithmic collusion, while identifying institutional limits. The analysis suggests that this approach reconciles legal coherence with behavioral realism.
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