Teaching Data Science for Lawyers with Caselaw Access Project Data

In the Spring of 2019, at the University of Iowa, I taught an experimental course called Introduction to Quantitative & Computational Legal Reasoning. The idea of the class was beginning “data science” in the legal context. The course is taught in Python, and focuses on introductory coding and statistics, with focused applications in the law (such as statistical evidence of discrimination).

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The Caselaw Access Project Research Summit

Since launching the CAP API and Bulk Data Service in Fall 2018, we’ve been developing a research community around the Caselaw Access Project dataset.

Last week we hosted the first Caselaw Access Project Research Summit to bring together researchers from this community who had already made progress exploring data made available by the Caselaw Access Project.

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Colors in Caselaw

The prospect of having the Caselaw Access Project dataset become public for the first time brings with it the obvious (and wholly necessary) ideas for data parsing: our dataset is vast and the metadata structured (read about the process to get to this), but the work of parsing the dataset is far from over. For instance, there’s a lot of work to be done in parsing individual parties in CAP (like names of judges), we don’t yet have a citator, and we still don’t know who wins a case and who loses. And for that matter, we don’t really know what “winning” and “losing” even means (if you are interested in working on any of these problems and more, start here: https://case.law/tools/).

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