Teaching

This academic year Professor Geller will be teaching three courses in Winter Quarter 2023, and two courses in Spring 2023.

C106: Crime and Public Policy (Winter 2023)

This upper-level undergraduate course is designed to increase students’ understanding of how public policy is, and could be, used to respond to and influence crime rates. It aims to bring abstract concepts and theories from academic criminology to everyday life. At the conclusion of the course, you will be able to (1) understand and articulate the ways in which key institutions and public policies are used to understand and address crime conditions; (2) critically analyze contemporary issues and controversies around crime and the criminal legal system; (3) communicate key issues and research findings to policy actors, taking a variety of perspectives. Assignments are designed to enhance your reading, writing, teamwork, and communication skills to better prepare you for future study and your career. 

C216: Public Policy, Crime, and Justice (Winter 2023)

The Masters-level course is designed to increase student’s understanding of how public policy is, and could be, used to respond to crime and related social problems. Each lesson is centered on a specific question about crime or criminal justice that is either (1) necessary for developing a coherent, evidence-based, response to crime or (2) of particular policy relevance. Through posted lessons and forum discussions, students will learn how to use meaningful data to quantify the magnitude of a policy problem, suggest practical policy remedies, and identify ways to evaluate whether or not a policy remedy actually “works” in practice.  This course is taught online and asynchronously, and is limited to students studying toward the CLS Masters of Advanced Study.

SE264B: Data Analysis (Winter 2023)

This doctoral-level course is designed to introduce the use of multiple regression for examining real-world problems in social science fields such as criminology, criminal justice, policy, and planning. These models have various usages: one approach uses them to form predictions of a particular outcome variable. Another approach uses them to estimate the relationship between one variable and the outcome variable while taking into account other variables that might otherwise confound this relationship. The course will be focused on understanding these models from an applied researcher standpoint. We will focus on learning the assumptions of these models, and some techniques to minimize the possibility of improper usage of these models. We will use the Stata software program for these analyses. Lab/homework assignments are based upon material presented in lecture and require use of the computer to generate output using statistical software.

C139: Police and Change (Spring 2023)

This upper-level undergraduate course familiarizes students with the history of and contemporary issues in the institution and practices of American policing. Students are introduced to the historical evolution of policing, and the philosophies and key events underpinning the changes of policing practices over time, and how they inform policing practices and institutions in the present day. They are introduced to an array of challenges facing contemporary police departments and the communities they serve. Finally, we discuss new opportunities for the policing profession. After taking this course, students have a broader, deeper, and balanced understanding of American policing, and are equipped with the reading, writing, and critical thinking skills that are important for the consumption and production of scientific knowledge in the field of criminology, law, and society.

C203B: Quantitative Practicum (Spring 2023)

This advanced methods capstone course provides doctoral students with hands-on experience using existing data to estimate the impact of policy and law on individual behavior or aggregate social outcomes. The course covers basic principles of data manipulation and description, as well as statistical strategies used to identify causal effects in the absence of an experiment. Particular emphasis is placed on understanding the strengths and limitations of different analytical approaches, what assumptions are necessary for credible inference in different analytical approaches, and how one might provide evidence that these assumptions are satisfied.