Crime Science

INTRODUCTION TO CRIME SCIENCE
FALL QUARTER 2023-24
ONLINE

Department of Criminology and Justice Studies
PROFESSOR CONTACT INFORMATION
Office hours: by appointment – in person, phone or other agreed upon method

COURSE DESCRIPTION
Crime science is the application of scientific methods and knowledge from many disciplines to the development of practical and ethical ways to reduce crime and increase security (Wortley, et al, 2018).

This course will interrogate this definition as we examine the social as well as the political dimensions of science as it relates to crime and the pursuit of justice in society. To do so we will examine topics such as predictive policing, data justice, and the use of machine learning technology in criminal justice.

Students will learn about the many practices that make up “crime science” as well as how science, technology and society interact in this area.

LEARNING OBJECTIVES
After completion of this course, the student should:

• Possess a clear understanding of the practices of crime science.
• Address the ethical and political implications of crime science.
• Understand how the police and other criminal justice entities use empirical practices to address crime.
• Know the basic legal issues about technology use in criminal justice, including relevant case law and the regulatory context of civil rights, crime prevention, and security.
• Have gained a working knowledge of the technology tools and applications currently used in crime science.

PLACE IN THE PROGRAM
This is the foundational, and required, course for undergraduate students who select the Crime Science and Analysis degree concentration. Students will take this course at the start of their CSA curriculum. The course will also serve as a program elective for students who select the Justice Studies and Criminal Justice concentrations.

REQUIRED TEXTBOOK
All reading will be available through Blackboard.

CITATIONS
We will be using APA style in this class. There are many citation guides available online and one of my favorites is OWL from Purdue University:

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