Comparative Criminology

CRIM30641 Comparative Criminology 20 Semester 1 Undergraduate Level 3 David Buil Gil Unit coordinator Criminology 1 FHEQ level (Framework for Higher Education Qualifications) ' Last part of a Bachelors ' European Credit Transfer & Accumulation System Rating : 10.0 This unit aims to provide students with a comprehensive understanding of the conceptual and methodological principles of comparative research in criminology. As the module progresses, course materials will guide students through the complexities of handling diverse data sources for comparative data analysis, including police statistics, criminal justice data (e.g., prison, conviction and probation records), victimisation and social surveys, and self-report delinquency studies, covering both quantitative and qualitative data. Criminal justice data recorded across countries, including in Africa, America, Asia, Europe, and Oceania, will be accessed, critically assessed, and analysed. With a focus on both cross-national and temporal dimensions, the unit aims to foster the development of theoretical and methodological frameworks for explaining crime variations across countries and over time. The intended learning outcomes serve as pillars, guiding students to navigate challenges in cross-cultural and historical comparisons, critically evaluate datasets, and effectively communicate findings of comparative criminological studies. Ultimately, the unit aims to cultivate a global perspective, enabling students to contribute meaningfully to the discourse on crime and justice in an interconnected world through reflective practice and a nuanced understanding of the strengths and weaknesses inherent in existing data sources. Students should not think of this course as a ‘data module’ (we do not learn data analysis), but as a substantive module for which their skills in data analysis learnt in other modules serve as a foundational element. This unit is all about learning how crime and justice happens elsewhere in the world, and the kinds of implications this has for how we should best understand such matters here. Using substantive developments, including, the European Sourcebook on Crime and Criminal Justice Statistics, the UN Survey on Crime and Criminal Justice Trends, the International Crime Victims Survey, the unit seeks to problematize the ’nature’ of comparative work, its potential significance and challenges faced. The workshops illustrate how comparative work moves constantly between the descriptive and the theoretical (including the policy learning dimension). Case-studies, cultural-context approaches and cross-national research form the basis for this analytic account of comparative criminology. The module “Comparative Criminology” immerses students in a dynamic exploration of the conceptual, theoretical, and methodological foundations for understanding, conducting and interpreting criminological research across diverse geographical and temporal contexts. This ten-week module encompasses a multifaceted approach to understanding and comparing crime and justice issues across countries and over time. The foundational weeks (1-2) provide a robust initiation, covering the basics of comparative research, and cross-national criminological policies and crime prevention practices. Students then delve into the methodological intricacies of comparative research in criminology (Weeks 3-7), navigating the challenges of cross-national comparisons with police statistics, criminal justice data such as probation and prison statistics, cross-national victimisation and social surveys, and self-report delinquency studies. We will explore both quantitative and qualitative data sources. The aim of this course is to equip students with a comprehensive toolkit for sourcing, handling and using, and critically assessing data from various data sources in comparative criminology. As the module progresses, the temporal dimension is introduced (Week 8), exploring crime trends over time and the use of existing crime data sources to explore temporal changes in crime. Finally, week 9 explores the development and utility of criminological theoretical frameworks to explain crime variation across countries and over time. The concluding week (10) synthesises this knowledge into a final assignment, where students demonstrate their ability to integrate and apply the acquired skills and insights. The Intended Learning Outcomes serve as pillars, guiding students towards a holistic understanding of comparative criminology. Students will learn to navigate the complex challenges inherent in cross-cultural and historical comparisons, critically evaluating datasets, and effectively communicating the findings of comparative criminological research. Moreover, the emphasis on reflective practise ensures that students not only analyse data but also engage in thoughtful consideration of the strengths and weaknesses inherent in existing data sources. In essence, this module transcends traditional criminological studies by instilling in students a global perspective, enabling them to recognise, analyse, and contribute to the discourse on crime and justice in an increasingly interconnected world.   Knowledge  Recognise the conceptual, theoretical and methodological challenges related to conducting criminological comparisons across time and space Systematic understanding of available sources of data for comparative analysis of crime and justice issues Understand the way in which criminological data is recorded across countries and over time Intellectual skills  Critically evaluate comparative analyses of crime data across countries and over time Be able to make a reasoned argument about the strengths and weakness of available datasets for comparative criminological research Be able to critically assess the extent to which comparative analysis of crime data are affected by factors other than crime Practical  Be able to effectively communicate the results of comparative criminological analyses across countries Be able to effectively communicate the results of comparative criminological analyses over time Identify the most suitable source of data to undertake comparative analyses of criminological phenomena Transferable  Be able to gather and interpret social sciences data across countries and over time Be able to analyse, present and describe social sciences data across countries and over time Capacity to critically reflect on the strengths and weakness of existing data sources for comparative research   Compulsory Reading Materials Each week, students are expected to complete two compulsory readings before the 2-hour lecture. These readings will provide fundamental background information about the topics covered during the lecture session. 10x 2-hour Lectures The 2-hour lecture session will present key conceptual and methodological themes around comparative criminology. 10x 1-hour Computer Lab Workshops Each week, students will complete a set of activities in a computer lab environment. They will access and critically assess real-world comparative data. Students will be given a link to access a real-world dataset and presented with a challenge (e.g., Which four countries have higher rates of rape in Europe? What continent has a higher proportion of countries where the death penalty is legal? In which year did homicide rates peak globally?) and asked to critically reflect on their findings. Students will not be given specific instructions on how to analyse the data and will be allowed to use the software they want to work with (e.g., NVivo, R Studio, Microsoft Excel). The aim of this course is not to learn how to use a given software, but to learn the foundations of comparative research and know what sources of data are available and how to access and use them. Students will not be taught how to access this data in a given software – we assume that in year 3 students can use at least one software for data analysis. The first 35 minutes of the session will be for students to complete the task independently or in groups, while the last 15 minutes will be dedicated to a live data analysis demonstration.   0 Other 100% 100% Coursework (3000 words)Students choose one variable of interest in criminological research (e.g., a given crime type, fear of crime, prison population, confidence in policing, recidivism rates, drug use), find suitable dataset or datasets to explore this topic, analyse the data, and describe the results following the structure of a research article (i.e., Introduction, Literature Review, Data and Methods, Results, Discussion and Conclusions, References). Y Week 1 Jowell, R. (1998). How Comparative Is Comparative Research? American Behavioral Scientist, 42(2), 168-177. Bennett, R. (2004). Comparative criminology and criminal justice research: The state of our knowledge. Justice Quarterly, 21, 1-21.Week 2 Tonry, M. (2015). Is cross-national and comparative research on the criminal justice system useful? European Journal of Criminology, 12(4), 505-516. Lappi-Seppälä, T. (2008). Trust, Welfare, and Political Culture: Explaining Differences in National Penal Policies. Crime and Justice, 37, 313-387.Week 3 Rose, R., & Mackenzie, W. (1991). Comparing Forms of Comparative Analysis. Political Studies, 39(3), 446-462. Aebi, M., et al. (2021). European Sourcebook of Crime and Criminal Justice Statistics 2021 (6th ed.). Göttingen University Press.Week 4 Aebi, M. (2010). Methodological Issues in the Comparison of Police-Recorded Crime Rates. In S. G. Shoham, P. Knepper & M. Kett (Eds.), International Handbook of Criminology (pp. 211-227). Boca Raton: CRC. von Hofer, H. (2000). Crime Statistics as Constructs: The Case of Swedish Rape Statistics. European Journal on Criminal Policy and Research, 8, 77-89.Week 5 Aebi, M., et al. (2021). European Sourcebook of Crime and Criminal Justice Statistics 2021 (6 ed.). Göttingen University Press. Aebi, M., & Linde, A. (2012). Conviction Statistics as an Indicator of Crime Trends in Europe from 1990 to 2006. European Journal on Criminal Policy and Research, 18, 103-144.Week 6 Van Dijk, J., van Kesteren, J., & Smit, P. (2007). Criminal Victimisation in International Perspective: Key findings from the 2004-2005 ICVS and EU ICS. Boom Juridische uitgevers.  Buil-Gil, D., Trajtenberg, N., & Aebi, M. (2024). Measuring Cybercrime and Cyberdeviance in Surveys. In Routledge Handbook of Online Deviance. Routledge.Week 7 Junger-Tas, J. (2010). The Significance of the International Self-report Delinquency Study (ISRD). European Journal of Criminal Policy and Research, 16, 71–87. Enzmann, D., Marshall, I., Killias, M., Junger-Tas, J., Steketee, M., & Gruszczynska, B. (2010). Self-reported youth delinquency in Europe and beyond: First results of the Second International Self-Report Delinquency Study in the context of police and victimization data. European Journal of Criminology, 7(2), 159-183.Week 8 Rosenfeld, R. (2018). Studying crime trends: Normal science and exogenous shocks. Criminology, 56(1), 5-26. LaFree, G. (1999). Declining Violent Crime Rates in the 1990s: Predicting Crime Booms and Busts. Annual Review of Sociology, 25, 145-168.Week 9 Franko Aas, K. (2007). Analysing a world in motion: Global flows meet `criminology of the other’. Theoretical Criminology, 11(2), 283-303. Albanese, J. (2017). Crime Control Measures, Individual Liberties, and Crime Rates: An Assessment of 40 Countries. International Criminal Justice Review, 27, 5-18. Chamlin, M., & Cochran, J. (2006). Economic Inequality, Legitimacy, and Cross-National Homicide Rates. Homicide Studies, 10(4), 231-252. Chon, D. (2012). The Impact of Population Heterogeneity and Income Inequality on Homicide Rates: A Cross-National Assessment. International Journal of Offender Therapy and Comparative Criminology, 56(5), 730-748. Farrington, D. (2015). Cross-national comparative research on criminal careers, risk factors, crime and punishment. European Journal of Criminology, 12(4), 386-399. Nivette, A. (2011). Cross-National Predictors of Crime: A Meta-Analysis. Homicide Studies, 15(2), 103-131.Week 10 Adler, F. (1996). Our American Society of Criminology, the world, and the state of the art-The American Society of Criminology 1995 presidential address. Criminology, 34, 1–10. Buil-Gil, D., Bui, L., Trajtenberg, N., Diviak, T., Kim, E., & Solymosi, R. (2024). Diversifying crime datasets in introductory statistical courses in criminology. Lectures 20 Practical classes & workshops 10 0 70 At UG level, this course is restricted to final year students only. Teaching in workshops is delivered alongside M level students (with assessment criteria at appropriate level). Preferable to have taken either CRIM14441, CRIM20441, CRIM20452 or a suitable statistics course that covers either descriptive or inferential statistical analysis in Microsoft Excel or R/R Studio.  If in doubt, discuss with the course convenor before choosing this unit. Restricted to: BA (Criminology); LLB (Law with Criminology); and BA Social Sciences (BASS).