Methodological Specification for the Mimicry Index (MI-1.0): Quantifying Expressive Distortion in Algorithmic Habitats
Year: 2026
Type: article
Abstract: 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:
Author: Pierce, J. Matthew
Institution: Ottawa University
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7154740544
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