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Big Data and the Study of Communities and Crime  

Daniel T. O'Brien

In recent years, a variety of novel digital data sources, colloquially referred to as “big data,” have taken the popular imagination by storm. These data sources include, but are not limited to, digitized administrative records, activity on and contents of social media and internet platforms, and readings from sensors that track physical and environmental conditions. Some have argued that such data sets have the potential to transform our understanding of human behavior and society, constituting a meta-field known as computational social science. Criminology and criminal justice are no exception to this excitement. Although researchers in these areas have long used administrative records, in recent years they have increasingly looked to the most recent versions of these data, as well as other novel resources, to pursue new questions and tools.


Calculating Crime Rates  

Rémi Boivin

Dividing the number of crimes in an area at a given time by the population of the same area at the same time has become the standard way to present the criminal phenomenon. Such a crime rate is obviously an appealing indicator: it is easy to calculate and based on readily available data. Consequently, crime rates allow much-wanted comparisons. However, there is growing empirical evidence that these advantages are accompanied by inaccuracies. There are two main strategies used to control for population (size) when studying crime and three pillars of crime rates: that the level of crime activity is well measured, that the relationship of population to crime is both obvious and trivial, and that residential population size is sufficient to account for the impact of demographics on crime. Presenting crime rates rarely involve in-depth discussions of the dark figure of crime, “ambient” populations or the impact of demography on crime, even if those questions are implied.


Crime Hot Spots  

David Weisburd and Sean Wire

Hot spots of crime, and the criminology of place more generally, deviate from the traditional paradigm of criminology, in which the primary assumption and goal is to explain who is likely to commit crime and their motivations, and to explore interventions aimed at reducing individual criminality. Alternatively, crime hot spots account for the “where” of crime, specifically referring to the concentration of crime in small geographic areas. The criminology of place demands a rethinking in regard to how we understand the crime problem and offers alternate ways to predict, explain, and prevent crime. While place, as large geographic units, has been important since the inception of criminology as a discipline, research examining crime concentrations at a micro-geographic level has only recently begun to be developed. This approach has been facilitated by improvements to data availability, technology, and the understanding of crime as a function of the environment. The new crime and place paradigm is rooted in the past three decades of criminological research centered on routine activity theory, crime concentrations, and hot spots policing. The focus on crime hot spots has led to several core empirical findings. First, crime is meaningfully concentrated, such that a large proportion of crime events occur at relatively few places within larger geographies like cities. This may be termed the law of crime concentration at places (see Weisburd, 2015). Additionally, most hot spots of crime are stable over time, and thus present promising opportunities for crime prevention. Crime hot spots vary within higher geographic units, suggesting both that there is a loss of information at higher levels of aggregation and that there are clear “micro communities” within the larger conceptualization of a neighborhood. Finally, crime at place is predictable, which is important for being able to understand why crime is concentrated in one place and not another, as well as to develop crime prevention strategies. These empirical characteristics of crime hot spots have led to the development of successful police interventions to reduce crime. These interventions are generally termed hot spots policing.


Crime Mapping and Policing  

Lisa Tompson

The empirical truism that crime clusters geographically has increasingly informed police practice in the first two decades of the 21st century. This has been greatly aided by crime mapping, which can be thought of as a summary term for the geographic analysis of data related to crime and disorder. Crime analysts use a range of mapping techniques to describe and explain patterns in data, being mindful of the unique qualities of geographically referenced data. These include point pattern maps, thematic maps, kernel density estimation, and GI* statistic maps. Rate maps are also used when the aim is to understand the risk of victimization. Crime maps can be used to identify hot spots for targeted action, identify recently committed crimes that might form part of a linked series, monitor the impact of police initiatives, and aid understanding of crime problems. Environmental criminology theory is often used for the latter of these purposes, as this can explain spatiotemporal patterns revealed through crime mapping and assists in understanding the mechanisms driving the patterns. The logic for organizing police efforts around geographical crime concentration is instinctive: by focusing on a small number of locations with high crime volumes, police can be more focused and hence effective. Thus, “hot spots policing” has become business as usual in many jurisdictions, focusing attention at small units of geography. Hot spot policing has, in many countries in the early 21st century, evolved into “predictive policing,” which is a data-driven crime forecasting approach. However, this approach has attracted strong criticism for further entrenching bias in the criminal justice system. Critics argue that the data sets on which the predictive policing algorithms are founded are racially biased and perpetuate police attention on communities of color. This serves to highlight the systematic biases that can be present in crime-related data, and professional crime analysts use a range of approaches to mitigate such biases, such as triangulating data sources.


Global Security Surveillance  

Keith Guzik and Gary T. Marx

Recent literature at the intersections of surveillance, security, and globalization trace the contours of global security surveillance (GSS), a distinct form of social control that combines traditional and technical means to extract or create personal or group data transcending national boundaries to detect and respond to criminal and national threats to the social order. In contrast to much domestic state surveillance (DSS), GSS involves coordination between public and private law enforcement, security providers, and intelligence services across national borders to counteract threats to collectively valued dimensions of the global order as defined by surveillance agents. While GSS builds upon past forms of state monitoring, sophisticated technologies, the preeminence of neoliberalism, and the uncertainty of post–Cold War politics lend it a distinctive quality. GSS promises better social control against both novel and traditional threats, but it also risks weakening individual civil liberties and increasing social inequalities.


Laws of Geography  

Michael Leitner, Philip Glasner, and Ourania Kounadi

The most prominent law in geography is Tobler’s first law (TFL) of geography, which states that “everything is related to everything else, but near things are more related than distant things.” No other law in geography has received more attention than TFL. It is important because many spatial statistical methods have been developed since its publication and, especially since the advent of geographic information system (GIS) and geospatial technology, have been conceptually based on it. These methods include global and local indicators of spatial autocorrelation (SA), spatial and spatial-temporal hotspots and cold spots, and spatial interpolation. All of these are highly relevant to spatial crime analysis, modeling, and mapping and will be discussed in the main part of this text.


Lethal Violence: A Global View on Homicide  

Dietrich Oberwittler

As the most serious crime, homicide is both relevant and suitable for cross-national comparisons. The global homicide rate of ca. 6 per 100,000 people is an average of hugely diverging national rates ranging from 0.25 in Singapore to ca. 100 in El Salvador. The validity of global homicide statistics suffers from various differences in definitions as well as reporting and registration processes. Both criminal justice and causes of death statistics are used by the World Health Organization to construct rates, yet these are available only for a minority of countries. An overview on homicide in history and non-state societies shows that violence levels were considerably higher compared to those in today’s developed world and have dropped dramatically in Europe and North America during the early modern period. The rates first increased and then declined between ca.1960 and today in most developed nations in a synchronized manner, hinting at common influences. In recent years, homicide trends have shown a polarizing pattern, with increasing rates in Latin America and decreasing rates in most other world regions, especially East Asia and the Pacific, where rates have fallen below the European average concurrent with rising scores on the Human Development Index. Except in Eastern Europe, the frequency of homicide is strongly linked to the use of firearms, which account for 44% of homicide cases worldwide. Longitudinal studies have produced robust evidence for the pivotal role of deprivation and inequality in fostering lethal violence and of social welfare policies in reducing it. Although the transition to democratic political systems seems to increase homicide rates temporarily, the legitimacy of state institutions and the suppression of corruption are connected to lower homicide rates. Because of conceptual and methodological problems, questions concerning the generalizability of effects across space and time remain. Nevertheless, the research findings are sufficiently robust to draw important conclusions for violence prevention: reductions in poverty and income inequality, investments in welfare policies and gender equality, and improvements in the legitimacy of state institutions will help to bring homicide rates down.


Moving From Inequality: Housing Vouchers and Escaping Neighborhood Crime  

Michael Lens

The Housing Choice Voucher (HCV) Program is the largest housing subsidy program in the United States, serving over 2.2 million households. Through the program, local public housing authorities (PHAs) provide funds to landlords on behalf of participating households, covering a portion of the household’s rent. Given the reliance on the private market, there are typically many more locational options for HCV households than for traditional public housing, which has a set (and declining) number of units and locations. The growth of this program has been robust in recent decades, adding nearly 1 million vouchers in the last 25 years. This has been a deliberate attempt to move away from the traditional public housing model toward one that emphasizes choice and a diversity of location outcomes through the HCV program. There are many reasons for these policy and programmatic shifts, but one is undoubtedly the high crime rates that came to be the norm in and near far too many public housing developments. During the mid-20th century, when the vast majority of public housing units were created, they were frequently sited in undesirable areas that offered few amenities and contained high proportions of low-income and minority households. As poverty further concentrated in central cities due to the flight of higher-income (often white) households to the suburbs, many public housing developments became increasingly dangerous places to live. The physical design of public housing developments was also frequently problematic, with entire city blocks being taken up by large high-rises set back from the street, standing out as areas to avoid within their neighborhoods. There are many quantitative summaries and anecdotal descriptions of the crime and violence present in some public housing developments from sources as diverse as journalists, housing researchers, and architects. Now that the shift to housing vouchers (and the low-income housing tax credit [LIHTC]) has been underway for over two decades, we have a good understanding of how effective these changes have been in reducing exposure to crime for subsidized households. Further, we are beginning to better understand the limitations of these efforts and why households are often unsuccessful in moving from high-crime areas. In studies of moving housing voucher households away from crime, the following questions are of particular interest: What is the connection between subsidized housing and crime? What mechanisms of the housing voucher program work to allow households to live in lower-crime neighborhoods than public housing? And finally, how successful has this program been in reducing participant exposure to crime, and how do we explain some of the limitations? While many aspects of the relationship between subsidized housing and crime are not well understood, existing research provides several important insights. First, we can conclude that traditional public housing—particularly large public housing developments—often concentrated crime to dangerously high levels. Second, we know that public housing residents commonly expressed great concern over the presence of crime and drugs in their communities, and this was a frequent motivation for participating in early studies of housing mobility programs such as Gautreaux in Chicago and the Moving to Opportunity experiment. Third, while the typical housing voucher household lives in a lower-crime environment than public housing households, they still live in relatively high-crime neighborhoods, and there is substantial research on the limited nature of moves using vouchers. Finally, while there is research on whether voucher households cause crime in the aggregate, the outcomes are rather ambiguous—some rigorous studies have found that clusters of voucher households increase neighborhood crime and some have found there is no effect. Furthermore, any potential effects on neighborhood crime by vouchers need to be weighed against their effectiveness at reducing exposure to neighborhood crime among subsidized households.


Place-Based Simulation Modeling: Agent-Based Modeling and Virtual Environments  

Nick Malleson, Alison Heppenstall, and Andrew Crooks

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.


Place Managers and Crime Places  

John E. Eck

Place management theory—a part of routine activity theory—explains why a relatively few places have a great deal of crime while most places have little or no crime. The explanation is the way place managers carry out their four primary functions: organization of space, regulation of conduct, control of access, and acquisition of resources. Place managers are those people and organizations that own and operate businesses, homes, hotels, drinking establishments, schools, government offices, places of worship, health centers, and other specific locations. They can even operate mobile places such as busses, trains, ships, and aircraft. Some are large—a multi-story office tower for example—while others are tiny—a bus stop, for example. Place managers are important because they can exercise control over the people who use these locations and in doing so contribute to public order and safety. Consequently, it is important to understand place management, how it can fail, and what one can do to prevent failures. Place management has implications beyond high-crime sites. When crime places are connected, they can create crime hot spots in an area. The concentration of high crime places can inflate crime in a neighborhood. Moreover, place management can be applied to virtual locations, such as servers, websites, and other network infrastructures. There is considerable evaluation evidence that place managers can change high crime locations to low crime locations. Research also shows that displacement to other places, though possible, is far from inevitable. Indeed, research shows that improving a high crime place can reduce crime at places nearby places. Although much of this research has studied how police intervene with place managers, non-police regulatory agencies can carry out this public safety function.


Population Changes at Place: Immigration, Gentrification, and Crime  

Graham C. Ousey

Immigration and gentrification are two sources of population change that occur in geographic communities. Immigration refers to the inflow of foreign-born residents, while gentrification involves middle- and upper-income residents moving into poor urban communities. Scholars have speculated that both types of population change may be related to crime rates. The nature of those relationships, however, is debated. Classic criminological perspectives, such as Social Disorganization Theory, suggest that these population changes are likely to result in increased crime rates. More recent perspectives proffer an opposing viewpoint: that immigration and gentrification may lower crime rates. Some research suggests that these opposing arguments may each draw empirical support but under differing social conditions or circumstances. Regarding the effects of immigration on crime, one theory is that immigration is most likely to be a crime-protective factor when it occurs in places where there is a well-established immigrant population base and institutional supports. And immigration may contribute to higher crime rates in places that lack the strong preexisting immigrant population and institutions. Study design variations also appear to impact the findings that researchers investigating the immigration-crime relationship have found, with longitudinal studies more consistently reporting the immigration works to reduce (rather than increase) crime. With respect to gentrification, scholars suggest that its effects on crime are likely to hinge on factors such as the racial composition of the place, the timing or stage at which the gentrification process is observed, or the degree to which gentrifying neighborhoods are surrounded by poor non-gentrifying neighborhoods or by other communities that have already progressed through the gentrification process.


Rural and Remote Policing  

Rick Ruddell

Although many city residents think of life in the countryside as peaceful, there are rural and remote communities with very high crime rates. In addition, some rural populations, such as Indigenous peoples and women, are at higher risk of victimization than their urban counterparts. Regardless of where one lives, levels of crime in the countryside and the formal and informal responses to those acts—including policing—have been shaped by a series of historical, political, geographic, economic, and demographic factors, and many of those factors are interconnected. Rural crime is further distinctive as some offenses, including illegal hunting (poaching) or environmental crimes, rarely occur in cities. Moreover, responses to those acts may be carried out by military organizations, nonpolice authorities, and police officers. The involvement of these quasi-police organizations in responding to rural crime is increasing in some nations. Rural is defined in this entry as a community or place with fewer than 2,500 residents located at least 30 miles from the nearest metropolitan area. Despite recognizing that crime in the countryside is unlike what occurs in cities, there has been comparatively little scholarship on rural or remote policing. Instead, most police research is conducted and disseminated by urban researchers—what some call an urban-centric focus—and as a result knowledge about rural policing is underdeveloped. There has been even less scholarship focusing on policing remote communities, and that is a significant limitation given the distinctive patterns of crime in some of these places. Although policymakers have developed a diverse range of interventions to respond to antisocial behavior, disorder, and crime in rural and remote jurisdictions, the people in these places have a common expectation: They want the same quality of policing city residents receive. The nature of rural policing, however, makes that a very difficult goal to achieve, as officers are often stretched thin and work in more dangerous conditions than their urban counterparts. Rural officers are also expected to respond to every conceivable call for service even though they often work alone and have limited backup. This is because many stand-alone rural police services are cash strapped as they draw from sparsely populated or impoverished tax bases. Inadequate funding also limits their ability to recruit officer candidates and inhibits the sophistication of investigations, opportunities for officer training, officer retention, and the ability to provide safe working conditions for their personnel. Four issues are of key importance to understanding rural and remote policing: (a) Rural crime differs from urban crime, and in some jurisdictions, the volume of crime is similar to (or greater than) city crime rates, although the nature of crime differs (e.g., some types of crimes occur more often in rural places); (b) rural officers carry out their day-to-day duties in a distinctively different manner than municipal officers; (c) the informal and formal expectations for rural officers are higher than their counterparts working in urban areas; and (d) the challenges of rural policing are magnified in remote locations.


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.