The application of criteria from previous judgments in subsequent cases is unclear. One such factor, the degree of assault and intimidation, influences the severity of a crime but is challenging for the public to assess due to its unclear derivation. To address this, numerous studies aim to identify core elements that empirically prove abstract concepts. This study introduces a method for analyzing judgments, extracting elements for each issue based on shared patterns in reference precedents. Unlike previous approaches, it can analyze numerous rulings through extensive data processing. The method relies on judgment criteria and establishes classification criteria according to theory, leading to linear regression results. The model demonstrates that the importance of elements varies for each issue, providing insight into the rationale behind judgments. The public can utilize this model to enhance judgment predictability by analyzing precedents. Moreover, it can be employed to assess judgment reliability in both the Anglo-American and civil law systems that recognize case law.
Ključne riječi:
Humanities data analysis, linear regression, precedents, importance analysis, feature selectionSažetak
The application of criteria from previous judgments in subsequent cases is unclear. One such factor, the degree of assault and intimidation, influences the severity of a crime but is challenging for the public to assess due to its unclear derivation. To address this, numerous studies aim to identify core elements that empirically prove abstract concepts. This study introduces a method for analyzing judgments, extracting elements for each issue based on shared patterns in reference precedents. Unlike previous approaches, it can analyze numerous rulings through extensive data processing. The method relies on judgment criteria and establishes classification criteria according to theory, leading to linear regression results. The model demonstrates that the importance of elements varies for each issue, providing insight into the rationale behind judgments. The public can utilize this model to enhance judgment predictability by analyzing precedents. Moreover, it can be employed to assess judgment reliability in both the Anglo-American and civil law systems that recognize case law.
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