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House of Mirrors: Monotone Nonlinear Transformations for Modeling and Quantifying Perceptual Distortion in Data-Driven and Psychometric Systems

2025-12-16

Abstract excerpt

This work presents a unified mathematical framework for understanding how monotone nonlinear transformations reshape data and generate structural forms of distortion, even when order is preserved. We model perception and algorithmic processing as the action of a monotone mapping h(x) applied to an underlying truth variable, showing that curvature alone can alter scale, emphasis, and information content. Using synt...

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Literature Corpus work
2a347a3f-6f28-5ccf-9863-c99b177922f0
DOI
10.20944/preprints202512.1283.v1
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House of Mirrors: Monotone Nonlinear Transformations for Modeling and Quantifying Perceptual Distortion in Data-Driven and Psychometric SystemsDOI 10.20944/preprints202512.1283.v1
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