Methodological Specification for the Mimicry Index (MI-1.0): Quantifying Expressive Distortion in Algorithmic Habitats

This methodological specification introduces the Mimicry Index (MI-1.0), a longitudinal framework designed to quantify "Expressive Distortion" within digitally governed environments. While traditional platform metrics (views, engagement) prioritize system performance, the MI-1.0 focuses on the psychological impact of algorithmic governance: the systematic convergence of individual behavior toward platform-favored norms. Grounded in the Expressive Space Framework and Self-Determination Theory (SDT), the model operationalizes the "autonomy-in-relatedness paradox" (Kluwer et al., 2020). The index utilizes a multi-dimensional protocol to calculate the statistical distance between a creator’s unique historical baseline and their post-catalyst output across four pillars: