Statistical analysis of court documents based on the developed taxonomy

This presentation explores the earnings within the realization of the Legal Case Law Analytics and Modeling (LCAM) project, which applies AI technologies and statistical modeling to large-scale civil judicial data in Ukraine. It details the development, structural transformation, and empirical validation of a multi-level taxonomy designed to systematically classify hundreds of procedural document types across court instances. Additionally, it analyzes judicial patterns—such as procedural barriers, regional disparities, and term renewals—to lay the groundwork for predictive justice and evidence-based legal reforms. The presentation was delivered by Tetiana Ianevych from Taras Shevchenko National University of Kyiv at the Legal Case Analytics & Modeling (LCAM): Mathematics meets Law workshop, organized by Linnaeus University and Taras Shevchenko National University of Kyiv on 18–21 August 2026 within the LCAM: Legal Case Law Analytics & Modeling (2024–2026) project, funded by the Swedish Institute (SI).