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Using Nlp To Model U.S. Supreme Court Cases, Katherine Lockard, Robert Slater, Brandon Sucrese
Using Nlp To Model U.S. Supreme Court Cases, Katherine Lockard, Robert Slater, Brandon Sucrese
SMU Data Science Review
The advantages of employing text analysis to uncover policy positions, generate legal predictions, and inform or evaluate reform practices are multifold. Given the far-reaching effects of legislation at all levels of society these insights and their continued improvement are impactful. This research explores the use of natural language processing (NLP) and machine learning to predictively model U.S. Supreme Court case outcomes based on textual case facts. The final model achieved an F1-score of .324 and an AUC of .68. This suggests that the model can distinguish between the two target classes; however, further research is needed before machine learning models …
The Lessons Of 1919, Lackland H. Bloom
The Lessons Of 1919, Lackland H. Bloom
SMU Law Review
One hundred years ago, the Supreme Court embarked on its first serious consideration of the First Amendment’s guarantee of freedom of speech. In 1919, the Court upheld four federal criminal convictions over First Amendment defenses. Three of the majority opinions were written by Justice Holmes. In the fourth, he offered a classic dissent. Two of the cases, Frohwerk v. United States and Debs v. United States, are of middling significance. The other two, Schenck v. United States and Abrams v. United States, are iconic. From these cases have sprung an expansive and complex jurisprudence of free speech. The …