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Spatializing the Social Networks of Gangs to Explore Patterns of Violence

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Abstract

The majority of spatial studies of crime employ an inductive approach in both the modeling and interpretation of the mechanisms of influence thought to be responsible for the patterning of crime in space and time. In such studies, the spatial weights matrix is specified without regard to the theorized mechanisms of influence between the units of analysis. Recently, a more deductive approach has begun to gain traction in which the theory of influence is used to model influence in geographic space. Using data from Los Angeles, we model the spatial distribution of gang violence by considering both the relative location of the gangs in space while simultaneously capturing their position within an enmity network of gang rivalries. We find that the spatial distribution of gang violence is more strongly associated with the socio-spatial dimensions of gang rivalries than it is with adjacency-based measures of spatial autocorrelation.

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Notes

  1. Two notable examples of this are the Project on Human Development in Chicago Neighborhoods (PHDCN) and the Los Angeles Family and Neighborhood Survey (LAFANS).

  2. Cohen and Tita (1999) argue that processes of imitation and direct influence can be conceptualized as different types of spatial diffusion and provide examples and a discussion of the various mechanisms related to diffusion within the realm of the urban homicide patterns.

  3. For a detailed review and critique of inductive approaches to modeling influence across space see Tita and Greenbaum (2009).

  4. Border effects refer to the fact that the often-arbitrary boundaries of study regions may exclude information that affects outcomes within the study region (see Griffith 1983). The modifiable areal unit problem refers to the fact that the results of statistical analysis, such as correlation and regression, can be sensitive to the geographic zoning system used to group data by area (see Gehlke and Biehl 1934 or Robinson 1950 for classic examples of MAUP, or Openshaw 1996 for a more contemporary review). While well-established in geography, these issues tend to resurface in other disciplines as spatial analysis becomes more prevalent (for example, see Hipp 2007). For a review of the treatment of these issues in the spatial analysis of crime, see Weisburd et al. (2009).

  5. City-level studies of violence, for instance, often exclude data from spatially contiguous areas located just beyond the focal city’s borders not because these areas are unimportant, but rather because the data may not be available. Because none of the rivalries extend to gangs that lie beyond the borders of the research site, there are no non-Hollenbeck rival gangs to be excluded thereby ensuring that the full extent of the social process believed to matter (gang rivalries) is being captured.

  6. Research has demonstrated that in this area of Los Angeles, gang involved violence accounts for 75% of all lethal violence (see Tita et al. 2003). Additionally, the current analysis was performed on all violent crimes regardless of gang involvement. Not surprisingly in light of the gang dominance in the commission of violent acts, there were no differences. These analyses are available from the authors upon request.

  7. As discussed previously, we theorize that the territoriality of gangs is at the heart of rivalry relations between gangs. However, we do not limit the W g matrix to include only units already claimed by neighboring gangs. We see areas that were unclaimed at the time of the study as something that gangs may compete over as well.

  8. The two most common approaches to equivalence in network analysis are structural equivalence and regular equivalence. The most important difference between the two is that structural equivalence requires that equivalent actors have the same connection to the same neighbors while regular equivalent actors have the same or similar patterns to potentially different neighbors (see Doreian et al. 2005).

  9. The choice of model should always be predicated on a particular theoretical argument. However, in exploratory work, model choice is often determined empirically based upon the results of diagnostic tests aimed at distinguishing which model (error or lag) best fits one’s data. Anselin suggests that one first consider the Lagrange multiplier test (LM). If this test is failed, then the structure of the data suggests a spatial lag process is appropriate over the alternative choice of a spatial autoregressive error model (Anselin 2002). Though the specification tests are meant for continuous variables, several transformations (logging, creating rates) of the current dependent variable (crime count) demonstrated support for the lag model over the spatial error model.

  10. Note that by using the spatially lags of the predicted values, we used a variant of the J test as originally presented in Leenders (2002) (see Piras and Lozano-Gracia (2008) for a discussion of the J test and this alternative specification). The J test was implemented using both specifications with no substantive differences. Though there were some differences in the size of the standard errors, the coefficients did not change. Both confirm the finding that the network-based specification of W better explains the observed spatial pattern of violence involving gang members.

References

  • Anselin L (1988) Spatial econometrics: methods and models. Kluwer, Dordrecht

    Google Scholar 

  • Anselin L (2002) Under the hood: issues in the specification and interpretation of spatial regression models. Agric Econ 27:247–267

    Article  Google Scholar 

  • Anselin L, Syabri I, Kho Y (2006) GeoDa: an introduction to spatial data analysis. Geogr Anal 38:5–22

    Article  Google Scholar 

  • Baller RD, Anselin L, Messner SF (2001) Structural covariates of U.S. county homicide rates: incorporating spatial effects. Criminology 39:561–590

    Article  Google Scholar 

  • Bellair PE (2000) Informal surveillance and street crime: a complex relationship. Criminology 38:137–167

    Article  Google Scholar 

  • Blau JR, Blau PM (1982) The cost of inequality: metropolitan structure and violent crime. Am Sociol Rev 47:114–129

    Article  Google Scholar 

  • Bursik R, Grasmick H (1993) Neighborhoods and crime: the dimensions of effective community control. Lexington Books, San Francisco

    Google Scholar 

  • Case AC, Rosen HS, Hines JR Jr (1993) Budget spillovers and fiscal policy interdependence: evidence from the states. J Public Econ 52:285–307

    Article  Google Scholar 

  • Cohen J, Tita G (1999) Diffusion in homicide: exploring a general method for detecting spatial diffusion processes. J Quant Criminol 15:451–493

    Article  Google Scholar 

  • Cohen J, Cork D, Engberg J, Tita G (1998) The role of drug markets and gangs in local homicide rates. Homicide Stud 2:241–262

    Article  Google Scholar 

  • Cork D (1999) Examining space-time interaction in city-level homicide data: crack markets and the diffusion of guns among youth. J Quant Criminol 5:379–406

    Article  Google Scholar 

  • Decker S (1996) Collective and normative features of gang violence. Justice Q 13:243–264

    Article  Google Scholar 

  • Dekker D, Krackhardt D, Snijders TAB (2007) Sensitivity of MRQAP tests to collinearity and autocorrelation conditions. Psychometrika 72:563–581

    Article  Google Scholar 

  • Doreian P, Batageli V, Ferligoj A (2005) Positional analyses of sociometric data. In: Carrington PJ, Scott J, Wasserman S (eds) Models and methods in social network analysis. Cambridge University Press, New York, pp 77–97

    Google Scholar 

  • Ettlinger N, Bosco FJ (2004) Thinking through networks and their spatiality: a critique of the US (public) war on terrorism and its geographic discourse. Antipode 36:249–271

    Article  Google Scholar 

  • Feld S (1981) The focused organization of social ties. Am J Sociol 86:1015–1035

    Article  Google Scholar 

  • Florax R, Rey S (1995) The impacts of misspecified spatial interaction in linear regression models. In: Anselin L, Florax R (eds) New directions in spatial econometrics. Springer, Berlin, pp 111–135

    Google Scholar 

  • Gehlke C, Biehl K (1934) Certain effects of grouping upon the size of the correlation coefficient in census tract material. J Am Stat Assoc 29:169–170

    Article  Google Scholar 

  • Getis A, Aldstadt J (2004) Constructing the spatial weights matrix using a local statistic. Geogr Anal 36:90–104

    Article  Google Scholar 

  • Goodchild MF (2004) GIScience, geography, form, and process. Ann Assoc Am Geogr 94:709–714

    Article  Google Scholar 

  • Gould R (1991) Multiple networks and mobilization in the Paris Commune, 1870. Am Sociol Rev 56:716–729

    Article  Google Scholar 

  • Greenbaum RT (2002) A spatial study of teachers’ salaries in Pennsylvania school districts. J Labor Res 23:69–86

    Article  Google Scholar 

  • Griffith DA (1983) The boundary value problem in spatial statistical analysis. J Reg Sci 23:377–378

    Article  Google Scholar 

  • Griffiths E, Chavez JM (2004) Communities, street guns and homicide trajectories in Chicago, 1980–1995: merging methods for examining homicide trends across space and time. Criminology 42:941–975

    Article  Google Scholar 

  • Hipp JR (2007) Block, tract, and levels of aggregation: neighborhood structure and crime and disorder as a case in point. Am Sociol Rev 72:659–680

    Article  Google Scholar 

  • Kennedy D, Braga A, Piehl A (1997) Mapping gangs and gang violence in Boston. In: Weisburd D, McEwan T (eds) Crime mapping & crime prevention. Justice Press, Monsey, pp 219–262

    Google Scholar 

  • Klein MW (1971) Street gangs and street workers. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Klein MW (1995) The American street gang: Its nature, prevalence and control. Oxford University Press, New York

    Google Scholar 

  • Krivo LJ, Peterson RD (1996) Extremely disadvantaged neighborhoods and urban crime. Soc Forces 75:619–650

    Google Scholar 

  • Kubrin CE, Weitzer R (2003) Retaliatory homicide: concentrated disadvantage and neighborhood culture. Soc Probl 50:157–180

    Article  Google Scholar 

  • Land KC, Deane G (1992) On the large-sample estimation of regression models with spatial effects terms: a two-stage least squares approach. Sociol Methodol 22:221–248

    Article  Google Scholar 

  • Land KC, McCall PL, Cohen L (1990) Structural covariates of homicide rates: are there any invariances across time and social space? Am J Sociol 95:922–963

    Article  Google Scholar 

  • Leenders RTAJ (2002) Modeling social influence through network autocorrelation: constructing the weight matrix. Soc Netw 24:21–47

    Article  Google Scholar 

  • Loftin C (1986) Assaultive violence as a contagious process. Bull N Y Acad Med 62:550–555

    Google Scholar 

  • Marsden PV, Friedkin NE (1994) Network studies of social influence. In: Wasserman S, Galaskiewicz J (eds) Advances in social network analysis. Sage, Thousand Oaks, pp 3–25

    Google Scholar 

  • McGloin JM (2005) Policy and intervention considerations of a network analysis of street gangs. Criminol Public Policy 4:607–636

    Article  Google Scholar 

  • McPherson M, Smith-Lovin L, Cook JM (2001) Birds of a feather: homophily in social networks. Annu Rev Sociol 27:415–444

    Article  Google Scholar 

  • Mears DP, Bhati AS (2006) No community is an island: the effects of resource deprivation on urban violence in spatially and socially proximate communities. Criminology 44:509–548

    Article  Google Scholar 

  • Meyers MK, Heintze T, WolfChild DA (2002) Care subsidies and the employment of welfare recipients. Demography 39:165–179

    Article  Google Scholar 

  • Moore J (1985) Isolation and stigmatization in the development of an underclass: the case of Chicano gangs in East Los Angeles. Soc Probl 33:1–12

    Article  Google Scholar 

  • Moore J (1991) Going down to the barrio: homeboys and homegirls in change. Temple University Press, Philadelphia

    Google Scholar 

  • Morenoff JD (2003) Neighborhood mechanisms and the spatial dynamics of birth weight. Am J Sociol 5:976–1017

    Article  Google Scholar 

  • Morenoff JD, Sampson RJ (1997) Violent crime and the spatial dynamics of neighborhood transition: Chicago, 1970–1990. Soc Forces 76:31–64

    Google Scholar 

  • Morenoff JD, Sampson RJ (2004) Spatial (dis)advantage and homicide in Chicago neighborhoods. In: Goodchild MF, Janelle DG (eds) Spatially integrated social science. Oxford Press, New York, pp 145–170

    Google Scholar 

  • Morenoff JD, Sampson RJ, Raudenbush S (2001) Neighborhood inequality, collective efficacy, and the spatial dynamics of urban violence. Criminology 39:517–560

    Article  Google Scholar 

  • Murphy KM, Topel RH (1985) Estimation and inference in two-step econometric models. J Bus Econ Stat 3:370–379

    Article  Google Scholar 

  • Newman D (2006) The resilience of territorial conflict in an era of globalization. In: Kahler M (ed) Territoriality and conflict in an era of globalization. Cambridge University Press, Cambridge, UK, pp 85–110

    Chapter  Google Scholar 

  • Openshaw S (1996) Developing GIS-relevant zone-based spatial analysis methods. In: Longley P, Batty M (eds) Spatial analysis: modeling in a GIS environment. Wiley, New York, pp 55–73

    Google Scholar 

  • Papachristos AV (2009) Murder by structure: dominance relations and the social structure of gang homicide. Am J Sociol 115:74–128

    Article  Google Scholar 

  • Piras G, Lozano-Gracia N (2008) Spatial J-test: some Monte Carlo evidence. Stat Comput

  • Radil SM, Flint C, Tita G (2010) Spatializing social networks: geographies of gang rivalry, territoriality, and violence in Los Angeles. Ann Assoc Am Geogr 100:307–326

    Article  Google Scholar 

  • Reiss AJ, Farrington DP (1991) Advancing knowledge about co-offending: results from a prospective longitudinal survey of London males. J Crim Law Criminol 82:360–395

    Article  Google Scholar 

  • Robinson W (1950) Ecological correlation and the behavior of individuals. Am Sociol Rev 15:351–357

    Article  Google Scholar 

  • Rosenfeld R, Bray T, Egley A (1999) Facilitating violence: a comparison of gang-motivated, gang-affiliated, and non-gang youth homicides. J Quant Criminol 5:495–516

    Article  Google Scholar 

  • Sack RD (1986) Human territoriality: its theory and history. Cambridge University Press, Cambridge

    Google Scholar 

  • Sampson RJ (1986) Crime in cities: formal and informal social control. In: Reiss AJ Jr, Michael T (eds) Communities and crime. University of Chicago Press, Chicago, pp 271–311

    Google Scholar 

  • Sampson RJ (1988) Local friendship ties and community attachment in mass society: a multi level systemic model. Am J Sociol 53:766–779

    Article  Google Scholar 

  • Sampson RJ (2004) Networks and neighbourhoods: the implications of connectivity for thinking about crime in the modern city. In: McCarthy H, Miller P, Skidmore P (eds) Network logic: who governs in an interconnected world? Demos, London, pp 157–166

    Google Scholar 

  • Sampson RJ, Groves WB (1989) Community structure and crime: testing social-disorganization theory. Am J Sociol 94:774–802

    Article  Google Scholar 

  • Sampson RJ, Sharkey P (2008) Neighborhood selection and the social reproduction of concentrated racial inequality. Demography 45:1–29

    Article  Google Scholar 

  • Sampson RJ, Raudenbush S, Earls F (1997) Neighborhoods and violent crime: a multilevel study of collective efficacy. Science 277:918–924

    Article  Google Scholar 

  • Sampson RJ, Morenoff JD, Gannon-Rowley T (2002) Assessing “neighborhood effects”: social processes and new directions in research. Annu Rev Sociol 28:443–478

    Article  Google Scholar 

  • Shaw CR, McKay H (1942) Juvenile delinquency and urban areas. University of Chicago Press, Chicago

    Google Scholar 

  • StataCorp (2005) Statistical software: release 8.0. Stata Corporation, College Station

    Google Scholar 

  • Taylor RB, Gottfredson S, Brower S (1984) Block crime and fear: defensible space, local social ties, and territorial functioning. J Res Crime Delinq 21:303–331

    Article  Google Scholar 

  • Thornberry TP, Krohn MD, Lizotte AJ, Smith CA, Tobin K (2003) Gangs and delinquency in developmental perspective. Cambridge University Press, Cambridge

    Google Scholar 

  • Tita G, Cohen J (2004) Measuring spatial diffusion of shots fired activity across city neighborhoods. In: Goodchild MF, Janelle DG (eds) Spatially integrated social science. Oxford Press, New York, pp 171–204

    Google Scholar 

  • Tita G, Greenbaum RT (2009) Crime, neighborhoods, and units of analysis: putting space in its place. In: Weisburd D, Bernasco W, Bruinsma GJN (eds) Putting crime in its place: units of analysis in spatial crime research. Springer, New York, pp 145–170

    Chapter  Google Scholar 

  • Tita G, Ridgeway G (2007) The impact of gang formation on local patterns of crime. J Res Crime Delinq 44:208–237

    Article  Google Scholar 

  • Tita G, Riley KJ, Greenwood P (2002) From Boston to Boyle Heights: The process and prospects of a ‘pulling levers’ strategy in a Los Angeles barrio. In: Decker S (ed) Gangs, youth violence and community policing. Wadsworth Press, Belmont, pp 102–130

    Google Scholar 

  • Tita G, Riley KJ, Ridgeway G, Grammich C, Abrahamse AF, Greenwood P (2003) Reducing gun violence: results from an intervention in East Los Angeles. RAND Press, Santa Monica

    Google Scholar 

  • Tita G, Cohen J, Engberg J (2005) An ecological study of the location of gang ‘set space’. Soc Probl 52:272–299

    Article  Google Scholar 

  • Tobler W (1970) A computer movie simulating urban growth in the Detroit region. Econ Geogr 46:234–240

    Article  Google Scholar 

  • Veysey BM, Messner SF (1999) Further testing of social disorganization theory: an elaboration of Sampson and Groves’ ‘Community structure and crime’. J Res Crime Delinq 36:147–156

    Article  Google Scholar 

  • Vigil JD (1988) Barrio gangs: street life and identity in Southern California. University of Texas Press, Austin

    Google Scholar 

  • Vigil JD (2002) A rainbow of gangs: street cultures in the mega-city. University of Texas Press, Austin

    Google Scholar 

  • Ward MD, Gleditsch K (2008) Spatial regression models. Sage, Thousand Oaks, CA

    Google Scholar 

  • Weisburd D, Bernasco W, Bruinsma GJN (eds) (2009) Putting crime in its place: units of analysis in spatial crime research. Springer, New York

    Google Scholar 

  • Weisburd D, Bushway S, Lum C, Yang S-M (2006) Trajectories of crime at places: a longitudinal study of street segments in the city of Seattle. Criminology 42:283–322

    Google Scholar 

  • Whyte WF (1943) Street corner society. University of Chicago Press, Chicago

    Google Scholar 

  • Wilkinson D, Fagan J (1996) Understanding the role of firearms in violence scripts: the dynamics of gun events among adolescent males. Law Contemp Probl 59:55–90

    Article  Google Scholar 

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Authors and Affiliations

  1. Criminology, Law and Society, University of California, Irvine, Irvine, CA, USA

    George E. Tita

  2. Department of Geography, University of Illinois at Urbana-Champaign, Urbana, Champaign, IL, USA

    Steven M. Radil

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  1. George E. Tita
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Correspondence to George E. Tita.

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Tita, G.E., Radil, S.M. Spatializing the Social Networks of Gangs to Explore Patterns of Violence. J Quant Criminol 27, 521–545 (2011). https://doi.org/10.1007/s10940-011-9136-8

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