Professor Gregory Duhl, Adjunct Professors Tara Jenson and Lisa Needham, and Instructional Designers Anthony Varela and Amanda Soderlind invite students to express interest in participating in a three-credit data analytics incubator in spring 2022. Students who are interested in this opportunity should email Professor Duhl at gregory.duhl@mitchellhamline.edu and explain why they are interested and what access-to-justice gap they might want to address. A more detailed description follows:
In this incubator, students will learn data literacy, management, and analysis skills to help pursue access to justice aims.
For base statistical sets, students will begin by using both 2020 Census Data (to understand demographic makeup) and Bureau of Labor Statistics data (to understand the availability of legal services). Students will begin by determining where in the country, and in what types of cases, individuals remain underserved by lawyers.
Ideally, students will be able to focus on issues near where they live, but that will be dependent on the availability of court caseload data in their state. The Court Statistics Data project maintains detailed information about state court caseloads in all 50 states, but not all states provide direct access to that data in a way that can be easily manipulated. After making that determination, students will be asked to make specific policy proposals to help close that gap.
In applying to the course, students should detail an access to justice problem within their city, county, or state that they believe could be addressed with data analysis. An example of a problem a student might wish to address is to determine what proportion of individuals are self-represented litigants in a given type of high-conflict court case and how legal services might be configured in an innovative fashion to ensure better availability of representation.
Students should be familiar with Excel enough to perform basic organizing and calculation within the program, but need not have any background in data analysis or coding.