Thanks for your interest in STS 363 / WGSS 363 / AMST 363 / MATH 308, Mathematical and Computational Approaches to Social Justice.

Civil rights activist, educator, and investigative journalist Ida B. Wells said that “the way to right wrongs is to turn the light of truth upon them.” In this research-based tutorial, students will bring the vanguard of quantitative approaches to bear on issues of social justice. Each tutorial group will carry out a substantial project in an area such as criminal justice, education equity, environmental justice, health care equity, economic justice, or inclusion in arts/media. All students should expect to invest substantial effort in reading social justice literature and in acquiring new skills in data science.

This course satisfies the Quantitative/Formal Reasoning requirement (QFR), the Difference, Power, and Equity requirement (DPE), and, depending on which cross-listed version you register for, it provides either Division II or Division III credit.

Some key points for students:

• The course is entirely research based, so you need to have a fairly well-defined interest going into the start of the semester.
• Choices of topics will require coordination, since everyone who takes this course will be part of a group.
• Because I have space for 5 tutorial meetings per week, and because I want to enroll as many students as I can reasonably handle, I’ll prefer groups of 4. This would allow 20 students which is double the usual capacity of a tutorial. If you have a case for a group of 3 or 5 students, I’ll consider it.
• If you are interested in taking the course, please email me to request access to the Google spreadsheet with all interest students so you can begin networking, exploring possible topics, and forming groups.
• If you intend to take the course, every student in the group must preregister. Otherwise the group will not be eligible.
• By the time preregistration is over, please submit a research proposal from your group. One to two pages is more than adequate. I urge you to look at this proposal from a previous term to get a sense of what makes a strong proposal. I am very happy to give you feedback on a draft of the proposal to help you arrive at a strong final proposal.
• One of the most challenging logistical aspects of this course is simply coordinating group members’ busy schedules. In your proposal, based on your tentative course enrollment plans, please list at least two one-hour slots each week during 8 am – 4 pm work hours (e.g., Tuesdays 1:15 – 2:15 pm, Fridays 9:30 – 10:30 am) when your entire group will be free for the weekly tutorial meeting with me. If you can list more than two one-hour slots it is much appreciated (but not required).
• I don’t have any per-student prerequisites. I’ll look at the total experience of each research group and ask if that team is equipped, collectively, with the skills to get the job done. More specifically, each group should have: multivariable calculus (e.g., Math 150/151), linear algebra (e.g., Math 250), statistics (e.g., Stat 161/201/202), computer programming (e.g., Comp 134), some working knowledge of or strong interest in social justice issues.
• Because this is an entirely research-based class and because you’ll be working in groups if you take it, I am setting ambitious research goals. I think this class will be quite time consuming, but also rewarding and impactful.

Finally, a word on topic choice. The most important thing to me is that you work on a topic that engages you and that is appropriate for this class. There are many fascinating topics to choose from and anything is fine with me so long as it is social justice focused, has the potential for quantitative approaches, and can lead to a focused research question.

That said, I’m happy to suggest a few of my own research topics for those of you who might be looking around for something. Most of my work these days is related to criminal justice, including:

• Race-based criminal sentencing disparities in a state court system
• Reach of the Federalist Society
• Identification of judges in criminal sentencing
• Topological structure of criminal justice data
• Discretion in the criminal justice system
• Network structure of court systems