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Race, Space, and the Spread of Violence Across the City
Abstract
A central explanation for elevated violence in urban African American neighborhoods is that the relationship can be accounted for by race-related differences in socioeconomic conditions. Yet recent studies have shown that predominantly African American neighborhoods experience higher rates of violence relative to other ethno-racial communities, even when socioeconomic conditions can be held constant. Explanations for these differences center on the deleterious effects of extensive residential segregation and the existing racial order privileging whites and their communities. This study examines whether the concentration and spread of urban violence can be characterized as a racially invariant process over half a century. In a detailed case study of the prototypical “rustbelt” city of Buffalo, New York, between the 1950s and the 1990s, negative binomial regression analyses fail to support the racial invariance thesis for predicting intra-neighborhood homicide rates. Multinomial logit regression models show that racial composition is also associated with vulnerability to inclusion in a cluster of highly violent neighborhoods as homicide diffused across the city, especially in recent decades. Thus, the spatial organization of urban African American neighborhoods generates a unique racialized vulnerability to the extralocal diffusion of violence; there is, in effect, an ecological racial variance in the spread of violence across the city. Moreover, this process has become increasingly entrenched over time, undermining any assertion that the urban experience reflects a post-racial America.
... Located in Western New York, the city grew substantially and prospered through the mid-1950s due to its strong industrial base and accessibility via railroads and the Erie Canal. Like other shrinking rust-belt cities, such as Cleveland and Detroit, the city underwent significant economic and demographic downturns in the second half of the twentieth century due to the decline in its manufacturing sector and urban deterioration (Griffiths 2013;Silverman et al. 2015). Currently, Buffalo is a mid-sized city with a population of a little more than 250,000 residents. ...
... While the majority of the demographic variables were not statistically significant, this is not surprising, given the short time period (five years) and using fixed effect models. Given that such demographic characteristics tend to be temporally consistent and slowly changing in Buffalo (Griffiths 2013), it is not surprising these effects do not result in statistically significant effects on crime (Worrall 2008). While we expected the inclusion of the residential addresses term to have a positive effect on crime, only in the CAD model did it have a statistically significant effect on crime, and this was negative. ...
Objectives
From 2010 through 2015, the city of Buffalo demolished over 2,000 residences. This study examines whether those demolitions resulted in crime reductions.
Methods
Analysis was conducted at microplaces matching demolished parcels to comparable control parcels with similar levels of crime. In addition, spatial panel regression models were estimated at the census tract and quarterly level, taking into account demographic characteristics of neighborhoods.
Results
We find that at the microplace level, demolitions cause a steep drop in reported crime at the exact parcel and result in additional crime decreases at buffers of up to 1,000 feet away. At the census tract level, results indicated that demolitions reduced part 1 crimes, but the effect was not statistically significant across different models.
Conclusions
While concerns over crime and disorder are common for vacant houses, the evidence that housing demolitions are an effective crime reduction solution is only partially supported by the analyses here. Future research should compare demolitions in reference to other neighborhood revitalization processes.
... Evidence suggests that exposure to community violence is not equally distributed among youth or across space (Peterson and Krivo, 2009;Rojas-Gaona et al., 2016;Voisin and Berringer, 2014). Indeed, a consistent findings in the violence literature is the enduring relationship among race, place, and violence (Friedson and Sharkey, 2015;Graif and Matthews, 2017;Griffiths, 2013;Morenoff et al., 2001). A large proportion of neighborhood studies historically emphasize the role of concentrated poverty and racial segregation on the differential rate of violence exposure among Black and Latinx youth as larger shares of these children and youth live in high poverty neighborhoods compared to the poorest of their white peers (Gibson et al., 2009;McArdle and Acevedo-Garcia, 2017;Sampson, 1993). ...
Exposure to community violence is an epidemic problem that causes debilitating effects on youth mental health. However, the relationships between violence exposure and youth mental health remain unclear when examining co-occurring socioecological risk and protective factors. The purpose of this study is to clarify the observed gaps in knowledge by utilizing structural equation modeling (SEM) to examine the mediating role of community violence exposure on the relationship between perceived neighborhood risk factors, parental behaviors, and peers on depressive symptoms in a sample of urban youth in low-income public housing communities (n = 320). Results indicate that community violence exposure and exposure to delinquent peers mediates the effects of perceived neighborhood risk and parenting behaviors on depressive symptoms. These findings suggest that while interventions that limit exposure to community violence and delinquent peers could reduce depressive symptoms, interventions that reduce community violence are essential to improve youth mental health.
... But, as later research proved, this is untrue. Segregation and homogeneity, especially in the context of capitalism, can sometimes lead to more conflict than heterogeneity, and crime is not caused by low-income populations or racial minorities (Bonilla-Silva, 1997;Griffiths, 2013). Overall, the original social disorganization theories were not explicitly racist, but theorists did not necessarily discuss the nuanced, problematic aspects of the theories thus leaving room for white supremacist ideologies to creep into research on crime, space, and place. ...
This paper provides a comprehensive review of space‐ and place‐based criminology, with a focus on the relationship between crime, the built environment, land use, and/or physical geography, through sociological and critical geography lenses. An historical overview of major criminological and spatial theories and contributors is presented before examining the current state of the field. In honor of critical geography's goal to be “a people's geography,”1 this paper aims to be an accessible overview of space‐ and place‐based criminological research, especially for readers who are unfamiliar with these topics.
... Social disorganization can play an important role in the diffusion of homicide across geographical space. Socially disorganized neighborhoods lack the capacity for community control, increasing opportunities for illegal markets, the spread of deviant norms, and conflict (Fagan & Davies, 2004;Griffiths, 2013). Social disorganization can also create conditions favorable to the emergence and spread of criminal and organized crime groups, as residents are often neglected by state security services and lack the collective capacity to confront these groups (Cardia et al., 2003;Oliveira et al., 2015;Rengert et al., 2005). ...
This study aims to contribute to understanding urban spatial and temporal patterns of social disorganization and homicide rates in São Paulo, Brazil (2000-2015). Using exploratory spatial data analysis and spatial panel regression techniques, we describe spatial-temporal patterns of homicide rates and assess to what extent social disorganization can explain between-district variation in homicide trajectories. The results showed some variation in the pattern of homicide decline across districts, and less disorganized communities experienced earlier, more linear declines. However, we found no evidence to suggest that changes in social disorganization are associated with differences in the decline in homicide rates.
... Minorities, regardless of sex, are more likely to reside in neighborhoods characterized by structural conditions that are linked to higher crime (e.g., Krivo and Peterson 1996;Ousey 1999;Phillips 2002;Sampson and Wilson 1995), and Blacks reside in the most disadvantaged circumstances ( Krivo and Peterson 1996;McNulty 2001). Empirical studies that account for aggregate-level differential exposure to disadvantage have found that the effects of structure on crime vary across race/ethnicity (e.g., Griffiths 2013;Krivo and Peterson 2000;Messner and Golden 1992;Ousey 1999;Steffensmeier et al. 2010), suggesting that racial/ ethnic groups may have a differential susceptibility to the structural disadvantage to which they are exposed. ...
Objectives
We draw upon theories of social disorganization, strain, and subculture of violence to examine how sex and race/ethnicity intersect to inform nonlethal violent offending at the macrolevel.
Methods
Using neighborhood-level incidents, we examine (1) the structural correlates of male and female nonlethal violence and (2) whether ecological conditions have variable impacts on the prevalence of White, Black, and Latino male and female offenses above and beyond differential exposure to disadvantage. We use multivariate negative binomial regression within a structural equation modeling framework which allows for the examination of the same set of indicator variables on more than one dependent variable simultaneously while accounting for covariance between the dependent variables.
Results
We find few significant differences in the salience of disadvantage on female and male violence across race and ethnicity although some differences emerge for White men and women. Structural factors are largely sex invariant within race and ethnicity.
Conclusions
Despite expectations that disadvantage would have differential effects across sex and race/ethnicity, we uncover only minor differences. This suggests that structural effects are more invariant than variant across subgroups and highlights the importance of investigating both similarities and differences when examining neighborhood structure, intersectionality, and criminal behavior.
... This general gap in scholarship has some notable exceptions. Recent research by Daniel Mears and Avinash Bhati (2006), Ruth Peterson and Lauren Krivo (2010), Patrick Sharkey (2014), and Elizabeth Griffiths (2013), for example, considers how spatial inequality plays an important role for social change in neighborhoods. In all of these studies, researchers find that, in varying ways, some neighborhoods experience a significant "spatial disadvantage," which may have serious implications for their crime rates (Sharkey 2014, 909). ...
Recognition is growing that criminogenic neighborhood effects may not end at the borders of local communities , that neighborhoods are located relative to one another in ways that shape local crime rates. Inspired by this insight, this research explores the changing spatial distribution of race and income around a location and determines how such changes are associated with crime patterns and trends in neighborhoods in Los Angeles. We examine how changes from 2000 to 2010 in the income composition, racial composition, and intersection of these two constructs are linked with changes in levels of crime across local areas. We find that neighborhoods experiencing greater increases in spatial inequality in a broader area (two and a half miles around the neighborhood) experience greater increases in crime levels in the focal area over the decade, and that this pattern is strongest for neighborhoods simultaneously experiencing increasing average household income or increasing inequality. We also find that neighborhoods simultaneously experiencing increases in inequality and racial-ethnic heterogeneity experience increases in crime.
... Desert conditions seem to amplify the effects of structural disadvantage on violence, leaving neighborhoods less sensitive of incremental increases in disadvantage compared with those that exist on the edge of more stable communities. Our Desert × Disadvantage interaction term shows that, in desert communities, added disadvantage is associated with predicted decreased rather than increased levels of violence-a finding that can be situated within broader research on threshold effects and the invariance thesis (Griffiths, 2013;Hipp & Yates, 2011;Light & Harris, 2012;Taylor, 2015). Our findings here support the assertion that extreme levels of disadvantage may work to dismantle all options of local social control (Hipp & Yates, 2011). ...
We advance discussion of structural inequality by operationalizing "concentrated" disadvantage in terms of highly disadvantaged communities located at the spatial core of contiguous areas of high disadvantage, and by testing the extent to which such location achieves an independent effect on violence. Using exploratory spatial data analysis and count modeling, we show that highly disadvantaged communities located at the center of a contiguous ghetto have significantly higher rates of violence than other highly disadvantaged communities; but, that this relationship is moderated by structural disadvantage. In addition to finding a significant interaction between these “deserts” of disadvantage and structural disadvantage as they relate to violent crime, we also observe that in desert communities, disadvantage has a diminishing effect on violence.
... First, that structural social inequalities -such as limited access to quality education, employment opportunities, medical services, housing, family support services, and transportation -are experienced by some racial and ethnic groups far more than others, which can create strain, frustration, and aggression, and lead to their differential involvement in crime (Balkwell, 1990;Blau and Blau, 1982;Lauritsen and Heimer, 2010;Massey and Eggers, 1990;Peterson, 2012;Phillips, 2002;Ulmer et al., 2012;Wright and Younts, 2009). Second, that the residential and community segregation of certain racial and ethnic groups perpetuates structural disadvantages and limits social mobility, thus preventing many people from escaping the destructive cycles of violence that create both victims and future victimizers (Griffiths, 2013;Krivo et al., 2009;Lee and Ousey, 2007;Peterson and Krivo, 1993;Peterson, 2012). And third, that historical and contemporary racial discrimination and bias have had a range of negative effects (Brunson, 2007;Duran, 2009;Weitzer and Tuch, 2004), and that for some individuals, they may increase the likelihood of criminal behavior. ...
In the popular discourse, it is commonly assumed that mass murderers and mass shooters are different from most criminals in the United States, because they are almost always white. The present study uses data on 308 mass murderers who attacked from 2006 to 2014 to evaluate this assumption, test for racial differences between mass murderers and all other murderers, and identify characteristics of mass murderers’ behavior by race and ethnic group. Findings suggest that, overall, the racial composition of mass murderers is similar to that of other murderers, and thus may be largely explained by similar social forces, such as structural disadvantages and social inequalities. However, there are significant differences across racial and ethnic groups in attack subtype, victims killed, and attack resolution. In particular, the structural advantages and aggrieved entitlement experienced by whites may help explain their involvement in public mass shootings. Further research in both the United States and other countries may shed additional light on the behavior of mass murderers and the broader social forces that shape them.
... Most conclusions regarding the segregation-crime link stem from analyses using one of two approaches. They either examine segregation measures that summarize overall differences in the geographic locations of race-ethnic and economic groups throughout a city or metropolitan area (e.g., Feldmeyer, 2010;Krivo et al., 2009;Peterson and Krivo, 2010a) or employ spatial regression techniques that incorporate geographic clustering of crime (or another outcome) into the modeling (Cohn and Jackman, 2011;Griffiths, 2013;Griffiths and Chavez, 2004;Morenoff et al., 2001;Tita and Radil, 2010). Studies using the former approach demonstrate that crime, particularly violent crime, is higher in cities and metropolitan areas where Blacks and Latinos are segregated in different neighborhoods from Whites. ...
... As Logan (2012) suggests, more "place for space" (i.e., how space shapes human social psychology and behavior) is needed in empirical work, and indeed there has been a relative outpouring of research that examines the influence of geographical contexts on things such as health disparities (e. g., Browning and Cagney 2003), environmental degradation (e.g., Elliot and Frickel 2013), crime (e.g., Griffiths 2013), and political contention (e. g., Leitner, Sheppard, and Sziarto 2008). This issue of the International Journal of Sociology seeks to contribute to this growing literature by investigating urbanization as both a determinant of attitudes and social organization and a policy challenge for environmental sustainability. ...
This study examined the relationship between neighborhood social ecology and homicide in Detroit, Michigan. Additionally, the research examined the influence of recent population decline in Detroit on homicides through a focus on localized population change at the census tract level. The study findings reveal that the traditional social ecological predictors of crime continue to operate in similar ways to previous studies. However, when the population change variable is introduced to the model, the traditional social ecological predictors are no longer significant. This indicates that population change might be a driving feature of the high homicide rate in Detroit. Implications for research, theory, and practice are discussed.
This study examined the relationship between neighborhood social ecology and homicide in Detroit, Michigan. Additionally, the research examined the influence of recent population decline in Detroit on homicides through a focus on localized population change at the census tract level. The study findings reveal that the traditional social ecological predictors of crime continue to operate in similar ways to previous studies. However, when the population change variable is introduced to the model, the traditional social ecological predictors are no longer significant. This indicates that population change might be a driving feature of the high homicide rate in Detroit. Implications for research, theory, and practice are discussed.
While U.S. homicide rates remain at near historical lows, large percentage increases in homicide in 2015 have generated much speculation about its causes among policy makers, academics, criminal justice practitioners, media representatives, and other social commentators. In this article, we show how two data visualization tools, funnel charts, and time series fan charts can show the typical volatility in homicide rates in different cities over time. Many of the recent increases are not out of the norm given historical patterns, and so one need not rely on various ex ante hypotheses to explain homicide spikes occurring in many U.S. cities.
This article tests a conditional effect hypothesis which predicts that the strength and magnitude of the association between
racial composition and crime rates will dissipate with increasing distance of neighborhoods from public housing projects.
We examine this hypothesis with 1990–92 geo-coded crime incident data matched with 1990 block-group-level census data for
Atlanta. The hypothesis is supported in models predicting murder, rape, assault, and public order crime, but not robbery and
property crime. Confirmation of our conditional effect hypothesis for several major types of crime suggests the potential
for bias in interpretations of estimated race effects in multivariate neighborhood-level models that do not control for public
housing.
The distinction between deindustrialization with destructuring—the disintegration of an economic structure - and deindustrialization with restructuring is missing from much of the debate over deindustrialization in metropolitan areas and the appropriate policy responses to it. Empirical research must account for different sequencing of destructuring and restructuring in different cities. Buffalo experienced destructuring with little or no restructuring, whereas Pittsburgh experienced them simultaneously. Both cities experienced deindustrialization well before the usual period of study. These issues are illustrated by a comparison of Pittsburgh and Buffalo, and some political and policy consequences are noted.
This study examined the spatial and temporal movement of homicide in Newark, New Jersey from January 1982 through September 2008. We hypothesized that homicide would diffuse in a similar process to an infectious disease with firearms and gangs operating as the infectious agents. A total of 2,366 homicide incidents were analyzed using SaTScan v.9.0, a cluster detection software. The results revealed spatio-temporal patterns of expansion diffusion: overall, firearm, and gang homicide clusters in Newark evolved from a common area in the center of the city and spread southward and westward over the course of two decades. This pattern of movement has implications in regards to the susceptibility of populations to homicide, particularly because northern and eastern Newark remained largely immune to homicide clusters. The theoretical and practical implications of the findings, as well as recommendations for future research, are discussed.
Most studies of the relationship between race and crime employ data aggregated at the city or SMSA level to show that high proportions of Blacks indicate high levels of crime. However, theoretical accounts of underlying criminogenic processes do not imply an effect for race, but rather involve explicit or implicit reference to the neighborhood as the unit of analysis. We combine 1990 census data with arrest records for 1989–1991 to generate complete block group information (n = 276) for a medium size southern city. Contrary to studies showing a relationship between racial composition and crime, we show that structural factors account for this effect completely. This finding challenges accounts of crime based on subculture and is consistent with accounts based on the social and economic structure of communities.
The link between resource deprivation and urban violence has long been explored in criminological research. Studies, however, have largely ignored the potential for resource deprivation in particular communities to affect rates of violence in others. The relative inattention is notable because of the strong theoretical grounds to anticipate influences that extend both to geographically contiguous areas and to those that, though not contiguous, share similar social characteristics. We argue that such influences—what we term spatial and social proximity effects, respectively—constitute a central feature of community dynamics. To support this argument, we develop and test theoretically derived hypotheses about spatial and social proximity effects of resource deprivation on aggregated and disaggregated homicide counts. Our analyses indicate that local area resource deprivation contributes to violence in socially proximate communities, an effect that, in the case of instrumental homicides, is stronger when such communities are spatially proximate. We conclude by discussing the implications of our findings for theories focused on community-level social processes and violence, and for policies aimed at reducing crime in disadvantaged areas.
Since 1968, violence and other crimes in New York City have followed a pattern of recurring epidemics. There have been three consecutive and contiguous cycles characterized by sharp increases in homicides and assaults to an elevated rate followed by equally steep declines to levels near the previous starting point. The most recent epidemic, from 1985-96, had the sharpest rise and steepest decline of the three epidemics. Popular explanations of the current epidemic fail to account for both the rise and fall of the decline, or for the repetitive pattern of these epidemics. In this article, we use public health data to identify factors associated with the cyclical rise and fall of homicides and non-lethal injury violence in this most recent of the three epidemics. Homicides in this period were concentrated among minority males, ages 15-24, while victimization rates for females of all ages remained stable. Gun homicides and non-lethal gun assaults accounted for all the increase and decline in interpersonal violence from 1985-95; intentional injuries caused by other means also were stable or declining over this period. Next, we use hierarchical linear regression models, with a rich set of time-varying covariates and controls for both temporal and spatial autocorrelation, to identify whether the rise and fall of homicide are explained by processes of diffusion across adjacent neighborhoods. We estimate the probabilities of homicides and assaults in a neighborhood controlling for rates of homicide or assault in the surrounding neighborhoods in the preceding year, and find that gun violence diffuses across neighborhoods over time. Epidemic patterns of violence disproportionately affected African Americans as victims of gun violence, both homicides and non-lethal gun assaults. Diffusion was strongest in neighborhoods where social control was compromised by extreme poverty and concentrated racial segregation. Concentrations of immigrant households in neighborhoods were a protective factor in suppressing the violence epidemic. We then use social contagion theories to link contagion of violence across neighborhoods to individual data on social interactions that may animate the transmission and diffusion of violence. Analyses of the social contexts and interpersonal dynamics of violent events reveals how street interactions in interpersonal disputes link individuals within and across social networks in a competition for status that is skewed by the presence of firearms. Decisions to carry, show and use weapons are based on perceptions of threat and danger, which are shaped by the presence of firearms and the potential stigma associated with non-action. These events occur across multiple contexts - bars, streetcorners, drug markets - to reinforce perceptions of risk and expectations of the threat or reality of lethal violence.
Spatial analysis is statistically and substantively important for macrolevel criminological inquiry. Using county-level data for the decennial years in the 1960 to 1990 time period, we reexamine the impact of conventional structural covariates on homicide rates and explicitly model spatial effects. Important findings are: (1) homicide is strongly clustered in space; (2) this clustering cannot be completely explained by common measures of the structural similarity of neighboring counties; (3) noteworthy regional differences are observed in the effects of structural covariates on homicide rates; and (4) evidence consistent with a diffusion process for homicide is observed in the South throughout the 1960–1990 period.
The possibility that homicides can spread from one geographic area toanother has been entertained for some time by social scientists, yetsystematic efforts to demonstrate the existence, or estimate the strength,of such a diffusion process are just beginning. This paper uses exploratoryspatial data analysis (ESDA) to examine the distribution of homicides in 78counties in, or around, the St. Louis metropolitan area for two timeperiods: a period of relatively stable homicide (1984–1988) and aperiod of generally increasing homicide (1988–1993). The findingsreveal that homicides are distributed nonrandomly, suggestive of positivespatial autocorrelation. Moreover, changes over time in the distribution ofhomicides suggest the possible diffusion of lethal violence out of onecounty containing a medium-sized city (Macon County) into two nearbycounties (Morgan and Sangamon Counties) located to the west. Althoughtraditional correlates of homicide do not account for its nonrandom spatialdistribution across counties, we find some evidence that more affluentareas, or those more rural or agricultural areas, serve as barriers againstthe diffusion of homicides. The patterns of spatial distribution revealedthrough ESDA provide an empirical foundation for the specification ofmultivariate models which can provide formal tests for diffusion processes.
In this article we take an empirical cross-country perspective to investigate the robustness and causality of the link between income inequality and crime rates. First, we study the correlation between the Gini index and, respectively, homicide and robbery rates along different dimensions of the data (within and between countries). Second, we examine the inequality-crime link when other potential crime determinants are controlled for. Third, we control for the likely joint endogeneity of income inequality in order to isolate its exogenous impact on homicide and robbery rates. Fourth, we control for the measurement error in crime rates by modelling it as both unobserved country-specific effects and random noise. Lastly, we examine the robustness of the inequality-crime link to alternative measures of inequality. The sample for estimation consists of panels of non-overlapping 5-year averages for 39 countries over 1965-95 in the case of homicides, and 37 countries over 1970-1994 in the case of robberies. We use a variety of statistical techniques, from simple correlations to regression analysis and from static OLS to dynamic GMM estimation. We find that crime rates and inequality are positively correlated (within each country and, particularly, between countries), and it appears that this correlation reflects causation from inequality to crime rates, even controlling for other crime determinants.
The epidemic history of measles is described and explored within the island of Iceland, and is used to develop and test a series of spatial diffusion models. 16 major measles epidemics have occurred over the last 80 years and both single and multi-region models are used. Time series methods are also used, and existing explicit process-based epidemic models are used. It was not found possible to provide accurate forecasts of both epidemic recurrence and magnitude. -J.Clayton
Social deprivation and social isolation perspectives provide grounds for expecting residential segregation to increase violent crime among oppressed minorities. This paper examines the impact of racial residential segregation on rates of African-American homicide victimization for large US central cities. The analyses demonstrate that black-white segregation leads to higher rates of black killing although the relationship exists only for stranger and acquaintance homicides. This suggests that social isolation, rather than social deprivation, is the mechanism by which segregation leads to higher levels of homicide among African Americans. -from Authors
Although low-skill, entry-level employment has facilitated the social mobility of central city populations, evidence confirms
that these once plentiful jobs are disappearing. This shift in the industrial structure of central cities has been especially
detrimental to the economic and social well-being of low-skill city residents and may be linked to the rates of violence in
urban communities. Using racially disaggregated data from the census and the Uniform Crime Reports for central cities in 1970
and 1990, we examine the direct and indirect relationship between the industrial structure of central cities and the rates
of homicide. The findings reveal that a decline in the access to low-skill jobs increases violence indirectly by first increasing economic deprivation. We model these relationships for racially disaggregated populations and find that
the effects are similar for blacks and whites. The analysis supports a macro-social link between violence and urban industrial
restructuring in central cities.
This analysis examines how the spatial concentration of Southern whites is associated with white argument-based lethal violence. Using a well-known measure of spatial segregation (V, the adjusted P* index) among Southern-born whites in U.S. counties in 2000, the results reveal that the spatial concentration of Southern-born whites is only moderately correlated with their overall representation within counties. This confirms that the quantity of Southerners in an area is not the same thing as their spatial distribution within that same area. Multivariate negative binomial regression models confirm that white argument homicide rates are higher where white Southerners are more spatially concentrated, a link that is confined to Southern counties. The findings illustrate the important role spatial arrangements may play in producing expressive violence among white Southerners.
Recent research has begun to address patterns and causes of homicide among African Americans, the population most at risk as victims and offenders. Seeking to add to this literature, a race-specific analysis of homicide rates and macrostructural variables among U.S. central cities is performed. A variety of factors from past homicide studies serve to predict white rates of homicide, allowing for the development of a broad profile of white communities with low rates of homicides. In contrast, only two factors (population size and residential segregation) are statistically-significant predictors of homicide rates among African Americans, resulting in an essentially non-descriptive community profile. The results suggest that the two groups may be subject to different social forces, and the ensuing discussion poses the possibility that understanding differences in homicide rates among African-American communities may require an incorporation of factors not normally considered in homicide research.
How can we understand the dramatic linkages among race, ethnicity, place, and violence in the United States? One contention is that differences in violence across communities of varying race-ethnic compositions are rooted in highly differentiated social and economic circumstances of the segregated neighborhoods inhabited by whites, African Americans, Latinos, and other groups. Here, the authors draw upon and expand this perspective by exploring how inequality in the character of internal and nearby neighborhood conditions leads to patterned racial and ethnic differences in violence across areas. Using data from the National Neighborhood Crime Study to examine the racial-spatial dynamic of violence for neighborhoods in thirty-six U.S. cities, the authors demonstrate that along with the social and economic conditions that exist within neighborhoods, proximity to more disadvantaged and especially racially privileged (heavily white) areas is particularly critical in accounting for the large and visible differences in violence found across neighborhoods of different colors.
This study tests the effects of neighborhood inequality and heterogeneity on crime rates. The results of this study, which were obtained by using a large sample of census tracts in 19 cities in 2000, provide strong evidence of the importance of racial/ethnic heterogeneity for the amount of all types of crime generally committed by strangers, even controlling for the effects of income inequality. Consistent with predictions of several theories, greater overall inequality in the tract was associated with higher crime rates, particularly for violent types of crime. Strong evidence revealed that within racial/ethnic group inequality increases crime rates: Only the relative deprivation model predicted this association. An illuminating finding is that the effect of tract poverty on robbery and murder becomes nonsignificant when the level of income inequality is taken into account; this finding suggests that past studies that failed to take income inequality into account may have inappropriately attributed causal importance to poverty. This large sample also provides evidence that it is the presence of homeowners, rather than residential stability (as measured by the average length of residence), that significantly reduces the level of crime in neighborhoods.
Previous research demonstrates differences in the processes that generate black and white rates of criminal violence. Analyses of race-specific urban homicide offending rates for 1990 test the hypothesis that racially different effects occur because the crime-generating process itself is conditioned by the social situations of blacks and whites. Results show that when African Americans and whites have similar low levels of concentrated disadvantage, the effects of disadvantage and homeownership are relatively comparable.
■ Abstract This paper assesses and synthesizes the cumulative results of a new "neighborhood-effects" literature that examines social processes related to problem behaviors and health-related outcomes. Our review identified over 40 relevant studies published in peer-reviewed journals from the mid-1990s to 2001, the take-off point for an increasing level of interest in neighborhood effects. Moving beyond traditional char- acteristics such as concentrated poverty, we evaluate the salience of social-interactional and institutional mechanisms hypothesized to account for neighborhood-level varia- tions in a variety of phenomena (e.g., delinquency, violence, depression, high-risk behavior), especially among adolescents. We highlight neighborhood ties, social con- trol, mutual trust, institutional resources, disorder, and routine activity patterns. We also discuss a set of thorny methodological problems that plague the study of neigh- borhood effects, with special attention to selection bias. We conclude with promising strategies and directions for future research, including experimental designs, taking spatial and temporal dynamics seriously, systematic observational approaches, and benchmark data on neighborhood social processes.
This article examines variation across cities in the geographic concentration of poverty, male joblessness, and female-headed families for Blacks and Whites. For each racial group, we describe the scope and analyze the sources of concentrated disadvantage along these dimensions for 1980 and 1990, and for changes between these two years. We explore whether patterns found in past research regarding poverty concentration are generalizable to the concentration of other aspects of disadvantage, including joblessness. Analysis of the sources of concentrated disadvantage focus on the differential role of racial residential segregation for explaining variation in concentrated disadvantage between Blacks and Whiles. These relationships are evaluated while accounting for other economic and sociodemographic conditions. We find that: between 1980 and 1990 Black and White disadvantage became more geographically concentrated along some dimensions (poverty and female-headed families) but not others (male joblessness); MO matter which dimension is explored, African Amt!ricans have a substantially higher concentration of disadvantage than Whites; and, racial residential segregation is critical for understanding concentrated disadvantage and especially for explaining why disadvantaged Blacks are so much more geographically concentrated than disadvantaged Whites.
The social disorganization and anomie perspectives generally suggest that poverty's criminogenic effect is racially invariant. These perspectives imply that policies that alleviate economic deprivation will equally reduce rates of violent crime in neighborhoods that are predominately white and neighborhoods that are predominately black. In contrast, several social commentators have suggested that alleviating poverty will be a relatively ineffective crime reduction strategy in predominately black areas. Existing empirical research on this issue has been mostly at the city level, and almost entirely cross-sectional. The present study examines potential racial differences in the longitudinal relationship between neighborhood poverty and violent crime rates. We use iteratively reweighted least squares, a robust regression technique, to estimate race-specific effects for Cleveland census tracts, 1990–2000. The results are supportive of the racial invariance hypothesis. Reductions in neighborhood poverty appear to produce similar reductions in violent crime in white and black neighborhoods.
Political elites and major economic development actors claim that Detroit is “coming back,” but they have rejected the former city of racial segregation and humiliation as a template for its reemergence. Instead, they are reimagining a new city, guided by three different templates: Detroit as a world-class city, Detroit as a tourist destination, and Detroit as the vital center of a prosperous metropolitan area. Unfortunately, Detroit's circumstances and resources are inadequate to realize any of these visions. Furthermore, the expenditure of political capital and financial resources in pursuit of these visions is creating a city that will function mainly for visitors rather than residents.
We merge Exploratory Spatial Data Analysis (ESDA) and a semi-parametric, group-based trajectory procedure (TRAJ) to classify communities in Chicago by violence trajectories across space. Total, street gun and other weapon homicide trajectories are identified across 831 census tracts between 1980 and 1995. We find evidence consistent with a weapon substitution effect in violent neighborhoods that are proximate to one another, a defensive diffusion effect of exclusively street gun-specific homicide increases in neighborhoods bordering the most violent areas, and a spatial decay effect of temporal homicide trends in which the most violent areas are buffered from the least violent by places experiencing mid-range levels of lethal violence over time. In merging these two methods of data analysis, we provide a more efficient way to describe both spatial and temporal trends and make significant advances in furthering applications of space-time methodologies.
Key Words urban crime, racial/ethnic inequality, structural disadvantage, neighborhood effects, deviance, social control ■ Abstract In 1995, Sampson & Wilson assessed the state of knowledge on race and violence and set forth an approach for future research. We review macrostructural analyses of race, ethnicity, and violent crime since 1995 to evaluate progress in ex-plaining inequality in criminal violence across racial and ethnic groups. Among the important advances are studies that attempt to gain insights from explicit comparisons of racially distinct but structurally similar communities, expansion of work beyond the black-white divide, and incorporation of macrostructural factors into multilevel models of racial/ethnic differences in violence. Yet, progress is limited in all these di-rections, and additional questions remain. Thus, we offer a perspective and suggestions for future research that will expand knowledge on this important topic.
Addressing the methodological shortcomings of extant research on the racial invariance thesis, race-specific rates of intimate assault are examined across census tracts in Hamilton County, Ohio. We extend Miles-Doan's (1998) approach to examining neighborhood structural effects on intimate assault rates in order to test the racial invariance thesis. Findings reveal comparable effects of neighborhood disadvantage and population age structure on assault rates for African-American males and white males, yet a stronger effect of “disinvestment” (in marriage and in neighborhoods) on rates for African-Americans. These results conflict with previous city-level analyses demonstrating stronger structural effects on other violent crime rates for whites.
Macrolevel research on the race-violence relationship has focused on the assumption of racial invariance in the effects of structural disadvantage measures on violence. Yet in most urban areas black and white disadvantage distributions only partially overlap, which precludes a critical empirical test of the assumption. I refer to this as the problem of “restricted distributions.” Using block group data for Atlanta, results show that the effect of a disadvantage index on violence is similar in black and white neighborhoods within the low range of the disadvantage distribution, but diminishes significantly at the higher levels prevalent in black areas. I discuss the implications of the findings and suggest avenues for future research.
Historians of telegraphy have traditionally focused on the system-builders who invented wire communications technologies and incorporated them into profit-making enterprises. Geographers of communications have traditionally traced the changes that the telegraph network wrought on the rank-size of cities and the speed of business. Both have ignored the history of the telegraph messenger boys and the “lived geography” of the telegraph network. This article summarizes a study of telegraph messengers as both active components of technological systems and laboring agents within produced urban spaces, bringing together the fields of both history of technology and human geography.
Structural theories in criminology generally assume that the effects of structural conditions on homicide are the same for all race-groups. However, previous homicide research testing this assumption contains methodological shortcomings and has produced inconsistent findings. Therefore, the validity of the “racial invariance assumption” remains highly questionable. Using 1990 data for 125 U.S. cities, this study addresses some of the limitations of previous research in an effort to provide a more definitive examination of race differences in the effects of important structural factors on homicide rates. Contrary to the expectations of the structural perspective, the results from this study reveal substantial and statistically significant race differences. Specifically, the associations between homicide and several measures of socio-economic deprivation (e.g., poverty, unemployment, income inequality, female-headed households, deprivation index) are found to be stronger among whites than blacks. A primary implication of these results is that the current versions of many structural theories need revision in order to account for observed race differences in the effects of structural factors and to explain fully the black-white gap in homicide rates.
The capabilities for visualization, rapid data retrieval, and manipulation in geographic information systems (GIS) have created the need for new techniques of exploratory data analysis that focus on the “spatial” aspects of the data. The identification of local patterns of spatial association is an important concern in this respect. In this paper, I outline a new general class of local indicators of spatial association (LISA) and show how they allow for the decomposition of global indicators, such as Moran's I, into the contribution of each observation. The LISA statistics serve two purposes. On one hand, they may be interpreted as indicators of local pockets of nonstationarity, or hot spots, similar to the Gi and G*i statistics of Getis and Ord (1992). On the other hand, they may be used to assess the influence of individual locations on the magnitude of the global statistic and to identify “outliers,” as in Anselin's Moran scatterplot (1993a). An initial evaluation of the properties of a LISA statistic is carried out for the local Moran, which is applied in a study of the spatial pattern of conflict for African countries and in a number of Monte Carlo simulations.
Highlighting resource inequality, social processes, and spatial interdependence, this study combines structural characteristics from the 1990 census with a survey of 8,872 Chicago residents in 1995 to predict homicide variations in 1996–1998 across 343 neighborhoods. Spatial proximity to homicide is strongly related to increased homicide rates, adjusting for internal neighborhood characteristics and prior homicide. Concentrated disadvantage and low collective efficacy—defined as the linkage of social control and cohesion—also independently predict increased homicide. Local organizations, voluntary associations, and friend/kinship networks appear to be important only insofar as they promote the collective efficacy of residents in achieving social control and cohesion. Spatial dynamics coupled with neighborhood inequalities in social and economic capacity are therefore consequential for explaining urban violence.
This article proposes a new method for examining dynamic changes in thespatial distribution of a phenomenon. Recently introduced exploratoryspatial data analysis (ESDA) techniques provide social scientists with anew set of tools for distinguishing between random and nonrandom spatialpatterns of events (Anselin, 1998). Existing ESDA measures, however, arestatic and do not permit comparisons of distributions of events in the samespace but across different time periods. One ESDA method—the Moranscatterplot—has special heuristic value because it visually displayslocal spatial relationships between each spatial unit and its neighbors. Weextend this static cross-sectional view of the spatial distribution ofevents to consider dynamic features of changes over time in spatialdependencies. The method distinguishes between contagious diffusion betweenadjoining units and hierarchical diffusion that spreads broadly throughcommonly shared influences. We apply the method to homicide data, lookingfor evidence of spatial diffusion of youth-gang homicides acrossneighborhoods in a city. Contagious diffusion between neighboring censustracts is evident only during the year of peak growth in total homicides,when high local rates of youth-gang homicides are followed by significantincreases in neighboring youth- nongang rates. This pattern is consistentwith a spread of homicides from gang youth to nongang youth. Otherwise, theincreases in both youth-gang and youth- nongang homicides generally occursimultaneously in nonneighboring tracts.
This article introduces the use of regression models based on the Poissondistribution as a tool for resolving common problems in analyzing aggregatecrime rates. When the population size of an aggregate unit is small relativeto the offense rate, crime rates must be computed from a small number ofoffenses. Such data are ill-suited to least-squares analysis. Poisson-basedregression models of counts of offenses are preferable because they arebuilt on assumptions about error distributions that are consistent withthe nature of event counts. A simple elaboration transforms the Poissonmodel of offense counts to a model of per capita offense rates. Todemonstrate the use and advantages of this method, this article presentsanalyses of juvenile arrest rates for robbery in 264 nonmetropolitancounties in four states. The negative binomial variant of Poisson regressioneffectively resolved difficulties that arise in ordinary least-squaresanalyses.
This paper examines the relationships among unemployment, crime, and family disruption in the black "underclass." The main hypothesis tested is that the effect of black adult male joblessness on black crime is mediated largely through its effects on family disruption. The study examines race-specific rates of robbery and homicide by juveniles and adults in over 150 U.S. cities in 1980. The results show that the scarcity of employed black men increases the prevalence of families headed by females in black communities. In turn, black family disruption substantially increases the rates of black murder and robbery, especially by juveniles. These effects are independent of income, region, race and age composition, density, city size, and welfare benefits and are similar to the effects of white family disruption on white violence. The paper concludes that there is nothing inherent in black culture that is conducive to crime. Rather, persistently high rates of black crime appear to stem from the structural linkages among underemployment, economic deprivation, and family disruption in urban black communities. Sociology
Shaw and McKay's influential theory of community social disorganization has never been directly tested. To address this, a community-level theory that builds on Shaw and McKay's original model is formulated and tested. The general hypothesis is that low economic status, ethnic heterogeneity, residential mobility, and family disruption lead to community social disorganization, which, in turn, increases crime and delinquency rates. A community's level of social organization is measure in terms of local friendship networks, control of street-corner teenage peer groups, and prevalence of organizational participation. The model is first tested by analyzing data for 238 localities in Great Britain constructed from a 1982 national survey of 10,905 residents. The model is then replicated on an independent national sample of 11,030 residents of 300 British localities in 1984. Results from both surveys support the theory and show that between-community variations in social disorganization transmit much of the effect of community structural characteristics on rates of both criminal victimization and criminal offending. Sociology
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