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Unravelling the Rule of Law: A Machine Learning Approach

Jaroslaw Kantorowicz
Bastián González-Bustamante

There are ongoing debates about what the rule of law is and was historically. Legal-philosophical scholars present strikingly different conclusions regarding, among others, the origins and causes of the rule of law, the evolution of its meaning and the most influential thinkers contributing to concept building. One such example of the differences of opinion concerns the thin and thick conceptualisations of the rule of law. In other words, to what extent should the rule of law exclusively refer to the quality of the legal system (thin conceptualisation) and to what extent should it also include human rights and other adjacent concepts (thick conceptualisation)? Relatedly, there is an ongoing and tense discussion revolving around the virtues of the rule of law, ranging from offering predictability to tempering arbitrary power.

Different approach

While acknowledging prominent legal-philosophical debates, this project proposes a radically different approach to provide insights into the concept of the rule of law. It employs cutting-edge automated text analysis methods from computer science and information retrieval fields to trace the changing meaning of the rule of law and the prevalence of the associated ideals (virtues) of the rule of law. Moreover, the project provides a tool for detecting and understanding the meaning of the rule of law by different audiences (cross-national differences) and evaluating the importance of various constitutive parts of the rule of law.

In a nutshell, this project applies novel machine learning techniques to:

  • Demonstrate how the meaning of the rule of law has changed over time;
  • Whether the understanding of the rule of law concept differs across jurisdictions;
  • Provide a novel way for creating the rule of law indicators.

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