Please use this identifier to cite or link to this item: https://zone.biblio.laurentian.ca/handle/10219/4107
Title: Outcome-based judgement categorization of the Supreme Court of Canada
Authors: Malley, Thomas
Keywords: Natural language processing;Canadian law;court case categorization;Supreme court of Canada;precedence
Issue Date: 12-Sep-2022
Abstract: Outcome-based judgement categorization of the Supreme Court of Canada (SCC) focuses on the multidisciplinary field of computational law. Regarding court hierarchy, the SCC is the highest court in Canada. Decisions from this court generally bind any lower court. Since court decisions are in a textual format, it is possible to correctly categorize outcomes of the SCC utilizing Natural Language Processing (NLP) techniques. The experiment contained shows algorithmic categorization performance F1 greater than 60. This result is significant given the binary nature of case outcomes (allow, dismiss) that an individual unfamiliar with the law should be able to guess 50% of the time correctly. This work is a preliminary study of future work to indicate the possibility of outcome forecasting in the judicial branch of the government.
URI: https://zone.biblio.laurentian.ca/handle/10219/4107
Appears in Collections:Computational Sciences - Master's theses

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