Since the earliest geographical explorations of criminal phenomena, scientists have come to the realization that crime occurrences can often be best explained by analysis at local scales. For example, the works of Guerry and Quetelet—which are often credited as being the first spatial studies of crime—analyzed data that had been aggregated to regions approximately similar to US states. The next major seminal work on spatial crime patterns was from the Chicago School in the 20th century and increased the spatial resolution of analysis to the census tract (an American administrative area that is designed to contain approximately 4,000 individual inhabitants). With the availability of higher-quality spatial data, as well as improvements in the computing infrastructure (particularly with respect to spatial analysis and mapping), more recent empirical spatial criminology work can operate at even higher resolutions; the “crime at places” literature regularly highlights the importance of analyzing crime at the street segment or at even finer scales. These empirical realizations—that crime patterns vary substantially at micro places—are well grounded in the core environmental criminology theories of routine activity theory, the geometric theory of crime, and the rational choice perspective. Each theory focuses on the individual-level nature of crime, the behavior and motivations of individual people, and the importance of the immediate surroundings. For example, routine activities theory stipulates that a crime is possible when an offender and a potential victim meet at the same time and place in the absence of a capable guardian. The geometric theory of crime suggests that individuals build up an awareness of their surroundings as they undertake their routine activities, and it is where these areas overlap with crime opportunities that crimes are most likely to occur. Finally, the rational choice perspective suggests that the decision to commit a crime is partially a cost-benefit analysis of the risks and rewards. To properly understand or model these three decisions it is important to capture the motivations, awareness, rationality, immediate surroundings, etc., of the individual and include a highly disaggregate representation of space (i.e. “micro-places”). Unfortunately one of the most common methods for modeling crime, regression, is somewhat poorly suited capturing these dynamics. As with most traditional modeling approaches, regression models represent the underlying system through mathematical aggregations. The resulting models are therefore well suited to systems that behave in a linear fashion (e.g., where a change in model input leads to a predictable change in the model output) and where low-level heterogeneity is not important (i.e., we can assume that everyone in a particular group of people will behave in the same way). However, as alluded to earlier, the crime system does not necessarily meet these assumptions. To really understand the dynamics of crime patterns, and to be able to properly represent the underlying theories, it is necessary to represent the behavior of the individual system components (i.e. people) directly. For this reason, many scientists from a variety of different disciplines are turning to individual-level modeling techniques such as agent-based modeling.
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Article
Place-Based Simulation Modeling: Agent-Based Modeling and Virtual Environments
Nick Malleson, Alison Heppenstall, and Andrew Crooks
Article
Prevalence of Gangs in the U.S.: Measurement Approaches and Findings From Police Data
Arlen Egley, Jr.
Street gang activity has garnered academic and public attention for many decades. Compared with other youth groups, street gangs contribute disproportionately to crime and violence, though the vast majority of crime and violence in the United States is unrelated to gang activity. A distinctive aspect in the study of gangs is the multiple dimensions in which gangs are situated. Depending on the research interest, gang activity may be construed as an independent variable (as a cause) or a dependent variable (as an effect). Moreover, gang activity simultaneously represents multiple levels of analysis: the individual level (gang member), the group level (gang), and the macro level (neighborhoods and broader geographical places in which gangs form and transform). These multiple dimensions present a wide variety of research streams in which to study gangs. Where and why gang activity emerges, when and why individuals join and leave gangs, the wide-ranging diversity in gang structure and organization are but a few of the many areas gang scholars have focused on in order to describe and explain gangs and gang members. Some research areas, such as the association between gang membership and criminal offending and the risk factors for gang joining, have been researched quite extensively. Other areas, such as the nature and extent of gang migration outside larger cities and desistance processes from the gang, have not received or have only recently begun to receive intensive and consistent scholarly attention. Definitional matters are also paramount and inextricably linked to understanding gang activity. How should we define “street gangs,” how should “gang membership” be defined and determined, when and how should a crime be designated as “gang related”? These definitional issues have sparked considerable and sometimes heated debates, and consensus remains elusive. It is important to be mindful of these various dimensions, streams, and issues as we continue our efforts to describe and document street gangs and enhance our understanding of gang processes. Successful strategies for the response to and reduction of street gang activity are contingent on them.
Article
Qualitative Interviewing
John J. Brent, Peter B. Kraska, and Justin Hutchens
Given the multifaceted and interdisciplinary nature of studying crime and criminal justice, the pursuit of credible, reliable, and rigorous knowledge requires a well-developed methodological infrastructure. To explore and examine these areas, there are times when research needs to document probabilities, examine rates, identify correlations, and test theoretical propositions. There are also times when research needs to explore the more qualitative elements, namely the perspectives, interpretations, lived experiences, and constructed realities. Among the more prominent qualitative methods within the field’s methodological toolbox are interviews. Aiding other approaches, qualitative interviews contribute to the field’s methodological means by first offering a more inductive and interpretive framework to study crime-related phenomena. From these foundations, they are replete with avenues through which to conceptualize, construct, and administer research efforts. They also provide a host of unique and beneficial methodological means to collect, code, and analyze collected data. When their overall impact is examined, the continued use and development of qualitative methods—more specifically, interviews—can progress the field’s body of knowledge while contributing to more informed practices and policies. Given their use and utility, interviews have become some of the most used methodological approaches within the social sciences.
Article
Qualitative Methods in International and Comparative Criminology
Max Travers
Although the field of international criminology has mostly employed quantitative methods to test universal theories, there is a growing recognition of the potential value of qualitative methods in understanding crime and criminal justice in a globalizing world. The difficulties in developing this field are partly practical and financial. It is difficult visiting different countries and overcoming language barriers. But there are also conceptual challenges. Criminology generally is only just starting to understand and engage with the distinction between quantitative and qualitative research methods and to discover the wide range of qualitative methods employed in interdisciplinary fields, such as education, health, environmental, media, and management studies, and to recognize that theories are important in this field.
Article
The Quantitative Study of Terrorist Events: Challenges and Opportunities
Jonathan Grossman and Ami Pedahzur
Since 2001, unprecedented resources have been invested in research into global terrorism, resulting in a dramatic rise in the number of academic publications on the topic. Works by scholars from predominantly quantitative disciplines predominate in this literature, and the unfolding development of data science and big data research has accentuated the trend. Many researchers in global terrorism created event databases, in which every row represents a distinct terrorist attack and every column a variable (e.g., the date and location of the attack, the number of casualties, etc.). Such event data are usually extracted from news sources and undergo a process of coding—the translation of unstructured text into numerical or categorical values. Some researchers collect and code their data manually; others use an automated script, or combine the efforts of humans and software. Other researchers who use event data do not collect and process their data at all; rather, they analyze other scholars’ databases. Academics and practitioners have relied on such databases for the cross-regional study of terrorism, analyzing their data statistically in an attempt to identify trends, build theories, predict future incidents, and formulate policies.
Unfortunately, event data on terrorism often suffer from substantial issues of accuracy and reproducibility. A comparison between the data on suicide terrorism in Israel and the occupied Palestinian territories in two of the most prominent databases in the field and an independent database of confirmed events reveals the magnitude of these problems. Among the most common pitfalls for event data are replication problems (the sources that the databases cite, if there are any at all, cannot be retrieved), selection bias (events that should have been included in the database are not in it), description bias (the details of events in the database are incorrect), and coding problems (for example, duplicate events). Some of these problems originate in the press sources that are used to create the databases, usually English-language newspaper articles, and others are attributable to deficient data-gathering and/or coding practices on the part of database creators and coders. In many cases, these researchers do not understand the local contexts, languages, histories, and cultures of the regions they study. Further, many coders are not trained in qualitative methods and are thus incapable of critically reading and accurately coding their unstructured sources. Overcoming these challenges will require a change of attitude: truly accurate and impactful cross-regional data on terrorism can only be achieved through collaboration across projects, disciplines, and fields of expertise. The creators of event databases are encouraged to adopt the high standards of transparency, replicability, data-sharing, and version control that are prevalent in the STEM sciences and among software developers. More than anything, they need to acknowledge that without good and rigorous qualitative work during the stage of data collection, there can be no good quantitative work during the stage of data analysis.
Article
Sampling from Online Panels
Luzi Shi and Sean Patrick Roche
Since the 2010s, online surveys have become a popular method among criminologists. Often these surveys are conducted with the assistance of private survey research companies, which gather large groups of people (i.e., respondents) who have indicated a willingness to share their opinions on a variety of issues. These panels of potential respondents vary in size and quality. Researchers planning to collect survey data via these online panels must also consider probability versus non-probability sampling methods. Probability samples provide stronger assurances that sample statistics—particularly, univariate point estimates—are generalizable to broader populations (e.g., adult Americans). They are also often very expensive, although this is somewhat dependent on the size and complexity of the proposed project. Two popular providers of probability samples of the American public are the Ipsos Knowledge Panel and the AmeriSpeak Omnibus panel. In criminology and criminal justice, researchers have used online probability panels to study a variety of topics, including behaviors regarding firearms, attitudes toward policing, and experiences of violence.
Non-probability samples present a budget-friendly alternative but may be less generalizable to populations of interest. Since 2010, these samples have become especially popular in the criminological literature and are much more commonly used than online probability samples. Findings from non-probability online surveys often yield remarkably similar relational inferences (e.g., correlations) to those obtained from probability samples. However, non-probability samples are generally unsuitable for providing generalizable univariate point estimates. Some of the leading providers of non-probability samples from panels are YouGov, Qualtrics, and Lucid. As of 2024, YouGov uses a matched opt-in sample with a more sophisticated sampling design, while Qualtrics and Lucid provide quota samples. Researchers may also directly recruit non-probability samples of respondents via crowdsourcing platforms, such as Amazon Mechanical Turk, or services that incorporate those platforms into their own business model, such as CloudResearch. Research suggests that platforms with more sophisticated sampling procedures tend to yield more accurate results. Consequently, matched opt-in samples such as YouGov are approximately twice as expensive as Qualtrics samples and are many times more expensive than crowdsourcing platforms. Finally, it should be noted that the demographic composition of online samples, even those that have been simply crowdsourced, tend to be more diverse than typical in-person non-probability samples used in criminology and criminal justice research (e.g., college students).
Article
Social Network Analysis: People and Places
Scott Duxbury
Network analysis is increasingly applied throughout the social sciences. Networks have been at the core of criminological thinking since its inception. As early as Sutherland and Shaw and McKay, networks have been regarded as important causes of delinquent behavior. Networks, by definition, reflect patterns of relationships between observations. Observations are typically human actors, but can represent any criminologically relevant entity, such as gangs, grocery stores, or street corners. Networks can even represent connections between actors that occupy distinct roles (e.g., connections between people and places). This flexibility in how networks can be defined and analyzed presents innumerable promising opportunities in the analysis of crime. Networks can influence criminal behavior by influencing selection into delinquent peer networks and by transmitting delinquent values and behaviors. While some of the earliest adopters of network methods turned to analyses of peer group context and delinquency, more recent applications examine the generative forces driving criminal organization dynamics, gang violence, and even social order among prison inmates. Some other visionary research examines how networks in physical space affect the distribution of crime, and some studies now suggest that networks act as an important mechanism linking formal sanctioning to recidivism. This body of recent evidence stands in contrast to general theories of crime, which argue that networks have little causal influence on criminal behavior. In contrast, selection into delinquent peer networks amplifies criminal behavior through both learning and opportunity.
Article
Social Networks in Gangs
Christian L. Bolden and Reneé Lamphere
Social networks in gangs refers to both a theoretical and methodological framework. Research within this perspective challenges the idea of gangs as organized hierarchies, suggesting instead that gangs are semi-structured or loosely knit networks and that actions are more accurately related to network subgroupings than to gangs as a whole. The situated location of individuals within a network creates social capital and the fluidity for members to move beyond the boundaries of the group, cooperating and positively interacting with members of rival gangs. Before the millennium, the use of social network analysis as a method to study gangs was rare, but it has since increased in popularity, becoming a regular part of the gang research canon. Gang networks can be studied at the group level and the individual level and can be used for intervention strategies. The concept of gangs as social networks is sometimes confused with social networking sites or social media, which encompasses its own rich and evolving array of gang research. Gang members use social networking sites for instrumental, expressive, and consumer purposes. While the use of network media allows for gang cultural dissemination, it simultaneously allows law enforcement to track gang activity.
Article
Structural Equation Modeling
John Wooldredge
Structural Equation Modeling (SEM) is a powerful quantitative tool for theory testing with the ability to generate latent variables that more closely approximate theoretical constructs and parsing out the causal effects (both direct and indirect) versus spurious relationships between them. The roots of SEM date back to the early 20th century, with the developments of Factor Analysis and Path Analysis, but it was not until the second half of the 20th century that CFA developed, and not until the late 20th century that these methods were extended to analyses of both continuous and categorical independent and dependent variables. Data requirements are more demanding for SEM applications relative to single-equation models with observed variables, and users must understand the limitations of both their data and conceptual model (the latter related to model “identification”). SEM applications in criminology have expanded considerably during the 21st century, although its use remains rare compared to other fields. A substantive understanding of the topic is critical for proper model building and model refinement in SEM, and the ability to assess both global fit (for the entire model) and local fit (for specific parameter estimates) is essential for a full evaluation of multi-equation systems. Aside from the more general applications of SEM, it provides one of the most useful methods for studying individual change over time through Latent Growth Curves. SEM is a rigorous method for both theory testing and policy evaluation.
Article
Using Cognitive Interviews to Guide Questionnaire Construction for Cross-National Crime Surveys
Stephen Farrall
What is a “snowball”? For some, a snowball is a drink made of advocaat and lemonade; for others, a mix of heroin and cocaine injected; for yet others, a handful of packed snow commonly thrown at objects or people; for gamblers, it refers to a cash prize that accumulates over successive games; for social scientists, it is a form of sampling. There are other uses for the term in the stock market and further historical usages that refer to stealing things from washing lines or that are racist. Clearly then, different people in different contexts and different times will have used the term “snowball” to refer to various activities or processes. Problems like this—whereby a particular word or phrase may have various meanings or may be interpreted variously—are just one of the issues for which cognitive interviews can offer insights (and possible solutions).
Cognitive interviews can also help researchers designing surveys to identify problems with mistranslation of words, or near-translations that do not quite convey the intended meaning. They are also useful for ensuring that terms are understood in the same way by all sections of society, and that they can be used to assess the degree to which organizational structures are similar in different countries (not all jurisdictions have traffic police, for example). They can also assess conceptual equivalence. Among the issues explored here are the following:
• What cognitive interviews are
• The background to their development
• Why they might be used in cross-national crime and victimization surveys
• Some of the challenges associated with cross-national surveys
• Ways cognitive interviews can help with these challenges
• Different approaches to cognitive interviewing (and the advantages of each)
• How to undertake cognitive interviews
• A “real-world” example of a cognitive interviewing exercise
• Whether different probing styles make any difference to the quality of the data derived.
Article
Using Naturalistic Observation to Develop Crime-Control Policies in Nighttime Entertainment Districts
Monica Perez-Trujillo
For the last 20 years, research based on the idea that opportunities for crime are related to specific times and places has informed crime-control policies in nighttime entertainment districts. In order to examine crime in these areas, many studies have relied on large data sets that associate city- and neighborhood-level factors with crime and delinquency. These studies have helped us understand the importance of environmental and situational factors, as well as the impact of changes in legislation and regulations to control alcohol availability (e.g., reducing the density of alcohol outlets and trading hours) and the implementation of interventions in licensed premises to reduce intoxication and disorder. However, when informing crime-control policies, the use of alternative methods to examine entertainment districts, such as naturalistic observations, can be vital. Because nighttime entertainment districts are extremely complex environments, observation is useful to examine and identify situational factors and local dynamics that increase or decrease the opportunities for crime in specific places. Observational methods can be particularly useful to understand the context in which criminal behavior and aggressive incidents occur, the interplay of situational risk factors specific to a public drinking environment, and the social and cultural factors (e.g., the relationship between police, staff, and customers) that can facilitate or challenge the implementation of crime-control strategies in these multifaceted contexts.
Naturalistic observation is a data-collection method that involves accessing the field to systematically record and describe features of the space, people’s characteristics and patterns of movement, individual behaviors, and exchanges between actors in natural settings. It can be used in both quantitative and qualitative designs, although in different ways. In entertainment districts, researchers have used this method to understand crimes that are underreported and underregistered, such as sexual harassment, and to study patrons’ behaviors in licensed premises and surrounding streets, as well as staff management practices and control strategies. While they have some limitations, such as the fact that information is filtered by what observers see and how they interpret events, observation methods can uniquely contribute to the development of crime-control policies in entertainment districts by focusing on specific situational and cultural factors relating to violence and crime at a local level, as well as suggesting differentiated responses to the types of incidents that take place in these settings.
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