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CRIM 1100-401 |
Criminal Justice |
Sultan Altikriti |
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MW 1:45 PM-3:14 PM |
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This course examines how the criminal justice system responds to crime in society. The course reviews the historical development of criminal justice agencies in the United States and Europe and the available scientific evidence on the effect these agencies have on controlling crime. The course places an emphasis on the functional creation of criminal justice agencies and the discretionary role decision makers in these agencies have in deciding how to enforce criminal laws and whom to punish. Evidence on how society measures crime and the role that each major criminal justice agency plays in controlling crime is examined from the perspective of crime victims, police, prosecutors, jurors, judges, prison officials, probation officers and parole board members. Using the model of social policy evaluation, the course asks students to consider how the results of criminal justice could be more effectively delivered to reduce the social and economic costs of crime. |
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SOCI2921401 |
Society sector (all classes) |
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CRIM 2005-001 |
Violent Crime |
Sultan Altikriti |
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MW 3:30 PM-4:59 PM |
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This course examines the definitions, patterns, and impacts of violent crime and the attendant causes and policy responses. Students will critically assess a range of theories that explore the sociological, psychological, and developmental precursors to violent offending. The topics covered in this course include generality and specificity in offending, homicide, gun violence, group violence, and intimate partner violence. Understanding the historic and contemporary research on violence is a central component of this course and this research is used to guide discussion and assessment of societal responses to violent crime policy. This course is intended to foster a nuanced understanding of violent crime and complexities of its policy implications. |
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CRIM 2020-001 |
Criminal Justice Reform: A Systems Approach (SNF Paideia Program Course) |
John F Hollway |
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R 3:30 PM-6:29 PM |
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America's criminal justice system, which affects every community in the United States, is often criticized for being biased, overly punitive, ineffective at reducing crime, and resistant to change. This course will review the various components of the criminal justice system, identify the structural challenges to the widespread implementation of reforms or improvements to the system, and provide students with a conceptual framework for dialogue and structural/cultural change that can improve the legitimacy and effectiveness of our criminal justice agencies and enhance the delivery of justice for all. |
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CRIM 3250-401 |
Methods of Investigation: Global Quantitative Data |
Leticia Marteleto |
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CANCELED |
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In a time of abundant fake news and mis-information, it becomes ever important for students (for all, really!) to learn how to critically assess (and produce) robust empirical evidence to uncover patterns and trends about social life. The goal of this course is to do just that through the use of census microdata, video and photographs, with a focus on social inequality! Or, in other words…a first goal of this course is to introduce students to empirical work that will let them identify robust evidence on social inequality across a diverse set of topics and countries. A second goal of the course is to provide students with key analytical skills through working with microdata to uncover social inequality globally. Having exposure and hands-on experience with the correct tools to read (and produce) evidence on patterns and trends on social research is an important skill for students in any major. We will use publicly available census microdata on more than 100 countries from IPUMS and photographs from the Dollar Street Project. Students will work with a country, produce their own analysis and combine it with photographs and videos. As a Signature Course, a third key goal of the course is to teach students skills that will enable them to more easily read empirical work and write results more clearly and concisely. Students will practice reading academic research, do class exercises, write case studies, and complete a research paper/video/photo essay that will aid them in these goals. |
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CRIM 4012-401 |
Machine Learning for Social Science |
Greg Ridgeway |
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MW 10:15 AM-11:44 AM |
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This course provides an introduction to machine learning techniques for social science researchers. The course will cover a range of techniques including supervised and unsupervised learning, as well as more specialized methods such as deep learning and natural language processing. The course will also discuss ethical and privacy considerations in the use of machine learning, as well as the role of machine learning in policy and decision-making.
The aim of the course is to be focused on applications. While the class will present the formal background on the development of the machine learning methods, the class will focus on putting the tools into practice. We will use data on a variety of topics including criminal justice data (recidivism prediction) as well as other social science disciplines. Students completing the course will know how to apply several of the most common machine learning tools to a variety of social science problems including prediction and clustering. The course will also discuss the role of machine learning in causal inference. |
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CRIM6012401, SOCI3501401, SOCI6012401 |
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https://coursesintouch.apps.upenn.edu/cpr/jsp/fast.do?webService=syll&t=202410&c=CRIM4012401 |
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CRIM 6001-301 |
Pro-Seminar in Criminal Justice |
Anthony Braga |
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R 1:45 PM-4:44 PM |
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This course provides and overview of what we know about the criminal justice system in the United States and other developed nations. The central purpose of the course is to increas your knowledge about how the U.S. criminal justice system works but we will also spend a great deal of time thinking about the quality of the available evidence and how we know what we know. Topics covered will vary from year to year; recent topics have included police use of force, capital punishment, pre-trial detention, the use of predictive algorithms in the criminal justice system and the relationship between immigration and crime in the United States. |
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CRIM 6003-301 |
Research Methods/Crime Analysis |
John M Macdonald |
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T 10:15 AM-1:14 PM |
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This course provides an overview of the application of social science research methods and data analysis to criminology. Students will learn research design principles and statistical techniques for the analysis of social science data, including how to interpret results as part of the rigorous practice of evidence-based criminology. M.S. students will conduct a semester-long, data-intensive crime analysis project using quantitative methods to address a specific research question. Student projects culminate with a poster presentation, an oral defense, and the submission of a written research paper. |
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CRIM 6012-401 |
Machine Learning for Social Science |
Greg Ridgeway |
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MW 10:15 AM-11:44 AM |
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This course provides an introduction to machine learning techniques for social science researchers. The course will cover a range of techniques including supervised and unsupervised learning, as well as more specialized methods such as deep learning and natural language processing. The course will also discuss ethical and privacy considerations in the use of machine learning, as well as the role of machine learning in policy and decision-making.
The aim of the course is to be focused on applications. While the class will present the formal background on the development of the machine learning methods, the class will focus on putting the tools into practice. We will use data on a variety of topics including criminal justice data (recidivism prediction) as well as other social science disciplines. Students completing the course will know how to apply several of the most common machine learning tools to a variety of social science problems including prediction and clustering. The course will also discuss the role of machine learning in causal inference. |
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CRIM4012401, SOCI3501401, SOCI6012401 |
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https://coursesintouch.apps.upenn.edu/cpr/jsp/fast.do?webService=syll&t=202410&c=CRIM6012401 |
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