Longitudinal Crime Trends at Places Research Paper

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The role of space and place has a long tradition in American criminology largely germinating from the ground-breaking research of Shaw and McKay (1942). Yet by the 1960s and 1970s, criminological attention had turned almost wholly to individual-level causes of crime. Over the past three decades, however, researchers have rediscovered the central role of communities in the causation and control of crime. Like people, communities have a criminal history or “criminal career”; they experience relatively more or less criminal activity than both other places in the city and compared to their own levels at earlier periods in time. To the extent that the natural history of a community affects its current crime rates, its reputation for violence, and its projected levels and patterns of crime and violence in the future, the idea that a community may follow a specific type of trajectory, or “career” may be more theoretically useful to criminologists than are cross-sectional or static patterns across space. This research paper describes the theoretical foundations of the literature on longitudinal crime trends at places, provides an abbreviated overview of various methodological approaches to modeling community crime trajectories, elaborates on some key findings, considers the conceptual implications of the unit-of-analysis (or what is meant by “place”), and ends with a discussion of both thorny issues and future directions for research.

Introduction

If it is true that the whole is greater than the sum of its parts, then a key to the success of any social group is its ability to build and sustain a sense of community – to generate a capacity for realizing the shared interests, actions, and fortunes of its members (Sampson and Groves 1989). The criminological literature on space and place primarily is concerned with investigating how one’s residential environment either creates vulnerabilities to risk of victimization or provides conditions conducive to offending among the already predisposed. Much scholarly work has identified the risk factors associated with crime in space, including: (1) the social and economic characteristics related to social disorganization such as poverty, family structure, residential mobility, ethnic and racial heterogeneity, and urbanization (Shaw and McKay 1942; Sampson and Groves 1989); (2) private, parochial, and public social controls (Bursik and Grasmick 1993; Carr 2003); (3) risky terrains rife with concentrated public housing, bus stops, liquor stores, leisure establishments, bars, and other entertainment venues (Caplan et al. 2011; Felson 1998; Griffiths and Tita 2009); and (4) gang territory or drug market locales (Tita and Ridgeway 2007), among others. These features affect the likelihood of criminal events occurring within neighborhoods.

Until recently, however, the neighborhoodeffects literature treated local characteristics as if they were relatively static or fixed. That is, the presence, absence or level of various population and land use features were used to predict the distribution of crime across urban space. Despite having much success in explaining cross-sectional aggregate crime patterns, this approach fundamentally ignores one of the basic lessons of the early disorganization scholars: communities change over time, either as a consequence or independently of the outcome under study. For this reason, it is important to consider the joint spatial and temporal aspects of communities or, said differently, longitudinal crime trends at places.

In 1986, Reiss and Tonry edited a volume of Crime and Justice: A Review of Research entitled Communities and Crime. In anticipation of this scholarly interest, the authors of Communities and Crime prepared thoughtful and important essays on the dynamics of crime across urban space, focusing on issues of stability, change, and community careers in delinquency, crime, and violence (Reiss and Tonry 1986). Unfortunately, their call for attention to the dynamics of community crime trends went largely unheralded. While the neighborhood-effects literature mushroomed (Sampson et al. 2002), it remained predominantly targeted at difference in crime across space rather than changes in crime at places over time. Criminologists are certainly much better prepared to discuss the role of communities in crime causation as a consequence of the neighborhood-effects literature, but our understanding of how crime changes over time across place remains in its infancy.

The remainder of this research paper is organized as follows. The first section describes the central theoretical arguments for explaining the dynamics of crime in space. In the second section, three common methodologies that have been employed to capture crime trends in empirical models are briefly outlined. The third section provides a short review of the literature on community trends in delinquency, crime, and violence. This is followed by a section that problematizes the plethora of “places” operationalized by researchers. Finally, the paper ends with a consideration of a number of data problems confronting scholars of neighborhoods and crime and touches upon anticipated directions of future research.

Theoretical Fundamentals

It was at the Chicago School that Clifford Shaw and Henry D. McKay first studied the distribution of delinquency across the city and pioneered one of the most important ideas in criminology of the twentieth century. In brief, Shaw and McKay (1942) observed that neighborhoods in the transitional zone – or in neighborhoods contiguous to but immediately outside of the central city – repeatedly represented the highest rates of juvenile delinquency over more than three decades (1900–1933), irrespective of the particular ethnic group residing in these places at any given period. In effect, then, rates of delinquency must be explained as a consequence of the conditions of the community rather than the personal characteristics of the persons who reside there. This finding, which undermines the premise that specific individuals or groups have an inherent predisposition toward antisocial behavior, was possible precisely because Shaw and McKay (1942) found stability in delinquency rates over a period in which extensive population change took place. It was the longitudinal nature of their research, in particular, that set the stage for this key theoretical breakthrough.

Despite its import, the heyday of social disorganization gave way as scholars turned toward individual-level explanations for offending behavior by the late 1950s and certainly the 1960s. A quarter of a century later, however, interest in places and crime trends reemerged. For example, Scheuerman and Kobrin (1986) explored the concept of stability and change in the crime rates of dangerous communities in Los Angeles and, in doing so, introduced the idea that communities have “careers” in crime in much the same way that individuals do. Specifically, they found that high-crime neighborhoods followed three distinct trends over two decades: emerging, transitional, and enduring. Moreover, the relationship between neighborhood deterioration and crime is a reciprocal one, with deterioration preceding initial spikes in crime but prompting additional deterioration once crime rates have reached high and stable levels. Scheuerman and Kobrin were focused on changes in social, economic, and family population characteristics of communities whereas both Wilson and Kelling (1982) and Skogan (1990) considered the potential reciprocity between crime and signs of neighborhood incivilities including social (panhandling, public intoxication, etc.) and physical (graffiti, broken windows, etc.) forms of disorder. According to this logic, places that appear to be uncared for by neighborhood residents and places that are void of private, parochial, and public controls are vulnerable to criminal invasion. The “spiral of decline” that ensues is inherently a temporal process (Skogan 1990).

While not focused specifically on the communities and crime question at its inception, it is noteworthy that Cohen and Felson’s (1979) Routine Activity theory also centers on how large-scale social changes influence the dynamics of crime over time. The routine activities of everyday life, including the work and home activities that shape the tempo, timing, and guardianship capabilities of communities, help to explain aggregate crime trends. At its core, then, place-based crime trends are a reflection of broad social and economic transformations that can be tracked and modeled over time. Like social disorganization theory, the central premise of routine activities theory is rooted in an examination of crime rate trends in places, rather than static or cross-sectional levels.

Methodological Diversity

A series of methodological innovations make examining crime trends at places possible. Some of the first studies focused on stability and volatility in community crime relied on cross-lagged correlations or residual change scores to decompose the degree of change between t and t-1 that could not have been predicted on the basis of levels at time t-1 (Bursik 1986). For example, Bursik (1986) compares change score models to cross-sectional models predicting community delinquency rates in Chicago at each decade between 1930 and 1970. These comparisons lead him to conclude that, “without testing the assumption of stability, ecological models will not only have a limited degree of theoretical power, but they will have an interpretive framework that is generally unrelated to the dynamics of modern urban areas” (Bursik 1986, p. 59). That is, static models ignore both expected and unexpected ecological changes that are entirely consistent with dominant theoretical explanations for community crime rates. A key limitation of these early methodological approaches is that they are “relatively cumbersome when multiple waves of data are analyzed and, for this reason, applications of such techniques have generally focused on a series of two-wave trends, providing a truncated sense of neighborhood change” (Kubrin and Herting 2003, p. 332).

More recent approaches to modeling neighborhood change and associated trends in crime rates utilize growth-curve modeling and/or semiparametric group-based trajectory procedures. Growth-curve regression models take advantage of information about the individual slopes of each geographical unit-of-analysis under study to predict how various independent variables affect changes or trends in the dependent variable (Kubrin and Herting 2003; Braga et al. 2010, 2011). The advantage of such an approach is related to the fact that no trend information is lost in the estimation of the models. Alternatively, some scholars have exploited the capacity of Nagin’s (1999) semi-parametric group-based trajectory procedure to reduce the temporal homicide rates of N census tracts, street segments, or other places into a smaller number of latent classes or groups exhibiting similar violence levels and following like-trends over some period of time (Griffiths and Chavez 2004; Groff et al. 2010; Weisburd et al. 2004). The resulting number and shapes of place-based homicide trajectories ostensibly capture the various types of place-based “criminal careers.”

Key Findings

This section provides a brief (and, of necessity, incomplete) overview of a few of the key findings in the longitudinal crime trends at places literature. Much of the research focused on crime trends across place has modeled longitudinal homicide rates – sometimes disaggregating by victim-offender relationship, motive, or weapon type – in part due to data availability and quality issues (Griffiths and Chavez 2004; Jennings and Piquero 2008; Kubrin and Herting 2003; Stults 2010). For example, in using growth-curve models to capture-distinctive trends in general altercation, felony, and domestic homicide trends in St. Louis neighborhoods, Kubrin and Herting (2003) find that disaggregation of homicide type is imperative as neighborhoods vary in temporal trends by homicide type. In particular, various aspects of neighborhood structure are related to both the amount but also the nature of neighborhood homicide. Griffiths and Chavez (2004) likewise demonstrate that Chicago neighborhoods exhibiting a high and increasing gun homicide trend between 1980 and 1995 have marked unobserved heterogeneity in their criminal careers (i.e., in their total homicide trajectories). Some of these neighborhoods are characterized by a high and unstable homicide trajectory driving citywide trends over the period, as one might expect. Yet four times as many neighborhoods following a high and increasing gun homicide trend are characterized by a moderate and relatively stable total homicide career over the same period, relative to other neighborhoods in the city. Cumulatively, these studies provide substantial evidence that place-based patterns in homicide type reveal considerable variability and instability both over time and across space.

Research at the county-level also illustrates the importance of place in understanding temporal homicide patterns. Jennings and Piquero (2008) show, for example, that rural counties are significantly more likely to exhibit non-declining intimate-partner homicide trends between 1980 and 1999, compared to their urban counterparts. And McCall et al. (2011) have recently extended this literature to examine temporal changes in the homicide rates of US cities over 30 years. Not only are cities distinguished by multiple and varied homicide trajectories, but disadvantage and other characteristics associated with social disorganization more generally (McCall et al. 2011; see also Land et al. 1990) predict membership in the consistently more violent city groupings compared to those cities that are members of the lower and more stable latent classes.

The literature on longitudinal crime trends at places is not limited to homicide research. For example, Weisburd et al. (2004) find that a very small group of street segments in Seattle are responsible for generating volatility in the citywide pattern of total criminal incident reports to police, as the vast majority of street segments follow relatively stable trends between 1989 and 2002. Studies employing trajectory or growth-curve models for crime trends at places have also measured juvenile arrests (Weisburd et al. 2009), robbery rates (Braga et al. 2011), and disorder (Yang 2010), among others. The bulk of the literature on trends in all types of criminal events at most aggregate micro (e.g., street segment, face block, intersection, etc.) and macro (e.g., census tracts, cities, counties, etc.) units-of-analysis has repeatedly shown that very few places are responsible for high rates of crime and violence, that these places tend toward volatility rather than stability in trends over time, and that the nature of the events under study (e.g., gun violence, intimate versus non-partner victim-offender relationship, age of offender, etc.) affect levels, trends, and the distribution of incidents both across places and over time.

A Plethora Of “Places”

The neighborhood-effects literature is rightfully concerned with what geographers call the Modifiable Areal Unit Problem – or the extent to which the unit-of-analysis used by the researcher as an operationalization of neighborhoods influences the findings of the study (Openshaw and Taylor 1979). Scholars interested in understanding neighborhood levels and changes in violence have tended to use census tracts as an approximation of neighborhoods (Griffiths and Chavez 2004; Hipp 2007; see Fagan 2008) while those focused on the emergence and stability of hot spots in micro-places have elected to use even smaller aggregates, such as street segments or block faces (Braga et al. 2010; Weisburd et al. 2004, 2010). Any unit-of-analysis is associated with both advantages and disadvantages, some of which are related to data availability (particularly over time), the spatial units at which policing agencies release information on criminal incidents within their jurisdictions, census units required to access structural characteristics of place, and size of the residential population or daily population flows into and out of the physical space.

One consideration in selecting the geographical unit of analysis is the extent to which the findings at one level are either robust across levels of analyses or almost wholly dependent upon the researchers’ definition of place (Hipp 2007). The problem is this: while findings that can be replicated at multiple aggregate units are arguably more robust than findings which vary across aggregations, robustness across units that bear little relation to one another or to what we mean by “neighborhood” suggests that the concept of neighborhood is relatively unimportant. It is not the extent to which the same findings can be replicated at different operationalizations that should matter, so much as the fit between the operationalization of neighborhoods in empirical research and neighborhoods on-the-ground, as identified and understood by residents.

The longitudinal crime trends at places literature is among the most open to the use of extremely varied aggregate units. This is, in part, because not all research in this area is concerned with neighborhood crime trends. Specifically, Braga and Weisburd (2010, p. 2) note that “micro-places” are “specific locations within the larger environments of communities and neighborhoods.. .[] sometimes defined as buildings or addresses, sometimes as block faces or street segments, and sometimes as clusters of addresses, block faces, or street segments.” It is in these micro-units that crime “hot spots” emerge. St. Jean (2007) makes the same point in his ethnographic study of a high-crime neighborhood in Chicago. He finds that very few streets within this community are the sites of crime and violence. The same result is found by Groff and colleagues (2010) in their quantitative study of street segments in Seattle, Washington. In this case, Groff et al. (2010) establish that there is considerable variability in the 16-year crime trajectories of street segments that are adjacent to one another; consequently, they argue that this heterogeneity in the criminal careers of very small geographic units which are situated in close spatial proximity reflects “the importance of looking at the micro level” (Groff et al. 2010, p. 26).

The openness of scholars in the longitudinal crime trends at places literature to using various different spatial aggregation of the unit-of-analysis generates a great deal of information about how crime is situated both in space and over time. Both the hot spots and the neighborhood crime literatures have benefitted from consideration of the size and shape of “places.’ At the same time, the opportunity to cherry-pick the size of the unit under study may necessitate careful theoretical unpacking. For example, how many street segments comprise a neighborhood? How is living beside a street segment following a high-crime trajectory different from living far away from one or any? Are any of the census classifications (e.g., tracts, blocks, etc.) reasonable proxies for neighborhoods? Does the concept of neighborhood really matter? What do we mean by “place” and how do places of varying sizes, shapes, and histories change the empirical picture?

Methodological Considerations And Future Directions

The longitudinal-crime-trends-at-places literature is an exciting field of study that remains largely in its infancy. As a consequence, scholars who study crime trends at places face difficulties related not only to the theoretical issues associated with defining places but also to methodological complications. A continual challenge is the availability of appropriate spatial and longitudinal data. For example, to predict changes in crime trends at places, scholars require data capturing changes in the various independent variables that are associated with aggregate levels of crime. The most widely accessible and most commonly used data on the social and economic conditions of place are compiled by the United States Census, which are available only on a decennial basis for most areas of the country. Land use and other characteristics of place not drawn from the Census can be coded to more fully specify quantitative models predicting crime trends. The problem these scholars face, however, is in explaining changes in crime as a consequence of risk factors in the setting (e.g., bars, leisure establishments, public housing) that remain relatively static over 5, 7, or even 10 years. In essence, researchers need to distinguish the “vulnerability” to crime created by these relatively stable criminogenic environmental conditions from “exposure” to crime, captured in unstable local crime trends (Caplan and Kennedy 2011).

In order for researchers to better model and specify how vulnerabilities in the form of local criminogenic conditions can result in different rates of exposure (or changes in crime over time), the gap between theory and data must be addressed. In particular, future researchers need to develop and collect more dynamic indicators of place-based crime and associated behaviors, social and demographic characteristics, land use, and other temporal aspects of place. Researchers need to consider innovative sources of data and more refined measures of key characteristics of places.

Greater attention should also be focused on measuring the intervening mechanisms which link risk and place, and which underlie the process of change in crime at places. Recent research on crime and place has identified a number of potential avenues to consider, such as social capital, collective efficacy, formal and informal social control, culture, and social isolation, among others. A renewed focus on intervening mechanisms requires that researchers integrate spatial and temporal data on these dynamics as a function of place. While developing innovative ways of substantively measuring intervening mechanisms is important, future research must also better specify the proper time lags for capturing change over time, as well as the reciprocal effects of patterns of crime, place-based characteristics, and intervening mechanisms.

Finally, future research needs to consider how the unique spatial characteristics of place create important considerations for change over time. While much of the focus on the dynamics of longitudinal trends in crime at places has centered on temporal change, we must not forget about space. A focus on space means that researchers must aim for a substantive understanding of the environment which surrounds a place, both socially and physically. Researchers need to consider how external factors may influence trajectories of crime and other place-based characteristics. The characteristics of proximate places may directly and indirectly influence levels and changes in crime. Future research should assess the interrelationship between internal rates and changes in both crime and place-based characteristics as well as external (environmental) factors. External influences include, but are not limited to, the structural and demographic characteristics of proximate places, as well as larger economic and political factors. Places may be influenced by their immediate neighbors, local law enforcement, political and economic policies, and decisions which occur well beyond the boundaries of a particular place. Focused attention toward these theoretical and methodological issues will further develop our collective understanding of the meaning of space, place, and time in the criminological literature.

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