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CONFERENCE VERSION

SOCIAL CONTAGION OF VIOLENCEa Jeffrey Faganb Deanna Wilkinsonc Garth Daviesd

a. This research was supported by grants from the Centers for Disease Control, the National Institute of Justice, and the Robert Wood Johnson Foundation, in addition to support from the Sloan Working Group on Social Contagion of Youth Violence. All opinions and errors are mine alone. Data on homicide characteristics and locations were generously provided by the Injury Prevention Program, New York City Department of Health. Excellent research assistance was provided by Jay Galluzzo, Garth Davies, Deanna Wilkinson, Tamara Dumanovsky, Marlene Pantin and Carolyn Pinedo. Thanks also to interviewers Richard McClain, David Tufino, Davon Battee, and Whetsel Wade, for creating a unique and very rich source of data on streetcorner life in New York City. b. Professor, School of Public Health, Columbia University, and Visiting Professor, Columbia Law School. c. Assistant Professor, Department of Criminal Justice, Temple University. d. Assistant Professor, Department of Criminology, Simon Fraser University.

Presented at the Urban Seminar Series on Children's Health and Safety John F. Kennedy School of Government Harvard University

May 11, 2000

SOCIAL CONTAGION OF VIOLENCE

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Like many large American cities, New York City experienced a sudden and dramatic increase in homicides beginning in 1985. The homicide runup was highest for adolescents, but rates increased quickly for older persons as well (Fagan, Zimring and Kim, 1998). Unlike other cities, however, where homicides declined gradually and have yet to recede to their pre-1985 levels, the increase in New York was followed by an even larger decline over the next five years. By 1995, homicide in New York City had returned to its 1985 level; by 1996, it was 15% lower than the previous low in 1985; by 1997, homicide was about 25% lower than its 1985 level. Both in New York and nationally, this decline was unprecedented not just in the present era, but represents a decline of greater magnitude than any observed in large American cities since the 1950s. Explanations of this rollercoaster pattern have tended to partition the periods of increase and decline as distinct phenomena with unique causes. Moreover, these causes are typically regarded as exogenous to the people or areas affected. For example, the onset and severity of the homicide trend was attributed to the sudden emergence of unstable street-level crack markets, with high levels of violence between sellers (Fagan and Chin, 1990; Baumer, et al., 1996). Others suggested that drug markets created a demand for guns that in turn trickled down from drug sellers into the hands of adolescents (Fagan, 1992; Blumstein, 1995). Structural theorists implicated race-specific economic deficits in inner cities (Peterson and Krivo, 1996) or racial residential segregation (Massey, 1995). There have been many claims regarding the sources of the decline, including changes in police strategy (Kelling and Cole, 1996), demographic changes (Eckberg, 1995; Cook and Laub, 1998), incarceration (Blumstein and Beck, 1999), and lower demand for illegal drugs (Curtis, in press). None of the explanations of either the increase or the decline are fully satisfying. Moreover, the gap between the scale of demographic and policy changes and the scale of the crime decline suggests that there are processes at work other than


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these usual suspects. Some have used the term epidemic metaphorically to describe the homicide runup and decline, but with little precision and often conflating several features of epidemics.1 Epidemic is a term widely used in the popular and scientific literature to describe two quite separate components of a phenomenon: an elevated incidence of the phenomena, and its rapid spread via a contagious process within a population in a short period of time.2 Epidemics need not be contagious. Consider an outbreak of food poisoning from contaminated materials, or a cancer cluster nearby a polluted water supply. These medical problems may occur at a rate well above an expected base rate, but are not spread from person to person through physical contact or an infectious process. In contrast, an outbreak of influenza, the adaptation of cultural fads, medical or industrial innovation, or changes in the rates of antisocial behavior, all reflect spread through interpersonal exposure to an “infectious” agent. While disease spreads through a host and agent,3 social contagion involves the mutual influence of individuals within social networks who turn to each other for cues and behavioral tools that reflect the contingencies of specific situations (Burt, 1987; Bailey, 1967; Coleman et al., 1966).

1. Others use the term more literally, but usually to conflate several different processes: social concentration, spatial diffusion, and temporal spikes. See, for example, Norman T. Bailey, The Mathematical Theory of Infectious Diseases and Applications (1976). 2. For example, Gladwell (1996: 33-4) describes how the incidence of an ordinary and stable phenomenon such as a seasonal flu can become epidemic when its incidence increases in a very short time from a predictable base rate to an elevated rate of infections. 3. See, for example, Kenneth Rothman, Modern Epidemiology (1986); Leon Robertson, Injury Epidemiology (1990).


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The contagious dimension is especially salient during the upswing of an epidemic, when physical or social contact is critical to spread pursuant to exposure. Epidemics end, also, as the rate of new incidence of the phenomenon declines. This may occur because the density of contacts may decline, or because some form of resistance develops that reduces the odds of transmission from one person to the next, even in the presence of exogenous contributing factors (Burt, 1992; Bailey, 1967). In this paper, we assess whether the rollercoaster pattern of homicides in New York City from 1985-96 fits a contagious model, and identify mechanisms of social contagion that predict its spread across social and physical space. This framework for interpreting the homicide trends as an epidemic includes two perspectives. First, the sharp rise and fall is indicative of a non-linear pattern where phenomenon are spreading at a rate far beyond what would be predicted by exposure to some external factor. And, the phenomenon declines in a similar pattern where the reduction from year to year exceed what might be expected by linear regression trends. This leads to the second perspective: the factors leading to its spread are not exogenous factors, as in the case of contamination or disaster. Instead, the non-linear increase and decline suggest that the phenomenon is endemic to the people and places where its occurrence is highest. And, this behavior may be effectively passed from one person to another through some process of contact or interaction. We assess the validity of these assumptions in three ways. In Part I, we use Vital Statistics data from the New York City Department of Health to present simple time series data that describe the increase and decline in homicides. We concentrate on homicides involving adolescents and young adults, populations who experienced the sharpest rise and decline in homicide, both in New York and nationally (Fagan et al., 1998; Cook and Laub, 1998). We supplement these data with police records of complaints and arrests to raise and evaluate competing explanations of youth homicide. In Part II, we examine the spatial and social trends in youth homicide by disaggregating the data by neighborhoods over the 11 year period, and fitting models


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to demonstrate the spatial diffusion of youth homicide in specific areas of the city. By covarying neighborhood social and economic characteristics with temporal homicide trends, we are able to show that the diffusion of homicide in this era was specific to the most socially isolated areas of the City. In this section, we isolate gun homicides as the contagious agent, showing that it is gun homicides that diffused across New York City neighborhoods, and gun homicides that retreated just as quickly. In Part III, we present data from interviews with young males active in gun violence during this time. Their reports of the role of guns in violent events further specify how diffusion may in fact be the results of a dynamic process of social contagion. We conclude by integrating these perspectives into a framework for theory, research and policy development.

I. THE EPIDEMIOLOGY OF YOUTH HOMICIDE IN NEW YORK CITY A. Historical and Current Homicide Trends

The epidemic of youth violence in New York City from 1985-95 is best understood in a social and historical context that spans nearly 35 years. Like the nation’s largest cities, New York experienced a sharp increase in homicide and other violence rates beginning in the mid-1960's. The homicide rate rose from 4.7 per 100,000 population in 1960 to 31.0 in 1995. By 1996, the rate had receded to 13.9 per 100,000, a level unseen since 1968. Figure 1 shows the homicide counts for 1968-96, disaggregated by gun and non-gun methods. The 1960 rates were typical of homicide rates in New York City for the first half of this century. With the exception of the decade influenced by the Volstead Act and the Great Depression, homicide rates in New York City varied between 3.8 and


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5.8 per 100,000 population.4 From 1965 to 1970, the average annual homicide rate rose from 7.6 to 12.6, and rose again to 21.7 by 1975. Thus, homicide counts and rates in New York nearly tripled within a decade. The rates have remained for the past 35 years at the plateau first reached in 1968. Accordingly, Figure 1 suggests that homicides in New York have been normalized at an elevated rate, and has become characteristic of the city’s social landscape. Thus, the escalation in killings is cumulative, with each new peak building on the elevation of the base rate established in the previous peak. One interpretation of the recent decline may simply be the recession of this longer-term social and historical trend. Figure 1 also shows that this long-term trend involves three sub-epidemics. The first of these peaked in 1972, the second in 1981, and the third in 1991. Each coincided temporally with drug epidemics and the growth of retail drug markets: heroin in the early 1970's, powder cocaine in the late 1970's, and crack beginning in 1985 (Johnson et al., 1990). Moreover, successive epidemics were cumulative in their trends, not distinct. To use a term introduced in Part I, the pattern of killings in particular does rather resemble the shape of a rollercoaster, with an ascent through the late 1970s to a relatively low peak, a return to near the previous low point, a sharp increase to a high peak in 1990 and a precipitous drop thereafter. Finally, Figure 1 also shows the growing importance of guns in homicides in each of the three peaks. Increases in both gun and non-gun homicides contributed to the tripling of homicide rates through 1972. In 1972, the ratio of gun to non-gun homicides was 1.23. By the next peak in 1981, the 1,187 gun deaths were nearly 1.76 times greater than the 673 non-gun homicides. In 1991, the modern peak, the 1,644 gun homicides were 3.16 times greater than the 519 non-gun homicides. In addition to sharp increases the number of gun homicides, the gun:non-gun

4. In its 1996 report, the Office of Vital Statistics and Epidemiology reports homicide rates prior to 1985 in five year intervals. Homicide rates rose from an average of 4.9 in 1916-1920 to 7.6 in 1931-1935, and declined to 4.5 by 1936-1940 (NYCDOH, 1997).


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ratio also rose sharply because of a long-term decline in the number of non-gun homicides. Since 1980, the number and rate of non-gun homicides has declined by nearly 50 percent, from 735 to 335 non-gun killings in 1996. There are thus two dynamic and different pattern in the data on homicide by weapon. Gun killings follow the rollercoaster pattern of steadily increasing peaks beginning in 1972. Nongun killings trend down from 1980, to rates unseen since 1960. This long-term secular trend in nongun killings is substantial, but it has not previously been noticed. Figure 1 also shows that the recent 1985-96 cycle was qualitatively different from the preceding peaks in four important ways: (1) its starting point was lower than the starting point for previous (1981) peak, (2) its peak was about 15% higher than the preceding peak, (3) it had a far greater share of gun killings, and (4) its decline was far steeper than any previous decline (Fagan et al., 1998). To illustrate the extent of the differences between the 1985-96 cycle and its predecessors, Figure 2 presents the data from Figure 1 normed to the 1985 base.5 Gun killings accounted for all of the increase in homicides in this period, and most of the decline. Non-gun killings declined steadily since 1986, and by 1996 were about half the 1985 rate. Gun homicides doubled from 1985 to 1991, and then declined by 1996 to about 70% of the 1985 starting point. From the peak in 1991, gun homicides declined by over 60 percent. While the declines after 1992 in nongun killings are a continuation of the eight years of previous decreases, the increase and decline in gun killings is evidence of a homicide spike that is unique from its predecessors.

B. The Social Structure of Homicide

5. The nongun total for 1990 has been adjusted by deleting 89 of the 90 killings from the Happyland Social Club fire, in effect counting that episode as one homicide. This is done to smooth out the long-term trend curve.


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The demographic patterns of gun and nongun homicide victimization during this period tell two interesting stories, and two predictable stories. First, the homicide trends for women differ from the patterns for men. Second, changes in adolescent homicide rates were accompanied by parallel but less dramatic changes among older populations. This trend varies from the national picture of steadily declining rates among older groups. Third, as we saw before, the homicide runup and decline were concentrated in gun killings. Fourth, the homicide epidemic was concentrated among non-whites. We observed these trends for both homicide victims and offenders.

1. Sex Nearly all the increase and decline in killings from 1985-95 were gun homicides of males.6 Table 1 shows that the rate of gun killings among males doubled from 21.8 per 100,000 in 1985 to 44.5 in 1991. Non-gun killings of males declined steadily throughout this period, and by 1995 were less than half the 1985 rate. Killings of males were increasingly gun events: the ratio of gun to non-gun homicide victimizations of males increased from about 1.5:1 in 1985 to 3.23:1 in 1995. Table 1 shows that the temporal patterns were similar for females. The rate of gun homicides of females peaked in 1991, the same year as males, and sustained their peak rate for approximately three years before dropping sharply in 1994. By 1995, gun homicides for females had dropped 5% below their 1985 levels. Non-gun homicides of women declined steadily throughout this period, from 4.7 per 100,000 in 1985 to 3.8 per 100,000 in 1995.

But unlike males, the rates of non-gun

homicides of females were higher than the rates of gun homicides. Throughout the

6. The 1990 spike for male nongun homicides most likely reflects the 89 arson homicide deaths in the Happyland Social Club fire. We could not adjust the age-, race-, or gender-specific rates for these homicide deaths since data were not available on their characteristics.


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period, the changes in rates for females were quite small, and not far from the expected rates historically. The same is true of male non-gun killings. Accordingly, this epidemic is confined to gun killings among males.

2. Race Nationally, virtually all increases in homicide rates from 1985 to 1990 among people 10-34 years of age were due to deaths of African American males. Most of these were firearm fatalities that were overwhelmingly concentrated demographically and spatially among African American males in urban areas (Fingerhut, Ingram, and Feldman, 1992a; 1992b.) The trends in New York mirror these national trends. Unfortunately, none of the data sources permitted detailed disaggregation of the homicide trends by ethnicity over the entire 1985-1995 period. Detailed data were available only for African Americans; whites and Hispanics were not distinguished in the police or Vital Statistics data until after 1990. Our analysis is limited to comparisons between whites and non-whites; non-whites are primarily persons of African descent, including some Hispanics. Table 2 compares gun and non-gun homicides by race for each year. The within-race ratio of gun to non-gun homicide rates illustrates the concentration of the homicide epidemic in gun homicides among non-whites. For whites, the ratio rises from 1.26:1 in 1985 to a peak of 3.23:1 in 1992, before receding to 2.1:1 in 1995. For non-whites, the ratio rises from 1.20:1 in 1985 to a peak of 4.05:1 in 1992, and recedes to 2.32:1 in 1995. The narrow difference between whites and non-whites in Table 2 is due to the inclusion of Hispanics among the whites in the population and homicide counts. The extent of this bias can be seen in 1993 data from the New York City Department of Health injury surveillance system. The mortality and morbidity rates of gunshot wounds for Hispanics is 228 per 100,000 persons, compared to 302 for African


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Americans and 60 for Whites in that period.7

3. Age Much of public and scholarly attention on violence in the past decade has focused on the increase in gun homicides by adolescents (Blumstein, 1995; Cook and Laub, 1998). Trends nationwide show that gun homicide rates for adolescents increased during this period while gun homicide rates for persons over 25 years of age were declining. In New York City, homicides were not confined to younger age groups, but were a serious problem across a wide age range from 15 to 34 years of age. Table 3 shows that gun homicide rates were higher than non-gun rates for all age groups. For each year, gun homicide rates were highest for persons 20-24 years in all years. Gun homicides by adolescents ages 15-19 rose more sharply over this period than other older population groups. Nevertheless, Table 2 shows that while adolescent participation in gun homicide did rise sharply from 1985-1991, rates for other age groups also continued to rise during this period. Gun homicide rates declined sharply for all three age groups from 1992-95, to about 50% of their peak rates in 1991, and were about the same as their 1985 rates. Although post-1991 decline was precipitous for adolescents 15-19 years of age, their 1995 gun homicide rates remained exceeded 25% above their 1985 base rate. Table 3 also shows that nongun homicide rates declined steadily for all age groups, and by 1995 were 50% or more lower than their 1995 rates.8 Similar to gun homicide rates, the non-gun homicide rates were highest for persons ages 20-24 years.

4. Victim-Offender Homogeneity

7. See, for example, New York City Department of Health, Injury Mortality in New York City, 1980-90 (1992); New York State Department of Health. Injury Facts for New York State (1994). 8. New York City Department of Health, id. at __.


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Most homicides are within-group events, especially with respect to gender, race and ethnicity (Sampson and Lauritsen, 1994; Cook and Laub, 1998). (Exceptions include domestic homicides, and homicides that follow rape.) For homicides in New York City from 1985-95, the aggregate age, gender and race characteristics of homicide victims also applied to homicide offenders. At the case level, we observed within-group homogeneity with respect to our limited categories of race. However, despite aggregate age similarities, the age composition of homicide events may differ for gun and non-gun killings, and these differences may have widened during the most recent homicide cycle. Age stratification of peer groups has traditionally created age-specific social networks. These rigid age boundaries offered few opportunities for cross-age social interactions among delinquent groups. For example, age grading is a hallmark of street gangs (Klein, 1995) and adolescent cliques (Schwendinger and Schwendinger, 1985). Recent changes in the social contexts of inner cities, where homicides were concentrated throughout this period, may contribute to a breakdown of traditional age-grading. Factors such as the emergence of street drug markets and dense streetcorner groups of males not in the workforce contribute to a mixing of the ages on the street. Among adolescents and young adults, competition for street status through violence contributes to a process of “status forcing” that promote cross-age interactions (Wilkinson, 1998). Using data from police reports, we analyzed the within-age distribution of homicide events for each year in the recent homicide cycle. Table 4 reports the percent of homicide offenders whose victims are within their own age group. In 1985, at the outset of the latest homicide runup, age homogeneity for gun and nongun homicides was comparable, but very low. For adolescents and young adults, about one gun homicide in four involved persons within the same age categories. For adults ages 25-34, about four in ten gun homicides were within-age killings. Once the gun homicide runup began in 1986, age homogeneity rose as homicide rates rose


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generally. For example, within-age gun homicides for young adults rose from 22.9 percent of gun homicides in 1985 to 35.8 percent in 1990; for offenders ages 25-34 years, within age group homicides rose from 38.5 percent in 1985 to 54.9 percent in 1989. Even with these increases, however, the majority of gun killings involved persons from different age groups. During the same period, within-age non-gun homicide rates varied from year to year in an inconsistent pattern. Comparing age-groups, age homogeneity for gun homicides was highest for homicide offenders 25-34 years old, and were lowest for 20-24 year olds. The low rates for the 20-24 group reflects their age status between the two other groups and the higher likelihood of cross-age interactions.

5. Contextual Effects Both popular and social science explanations of the homicide epidemic in New York and elsewhere have focused on important social trends, particularly changes in drug markets (Blumstein, 1995). Fagan et al. (1998) discuss the appeal of these explanations First, homicide and drug epidemics have been closely phased, both temporally and spatially, in New York and nationwide, for nearly 30 years (Fagan, 1990, 1997). Homicide peaks in 1972, 1979 and 1991 mirror three drug epidemics: heroin, cocaine hydrochloride (powder), and crack cocaine. These longterm trends predict that trends in drug use would occur contemporaneously with trends in homicide. Second, the emergence of volatile crack markets in 1985 is cited as one of the primary contextual factors that have driven up homicide rates in New York(Goldstein et al., 1989; Johnson et al., 1990; Bourgois, 1995). Competition between sellers, conflicts between buyers and sellers, and intra-organizational organizational conflict were all contributors to lethal violence within crack markets (Fagan and Chin, 1990; Hamid, 1994). Crack also is implicated in the decline of homicide since 1991 (Curtis, 1998). Figure 3 compares trends in gun homicides for three age groups with trends


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in drug overdose deaths. Drug overdose deaths follow a pattern of short cycles, with relatively brief periods of increase and decline. The rates increase from 1986 to 1988, decline through 1990, and increase again for three years before leveling off. The runup of gun homicide rates in 1985 to 1988 matches the increase in drug overdose deaths, but the homicides continue to increase even as drug overdose deaths decline. Drug overdose death rates increase from 1992 to 1994, even as gun homicide rates decline. Accordingly, there appears to be little mutual influence of drug overdose deaths and gun homicide trends for any of the three age groups.9 Changes in drug use patterns may explain this disjuncture, with drugs such as heroin and ketamine supplanting crack as the favored street drug (Curtis, 1998) . These drugs are more likely to cause overdose deaths. An alternative though imperfect indicator of drug market activity is drug arrests. Arrests reflect both strategic decisions by police as well as drug market characteristics. In conjunction with other indicators, arrests are a useful marker of drug trends. The trend lines in Figure 4 for age-specific homicide victimization rates and felony drug arrest rates also show little relationship between gun homicides and drug arrests. Both drug arrests and gun homicides rates increase from 1986 through 1989, but the trend lines move in different directions after that. Homicides increase through 1991 for adolescents and 1992 for young adults. Drug arrests decline from 1990 through 1993, and begin to rise again in 1994. Most of these felony drug arrests were for sale or possession with intent to sell, and most were either crack or cocaine arrests, the two drugs that were most actively traded in street markets. The portion of felony drug arrests that involved crack or cocaine rose from 57 percent in 1986 to 64 percent in 1988, and declined steadily to 48 percent in 1995. Overall, drug selling activity fails to adequately explain the runup and decline 9. Other indicators, such as drug use among arrestees recorded in the Drug Use Forecasting System (DUF), also show little relationship with trends in gun homicide rates. Fagan et al. (1998) show that the incidence of drug-positive arrestees remains unchanged throughout the period, and is unrelated to both firearm and non-firearm homicide trends.


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in gun homicides. Violence associated with drug use remained relatively infrequent during the onset of the crack crisis (Fagan and Chin, 1990; Fagan, 1992). Moreover, the share of homicides due to drug selling did not rise during the homicide runup (Goldstein et al., 1989). Drug selling accounts for an unknown proportion of homicides, with estimates ranging from about 10 percent in the FBI’s Supplemental Homicide Reports,10 to 50 percent in local studies in New York (Goldstein et al., 1989) or Los Angeles (Maxson et al., 1991). Thus, a decline in street-level drug selling activity may have reduced, to some unknown extent, the types of social interactions that lead to gun killings. But drug selling alone is unlikely to have produced the unprecedented runup or decline in gun killings so consistently across time, social groups and areas.

10. Analysis by authors, data available on request.


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Finally, demographic changes also offer weak explanations of the homicide increase or decline. The population for the highest risk groups, non-white males ages 15-29, declined by about 10 percent from 1985-95 (Fagan, Zimring and Kim, 1998), a far smaller scale of change than the change that could produce the observed declines in gun homicides. While is tempting to dismiss demography as a correlate of the homicide decline, the relationship of population to a changing behavioral pattern may be non-linear, though (Gladwell, 1996). In other words, did the population decline reach a threshold where it could lead to a decline in the incidence of gun homicides?11 This is a plausible but unfalsifiable explanation. Like the effects of declining drug markets, the contraction in the highest risk population is an important but unknowable influence on the decline in firearm homicides from 199296. In other cities, the emergence and evolution of street gangs has been linked to homicide increases. From 1980 to 1992, over 80 percent of the nation’s 250 largest cities reported new or intensified gang activity, much of it linked to drug selling. In New York, however, gangs provide a very limited explanation of the homicide trends, especially for the increase and decline in gun homicides. Street gangs of adolescents in New York City are largely a thing of the past. Contemporary street gangs are weak and disorganized structures (see, for example, Sullivan, 1989). Current gangs either are extensions of multistate prison gangs such as the Latin Kings or their rivals (Brotherton, 1998), tied to adult crime groups (see, for example, Chin, 1995, on Chinese gangs), or are drug business organizations (Fagan, 1994;

11. According to Burt (1987), the relationship of network density to social contagion is non-linear. Thus, epidemiologists discuss thresholds, or tipping points, where behavioral change accelerates and spreads through a population before beginning its process of decline (see, for example, Crane, 1991; Gladwell, 1996).


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Curtis, 1998). There are nascent gang structures in middle and secondary schools, but they have emerged only recently and well after the decline in gun homicides.

II. NEIGHBORHOOD EFFECTS ON SOCIAL CONTAGION OF YOUTH HOMICIDE We begin the task of dissagregation of “contagion effects” into dynamic processes across social aggregates. The first discussion sets out a framework for understanding the hierarchical structure of contagion, from social circumstance to individual interactions. Next, we present analyses to show the transmission of behaviors across social areas or neighborhoods. We use census tract as the boundary for “neighborhood,” based on the size (area) of tracts in New York and their isomorphism with important social units such as public housing developments and feeder school patterns.12 These analyses set the stage for the analysis in Section III of micro-social interactions where social contagion take place.

12. Tracts are commonly used to represent neighborhoods in sociological research, due to their size and robustness in predicting variation in a variety of social interactions. See, for example, Kenneth Land, Patricia McCall, and Lawrence Cohen, Structural covariates of homicide rates: Are there any invariances across time and space, 95 American Journal of Sociology 922 (1990). Most cities lack well organized data sets that are aggregated to meaningful social areas. For exceptions, see, for example, Robert J. Sampson, Stephen W. Raudenbush, & Felton Earls, “Neighborhoods and violent crime: A multilevel study of collective efficacy,” 277 SCIENCE 918 (1997), analyzing neighborhood differences in crime rates and informal social control in Chicago using tract-level data; Jonathan Crane, The epidemic theory of ghettos and neighborhood effects on dropping out and teenage childbearing. 96 American Journal of Sociology 1226-59 (1991), analyzing the spread of teenage births across Chicago census tracts.


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A. Background The spread of ideas and practices is contingent on the way in which social structure brings people together in close physical proximity within dense social networks (Burt, 1987: 1288).13 Through a process of mutual influence involving contact, communication and competition, adoption of behaviors occurs when information is transmitted that communicates the substance of the innovation and the consequences of adoption. The consequences can be econometric or intrinsically pleasurable, and may be reinforced through the benefits of a vicarious experience or a trial use. In addition, these behaviors acquire social meaning that is communicated through repeated interactions within social networks (Lessig, 1995: 947).14 Contagious epidemics involve the transmission of an agent via a host through susceptible organisms whose resilience is weakened by other conditions or factors (Bailey, 1967). Susceptibility is critical to the ability of an agent to exert its process on a host. This medical rendering of contagion can be analogized to social contagion. Thus, the fundamental social causes of disease -- primarily social structural, or ecological -- can be seen as pathways along which more micro-level causes can exert their effect (Gostin, Burris and Lazzarini, 1999: 74). According to Gostin et al., these fundamental social causes reflect inequalities that work in two ways. First, these conditions increase exposure to the more proximal causes, whether microbic or behavioral. Second, they compromise the resistance or resilience of social groups to these proximal causes. That is, their exposure and their behavior in those structural circumstances both have social roots.15

13. See, also, David C. Rowe and Joseph L. Rogers, A Social Contagion Model of Adolescent Sexual Behavior: Explaining Race Differences, 41 Social Biology 1, 16 (1994), showing that an epidemic model combining social contagion through social contacts among adolescents of within a narrow age band explains the onset and desistance of adolescent sexual behavior. 14. See, also, Dan M. Kahan, Social Influence, Social Meaning, and Deterence, 83 Virginia Law Review 349, 367-73 (1997). 15. Lawrence O. Gostin, Scott Burris, and Zita Lazzarini, The Law and the Public’s Health: A Study of Infectious Disease Law in the United States, 99 Columbia Law Review 59, 75 (1999).


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Memetics provides a complementary framework for understanding how beliefs, ideas and behaviors spread throughout society. Memes are singular ideas that evolve through a process of natural selection not unlike the evolution of genes in evolutionary biology.16 The principal law governing the birth and spread of memes is that of the “fittest ideas,” defined as those ideas that are the best at self-replication rather than those that may be truest or have the greatest utilitarian value.17 In the present analysis, violence may be the “fittest” behavior, even when it contradicts more socially useful normative values imported from the dominant society. Memes achieve high-level contagion through a variety of social interactions across social units such as families and social networks, and each mode increases the “host” population for that meme. The meme is then reproduced within networks and transmitted across interstitial network boundaries. Replicated memes become what Balkin refers to as “cultural software” that is expressed in language, behavior and normative beliefs,18 creating a set of narrative expectations, or behavioral “scripts.”19 Script theory can explain contagion in several ways: (1) scripts are ways of organizing knowledge and behavioral choices;(2) individuals learn behavioral repertoires for different situations; (3) these repertoires are stored in memory as scripts and are elicited when cues are sensed in the environment; (4) choice of scripts varies between individuals and some individuals will have limited choices; (5) individuals are more likely to repeat scripted behaviors when the previous experience 16. Aaron Lynch, Thought Contagion: How Beliefs Spread Throughout Society (1996); Jonathan Balkin, Cultural Software (1998). 17. Lynch, id __. 18. Balkin at 42-57. 19. Jeffrey Fagan, Context and Culpability in Adolescent Violence, 6 Virginia Review of Social Policy and Law 101 (1999). The script framework is an event schema used to organize information about how people learn to understand and enact commonplace behavioral patterns. A “script” is a cognitive structure or framework that organizes a person’s understanding of typical situations, allowing the person to have expectations and to make conclusions about the potential result of a set of events Robert P. Abelson, “Script processing in attitude formation and decisionmaking,” In Cognition and Social Behavior (J.S. Carroll and J. W. Payne, eds.) (1976); Robert P. Abelson, “Psychological status of the script concept,” 36 American Psychologist 715 (1981).


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was considered successful;and (6) scripted behavior may become “automatic” without much thought or weighing of consequences.20 Accordingly, social contagion is convergence of transmission of behaviors and beliefs that motivate or sustain them. Social contagion arises from people in proximate social structures using one another to manage uncertainty of behavior.21 It requires an interaction where information, behavioral innovation, belief, or meme, is transmitted across a social synapse. At its core, contagion occurs when two people interact where one has adopted a construct and the other has not.

Contact,

communication or imitation, are influential processes that make transmission possible.22

Synapses themselves are situated within social networks, and the

adoption of innovation or a meme triggers the adoption by another person. Burt (1987) suggests that adoption has less to do with the cohesion of people within social structures, or networks, and more to do with the structural equivalence – the social homogeneity – of the network. That is, transmission is more likely to occur between similarly situated persons – siblings, fellow graduate students, streetcorner boys – than persons simply because they are closely bonded.23 Within structurally equivalent networks, similarly situated people are likely to influence or adopt behaviors from one another that can make that person more attractive as a source of further relations. The importance of structural equivalence – or placement within a socially homogeneous interpersonal network – is that it fosters interconnected patterns of relationships that makes contagion efficient. In the remainder of this section, we show how transmission of violence occurs across neighborhoods whose social structures of densely packed networks are 20. Abelson, supra n. 19 21. Burt, at 1288. Thus, the diffusion of innovation takes place in a parallel structural context as does the diffusion of drug trends or sexual behavior. See, Rowe and Rogers, supra n. __; Lawrence Gostin, The Interconnected Epidemics of Drug Dependency and AIDS, 26 Harvard C.L.-C.R. Law Review, 113, 125 (1991). 22. Burt, id at 1288-89.


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vulnerable to rapid contagion. In the next section, we show how the memes of toughness and the valued status from violence are the object of transmission and exchange. The implications for a social influence model of contagion are discussed in the concluding section.

B. Susceptibility: Neighborhood Risk We draw on the literature of neighborhoods and violence to construct a framework of structural risk that simultaneously compromises resilience against transmission while increasing susceptibility. Both theory and empirical research suggest that neighborhoods are susceptible to the spread of violence when structurally weakened (Taylor and Covington, 1988; Patterson, 1991; Massey, 1995).24 Wilson (1987) argues that there has been both an economic and a social transformation of the inner city, where the exodus of manufacturing jobs beginning in the 1970's has changed the social and economic composition of inner cities, leading to a concentration of resource deprivation. Wilson (Wilson, 1987: 58) goes on to suggest that the concentration of resource deprivation in specific areas led to dynamic changes in the processes of socialization and social control in those areas. As middle- and working class African American families moved away from the inner cities when their jobs left, there remained behind a disproportionate concentration of the most disadvantaged segments of the urban populations: poor female-headed households with children and chronically unemployed males with low job skills. The secondary effects of this exodus created conditions that were conducive to rising teenage violence: the weakness of mediating social institutions (e.g., churches, schools), and the absence 23. Id at 1291. 24. For example, recent studies suggest that violence shares several explanatory variables with concentrated poverty (Wilson, 1987, 1991; Sampson and Lauritsen, 1994) or resource deprivation (e.g., Williams and Flewelling, 1988; Land et al., 1990). These constructs describe the lack of sufficient means, including income poverty and inequality, to sustain informal social control


20

of informal social controls to supervise and mentor youths.25 Wilson (1987) refers to these conditions of weak social control as social isolation. The concept of social isolation suggests an ecological dynamic where the components of poverty and structural disadvantage are interconnected with the dynamics of social control and opportunity structures. The decline of manufacturing jobs increased unemployment among adult males, primarily African Americans, whose job skills limited them to unskilled labor. Other economic transformations, including the rise of service and technical jobs outside central cities, motivated the exodus of middle-class families to the outer rings and suburbs surrounding the inner cities. Remaining within the abandoned central cities were unskilled males whose "marriage capital" was low, giving rise to an increasing divorce rate and declining marriage rate. Changes in the composition of central city neighborhoods also weakened the social institutions that were critical to the informal social control and collective supervision of youths. The weakening of social controls had their strongest effects in transactional settings of neighborhoods and in places like schools and

(Sampson and Wilson, 1995). 25. The male divorce rate also is a consistent predictor of violence and homicide rates, and effects are greater for juveniles than for adults. For example, Messner and Sampson (1991) showed that Black family disruption was substantially related to rates of murder and robbery involving Blacks. These findings are consistent with the consistent findings in the delinquency literature on the effects of broken homes on social control and guardianship. The effects of male divorce can be interpreted either as a consequence and correlate of the rise of female-headed households, or as an indicator of weak social control of children who then are raised primarily by women. Whatever its meaning, the male divorce rate has positive, clear cut effects on robbery, assault, rape and homicide (Sampson and Lauritsen, 1994).


21

church where adolescent development takes place. And, the exodus of middle class families from inner cities weakened the political strength of the remaining families, leading to physical deterioration (Wallace, 1991), lower housing values and in turn increased residential (spatial) segregation (Massey and Denton, 1993). In turn, the social isolation of people and families was extended to institutions. The rise in poverty and weak social institutions also undermined the presence of and institutional support for conventional behaviors. As a result, conventional values and behaviors were attenuated because they were not salient and had little payoff for one's survival or status (Elliott et al., 1996; Wilson, 1987). These dynamics in turn attenuated neighborhood social organization, increasing the likelihood that illegitimate opportunity structures would emerge: illegal economies including drug distribution or extortion, gangs, and social networks to support them. These structures competed with declining legal work opportunities both as income sources and as sources for social status. As these networks flourished, the systems of peer and deviant social control replaced the controls of social institutions and conventional peer networks (Fagan, 1992). Accordingly, structural change that violence and homicide are more likely to occur in an ecological context of weak social control, poorly supervised adolescent networks, widespread perceptions of danger and the demand for lethal weapons, and the attenuation of outlets to resolve disputes without violence. It is in this ecology of danger that violence becomes transmittable through weapons and their impact on perception and decision making in social interactions.

C. Guns and Social Contagion In these social contexts, several processes contributed to the epidemic of lethal violence. The growth in illegal markets heightens the demand for guns as basic tools associated with routine business activity in illegal markets (Johnson et al., 1990; Blumstein, 1995). In turn, the increased presence of weapons and their diffusion into


22

the general population in turn changes normative perceptions of the danger and lethality associated with everyday interpersonal disputes, giving rise to an "ecology of danger" (Fagan and Wilkinson, 1998). Thus, we hypothesize that guns were initially an exogenous factor in launching an epidemic of gun homicide, but became endogenous to socially isolated neighborhoods and came to dominate social interactions (Wilkinson and Fagan, 1996). Everyday disputes, whether personal insults or retributional violence, in turn are more likely to be settled with lethal violence (Fagan and Wilkinson, 1998). Whether viewed in social, medical or memetic frameworks, guns can be constructed as a primary agent of violence contagion over the most recent epidemic cycle.

Guns are a form of social toxin (Delgado, 1985) in everyday social

interactions, altering the outcome of disputes and changing the developmental trajectories of young males whose adolescent development took place in contexts of high rates of gun use (Fagan, 1999).26 The development of an ecology of danger reflects the confluence and interaction of several sources of contagion. First is the contagion of fear. Weapons serve as an environmental cue that in turn may increase aggressiveness (Slaby and Roedell, 1982). Adolescents presume that their counterparts are armed, and if not, could easily become armed. They also assume that other adolescents are willing to use guns, often at a low threshold of provocation. Second is the contagion of gun behaviors themselves. The use of guns has instrumental value that is communicated through urban “myths,” but also through the incorporation of gun violence into the social discourse of everyday life among preadolescents and adolescents. Guns are widely available and frequently displayed. They are salient symbols of power and status, and strategic means of gaining status, 26. Jeffrey Fagan, Context and Culpability in Adolescent Violence, Virginia Review of Social Policy and Law (in press).


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domination, or material goods. Third is the contagion of violent identities, and the eclipsing or devaluation of other identities in increasingly socially isolated neighborhoods. These identities reinforce the dominance hierarchy built on “toughness” and violence, and its salience devalues other identities. Those unwilling to adopt at least some dimensions of this identity are vulnerable to physical attack. Accordingly, violent identities are not simply affective styles and social choices, but strategic necessities to navigate through everyday dangers.27 The social meanings of violent events reach a broader audience than those immediately present in a situation. Each violent event or potentially violent interaction provides a lesson for the participants, first-hand observers, vicarious observers, and others influenced by the communication of stories about the situation which may follow.

D. Analytic Models: Diffusion and Contagion We estimated models of contagion of gun violence and its diffusion across New York City neighborhoods beginning in 1985. We tested two distinct conceptual models for the spread of gun violence from one neighborhood to the next. An outward contagion model posits that adolescent homicide spreads out from a central census tract (T) or the immediate neighborhood, to adjacent census tracts (X, Y and Z) or the surrounding community. In this model, the incidence and prevalence of adolescent homicide in a given neighborhood exerts a significant influence over the incidence and prevalence of adolescent homicide rates in the adjacent community. 27. One important development is a breakdown in the age grading of behaviors, where traditional segmentation of younger adolescents from older ones, and behavioral transitions from one developmental stage to the next, are short-circuited by the strategic presence of weapons. Mixed age interactions play an important role in this process. Older adolescents and young adults provide modeling influences as well as more direct effects. We found that they exert downward pressure on others their own age and younger through identity challenges which, in part, shape the social identities for both parties. At younger ages, boys are pushing upward for status by challenging boys a few years older. See, Deanna Wilkinson, The Social and Symbolic Construction of Violent Events among Inner City Adolescents (Doctoral dissertation, Rutgers University) (1988).


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This influence is hypothesized to operate in at least two different ways. First, a threshold effect is expected concerning adolescent homicide counts, such that the presence of at least one adolescent homicide in a given neighborhood will substantially increase the probability of experiencing at least on adolescent homicide in the surrounding community. Second, with respect to adolescent homicide rates, positive covariation is anticipated whereby increases or decreases in the adolescent homicide rates in a neighborhood are reflected in concomitant increases or decreases in the surrounding community’s adolescent homicide rate. It is also possible that the contagion effect of adolescent homicides is, in fact, reversed. Accordingly, the inward contagion model asserts that the adolescent homicide level in an immediate neighborhood is at least partially contingent upon the level of adolescent homicides in its broader community. Again, the two distinct relationship forms (threshold effect and positive covariation) are possible.

By

considering the simultaneous influence of adjacent spaces, we address the problem of spatial autocorrelation by effectively controlling for mutual influences within and over time. In addition to corresponding adolescent homicide rates, both the outward and inward contagion models incorporate relevant structural and demographic features of neighborhoods and communities as key explanatory constructs. Thus, for the full outward contagion model, the presence and rate of adolescent homicide in the surrounding community is function of the relevant characteristics of the community as well as the presence or rate of adolescent homicide in the neighborhood. In contrast, the full inward contagion model suggests that both relevant neighborhood features and the presence or rate of adolescent homicide in the community predict the presence or rate of adolescent homicide in the neighborhood. Although these factors are presumed to play a significant, independent role in the prediction of adolescent homicide rates, it is nonetheless hypothesized that effects of homicide rates as dependent variables will remain substantial even once controls for relevant


25

neighborhood and community characteristics have been introduced. Models were estimated using mixed effects regression models (Singer, 1999). Mixed effects regression models approximate multilevel models where data are hierarchically organized. For example, this class of models is useful in cases such as estimating the simultaneous effects of school climate and individual student family background on standardized test scores, or neighborhood characteristics and household composition on crime rates.28 In these examples, we might specify the ecological effects of school or neighborhood as fixed effects and individual household or family influences as random effects. This specification approximates the presumed hierarchy of influences. One may reverse the specification, as well, comparing estimates to assess reciprocal effects between the two sets of predictors. Mixed effects models simulate the hierarchy of effects by estimating the differences in error-covariance matrix structures for each set of effects (Singer, 1999: 3).29

28. Mixed effects models also are useful in estimating individual growth curves, or within-subject change over time. See, for example, Anthony Bryk and Stephen Raudenbusch, Hierarchical Linear Models (1992), T.A.B. Snijders and R.J. Bosker, Modeled Variance in Two-Level Models, 22 Sociological Methods and Research 342 (1994). 29. A second advantage of the mixed models approach is that it allows for greater flexibility in specifying the covariance structure of the data. Specifically, mixed models allow for the analysis of data where the requisite assumptions of OLS regression concerning error term independence are violated. This is particularly important in research involving aggregate units. Because the neighborhoods and communities are comprised of geographically contiguous census tracts, autocorrelation is inherent in the data structure and it would be inappropriate to assume a simple covariance structure for these analyses. All of the models are instead analyzed with an autoregressive covariance structure.


26

In this analysis, the contagion models specifies the characteristics of the “sending” neighborhood as fixed effects, and characteristics of the adjacent neighborhood as random effects. To estimate contagion effects on prevalence, we use the logistic form of the equation. To estimate changes in rates, we use the linear regression form of the equation. To estimate changes over time, we use a repeated measures design where year is included as a random effect that approximates a developmental growth curve (see, Goldstein, 1995).

E. Data Dependent Variables. There are four dependent variables, two for each of the contagion models. In the outward contagion model, the first dependent variable is a dichotomous indicator of whether or not at least a single adolescent homicide had occurred in at least one of the census tracts that comprise the surrounding community. This will allow for the testing of a threshold effect hypothesis. The second dependent variable is the aggregate adolescent homicide rate for the surrounding community and is directly related to a positive covariance hypothesis. The dependent variables for the inward contagion model are: (1) a dichotomous indicator noting whether at least a single adolescent homicide had occurred in the neighborhood, and (2) the adolescent homicide rate for the neighborhood. Again, these dependent variables are used to address the threshold effect and positive covariance propositions respectively. Independent Variables. In addition to the variables based on adolescent homicide rates for each neighborhood by year, we operationalized the model of neighborhood risk or susceptibility described earlier. Data reflecting the structural and demographic composition of neighborhoods and communities are predictors the contagion models. Following Land et al. (1990), we selected 14 tract-level variables from the 1990 Census (STF3A and 3B files) to characterize social areas. Means and variances


27

for the 14 initial variables are presented in Appendix B. Principle components analysis was used to eliminate autocorrelation among the 14 variables, and identify three orthogonal and conceptually distinct factors. The results in Table 5 show that neighborhoods and communities are characterized along three dimensions: deprivation, population characteristics, and social control. Because communities are actually composites of census tracts, their factor scores are actually weighted factor score composites.30 Lag Effects. The “contagion effect” of adolescent homicide is not expected to be immediate. Rather, it is more reasonable to assume that some period of time must elapse between the occurrence of an adolescent homicide (threshold effect) or change in the adolescent homicide rate (positive covariation) and the realization of a related occurrence or rate change. For this study, the time elapsed is estimated to be one year.31 Thus, all the of models have been run with data lagged at one-year intervals. For example, with the outward contagion model, the adolescent homicide rate in a neighborhood for 1990 is used to predict the rate in the surrounding community for 1991. Conversely, the adolescent rate for a neighborhood in 1993 under the inward contagion model is estimated using the community adolescent homicide rate from 1992.

F. Results 1. Epidemic Effects: Neighborhood Trajectories. Table 6 simply shows the prediction of homicide rates over time from the three neighborhood factors in each census tract. Recall from Figures 1 and 2 that the distribution of homicides over time is curvilinear, reflecting the epidemic pattern. Accordingly, we applied

30. The weighting variable was 1990 population. 31. It is worth noting that models with two year time lags produced results very similar to those reported here. Thus the results as reported to not appear to be an artifact of the lag time chosen.


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individual growth curve models to neighborhoods to estimate models for change over time by neighborhood. Table 6 shows the estimation of a growth curve model with covariates. We assume neighborhood structure is fixed at its 1990 status, midpoint in the time period.32 The results show that homicides were concentrated in the city’s poorest neighborhoods over time. The effects of neighborhood factors on the likelihood of experiencing an adolescent homicide in that area consistently significant, but vary greatly in their magnitude. Repeated measures logistics regression shows that homicide rates were highest over time in neighborhoods characterized by economic deprivation (poverty) and population risk factors. Anonymity and social control are not significant predictors of homicide trends over time. 2.

Reciprocal Contagion Effects.

We next estimated models of the

reciprocal effects of homicides between neighborhoods. Table 7 shows the results of both repeated logistic regression and repeated standard (least squares) regressions to estimate the spread of homicide over time from one neighborhood to the next. Models 1 estimates the spread of homicide from a neighborhood to the adjacent neighborhoods without covariates; Model 2 adjusts these estimates for the effects of covariates of the source neighborhood. Model 3 estimates the inward spread from surrounding areas to a surrounded neighborhood, and Model 4 adjusts these estimates for the effects of covariates of the target neighborhood. Together, the significant coefficients in both parts of Table 7 suggest reciprocal contagion effects. That is, adolescent homicide is characterized by both outward and inward contagion processes. In the upper half of Table 7, results of all four models show that the presence of at least one adolescent homicide in a census tract significantly increases the likelihood of at least one adolescent homicide 32. We estimate models with covariates where both slopes and intercepts vary, and residual observations within census tracts are correlated through the within-tract error-covariance matrix.


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occurring in the surrounding neighborhood. The introduction of neighborhood characteristics reduces the effect size for both inward and outward contagion, but the contagion effect remains significant even when controlling for relevant neighborhood characteristics. The lower half of Table 7 shows a similar pattern of results for models of changes in the rates of homicide. 3. Guns and Social Contagion of Homicide. To assess the effects of guns on social contagion, we next estimated models that separated the contagious effects of gun homicides from non-gun homicides. Models of outward contagion of gun homicides are shown in Tables 8 and 9. Model 1 estimates the effects of gun homicides in one neighborhood on gun homicides in a surrounding neighborhood; Model 2 adjusts these estimates for the effects of the covariates of the source neighborhood. Models 3 and 4 repeat these procedures to estimate the contagious effects of gun homicides on non-gun homicides. The upper half shows results for changes in homicide prevalence, and the lower half shows results for changes homicide rates. Tables 8 and 9 both show that the contagious effects of gun homicides in one area are limited to gun homicides in adjacent areas. Table 8, Model 1 shows that gun homicides are contagious, both for prevalence and increases in rates. Although neighborhood characteristics diminish the effect sizes, Model 2 shows that the results remain the same. The presence of gun homicides in one neighborhood significantly increases the likelihood of a gun homicide in any of the surrounding neighborhoods in the subsequent year, after independent of neighborhood characteristics. Once again, a similar results were obtained for changes in the homicide rate. No such effect was found for the effects of gun homicides on non-gun homicides. Models 3 shows evidence of contagion, but Model 4 shows that the effect is not statistically significant when the model is adjusted for neighborhood covariates. And once again, a similar pattern of results is evident for changes in the homicide rate.


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Table 9 repeats this analysis for inward contagion: the spread of homicides from surrounding neighborhoods to a central neighborhood. The same pattern of effects was observed: gun homicides were contagious only to produce other gun homicides, after controlling for neighborhood characteristics; gun homicides had no such effects on the prevalence or rates of non-gun homicides in the surrounding areas. Tables 10 and 11 reverses this analysis, estimating the contagious effects of non-gun homicides on gun and non-gun homicides. The models in Table 10 show no outward contagious effects of non-gun homicides on either gun or non-gun homicides. Table 11 shows one significant effect: inward contagion of non-gun homicide rates.

Non-gun homicide rates predicted higher non-gun rates in

surrounded neighborhoods, after controlling for neighborhood characteristics. However, the relatively high proportion of gun to non-gun homicides throughout this period raises the possibility that estimates of non-gun contagion might be unstable. We addressed this by re-estimating the models in Tables 10 and 11, but including total homicide as the predicted measure. The results in Tables 12 and 13 confirm the earlier pattern for gun homicides: gun homicides show effects of both outward and inward contagion, for both prevalence and rates, after controlling for neighborhood characteristics. Non-gun homicides appear to have contagious effects on total homicides, but only in models of inward contagion. There is no outward contagion effect of non-gun homicides on total (gun and non-gun) homicides.

G. Summary The contrast in findings of non-gun contagion for non-gun versus total homicide illustrates the importance of guns in the dynamics of social contagion at the population level. In addition, the consistent finding of socio-economic risk as a contributor to the spread of violence captures both the significance of susceptibility


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and the importance of structural equivalence in shaping the trajectory of diffusion. That is, the adoption at the population level of gun violence was facilitated by the social concentration of poverty, and of the close social synapses intrinsic to poor neighborhoods. Accordingly, the social and spatial clustering of homicide suggests that it is concentrated within overlapping social networks in small areas (Fagan and Wilkinson, 1998). Social contagion theory suggests that individuals are likely to mutually influence the behaviors of others with whom they are in frequent and redundant contact (Burt, 1987; Bovasso, 1996, at 1421). The social interactions underlying assaultive violence suggest its spread by social contact (Loftin, 1986). Moreover, the dissolution of social networks from attrition -- death, incarceration, or declining birth rates -- would reduce opportunities for social transmission. We explore these themes in the next section.

III. SOCIAL IDENTITY, YOUTH VIOLENCE, AND SOCIAL CONTAGION We turn next to an analysis of the individual- and group-level processes of social contagion. We identify dynamic social processes that fuel the social contagion of youth violence.

At the heart of this process is the development and

communication of social identities among males. Violence plays a central role in the formation and maintenance of social identities among adolescents in inner city neighborhoods, where structural conditions often make other social identities unavailable. The contagious element in the epidemic of youth violence is the process of making, maintaining and exchanging status through the use of violence. The strategic value of guns in this process intensifies the dynamics that fuels the epidemic. Thus, the presence of guns in events where there is “status forcing” or exchanges of identities links together persons and events across time, and sustains


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the processes of social contagion. We begin the discussion by examining the role of identity in adolescent development, and decomposing identity into several components. Then, we review specific social identities, and show how identities are linked across persons to provide a motivational context for violence. Next, we describe the process of “status forcing” and its role in fueling identity-based violence. The importance of guns is evident in these interactions.

A. Youth Violence and Social Identity Issues of respect, honor, and pride are repeatedly described as central features of male identity formation beginning in early adolescence.33 “Toughness” also has been central to the development and maintenance adolescent masculine identity in many social contexts of American life. Physical prowess, emotional detachment, and the willingness to resort to violence to resolve interpersonal conflicts are hallmarks of adolescent masculinity. While these terms have been invoked recently to explain high rates of interpersonal violence among nonwhites in central cities, “toughness” has always been highly regarded and a source of considerable status among adolescents in a wide range of adolescent subcultures, from street corner groups to gangs.34

While changing over time with tastes, these efforts at “impression

33. See, for example, Messerschmidt, 1993; Anderson, 1994; Sullivan, 1989; Majors and Billson, 1992; Oliver, 1994; Luckenbill and Doyle, 1989; Toch, 1969; Horowitz and Schwartz, 1974; Nisbett and Cohen, 1996; Connell, 1995; Canada, 1995. 34. Whyte, 1943; Goffman, 1959; 1963; 1967; Wolfgang and Ferracuti, 1982; Canada, 1995;


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management” through violence have been evident across ethnicities and cultures (Katz, 1988).35 Violence often is used to perpetuate and refine the pursuit of “toughness,” and to claim the identity of being among the toughest.

Hagedorn, 1997. 35. In some cases, displays of toughness are aesthetic: facial expression, symbols and clothing, physical posture and gestures, car styles, graffiti, and unique speech are all part of “street style” that may or may not be complemented by physical aggression. The ‘tough’ status requires young males to move beyond symbolic representation to physical violence


34

The process of self-preservation through displays of toughness, nerve, or violent behavior is necessary part of day to day life for inner-city adolescents, especially young males.36 Acquiring fighting skills (and perhaps more importantly shooting experience) is considered important as a means of survival in the inner city. The status and reputations earned through violent means provide inner city adolescent males with positive feelings of self worth and “large” identities especially when other opportunities for identity development are not available (Messerschmidt, 1993; Hagedorn, 1997). Those individuals who have prestigious identities are granted respect while the stigmatized face attacks on self.37 Group formation crystalizes one’s personal and social identity.38 Social identity often shapes the extent to which violence occurs.39 Social identity has a particularly strong influence because “individuals have little control over situations and especially going outside of the expected role for their particular social identity” (Goffman, 1963: 128). Strauss (1996: 57) explained that “face-toface interaction is a fluid, moving, running process; during its course the participants take successive stances vis-a-vis each other. ...The initial reading of the other’s identity merely sets the stage for action, gives each some cues for his lines.”

In addition, Strauss po

who are tough, who have gained respect by proving their toughness, and who reenact 36. See, Fagan and Wilkinson, 1998, and Sullivan, 1989:113. 37. The concept of respect or honor refers to granting deferential treatment to what Goffman called one’s “personal space.” One who grants another respect would acknowledge and esteem the other’s individuality and personal space (or least not attack it). The adolescent male is looking to others to reflect back (“looking glass self” phenomenon) aspects of his own self-image which is constantly shaped and reshaped within the context of social interaction with others. 38. Many of the vital functions of adolescent social life operate through these groupings whether they are loosely or tightly connected (e.g. social learning and mentoring, play, nurturing, social support, and economic opportunity). Researchers have described the dynamic nature of social identity during different periods of adolescent development. Kinney (1993) for example, found that “identity recovery” was possible through increased opportunity and diversity of peer groups. These school-based studies show that the school setting offers a myriad of opportunities and constraints to identity development. The street, as a social context, offers a similar opportunity for adolescent identity formation, trials, and maintenance. For specific examples, see: Goffman, 1963; Schwendinger and Schwendinger, 1985; Eder, 1995; Kinney, 1993.


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their appropriate role in public.

B. Status Forcing and the Communication of Social Identity Social identity may be built, earned, applied, or assigned (Strauss, 1996: 145). During the course of social interaction, individuals “may force each other into such statuses” (79). Status forcing has different consequences for the identity of actors depending upon the duration and permanence of that status. Strauss argued “it makes a difference whether the placement is temporary (banishment), permanent (exile), or of uncertain duration (idolization)” (Strauss, 1996: 83). He argued that some forced statuses were “reversible” and therefore would have less long term impact on identities. In this section, we analyze narrative reconstructions of violent events reported by 125 adolescents and young men from two inner-city neighborhoods in New York (Fagan and Wilkinson, 1998). The events have been classified as erupting out of some type of challenge or test to one’s social identity or status. Three distinctive types of challenges to identity were described: personal, material, and social. Personal attacks challenge who a person has a right to be (projected self-image), material affronts contest what possessions a person has a right to have, and finally, relational assaults who a person has a right to be in relationship with. The initial interaction sparking many of these events involved some type of insult, degradation, violent threat, bump, slight, ice grill (hard stares), domination, cunning, or unprovoked physical attack. These violent event accounts for 66.5% of all of the events described by respondents.

The parameters of a character contest are

determined by social interactions among actors of differing status (“mixed interactions”) in specific contexts. We describe different types of situational identities that our respondents

39. Supra, n. 16 and supra, n. 18.


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reported, how those identities were won and lost, and how young men compete for desirable identities. The analysis explores what appears to be a hierarchy of social identities with regard to violent behavior. Young inner-city residents must learn to negotiate the street world by building a social identity, projecting a reputation, and developing a protective peer group in the neighborhood. The process of finding a niche and forming a “safe” identity typically includes engaging in violent behavior. The data also suggest that guns play a significant role in forming and sustaining “positive” social identities within the neighborhoods.

1. Socialization and Identity The social construction of male identity in the context of the street world follows specific age-graded tracks. Violence plays a central role in “defining” social identities during different age periods in the inner-city street context. Development, age specific expectations, and ritualized “rites of passage” add legitimacy to gaining and withholding respect through violent means. Violence appears to be a resource for passage from one status or identity to another. Making a powerful social identity is a critical tool for survival in the inner-city context. The socialization process into this dynamic is quite clear according to our respondents. At an early age, males frequently experience violent attacks and must learn “how it was in the street.” One respondent reported: “Alright say your small, probably let people pick on you and stuff like that, just let them do what they want but as you get older you start fighting back. You stop letting people take advantage of you.” (SBN35). Developing a desirable social identity for the street appears to become important for males beginning between the ages of seven and eleven. Defining one’s status in comparison to others involves a number of staged plateaus or scheduled. According to several respondents (SBN27) “everybody’s a herb when they’re --- in the beginning, everybody. ...Everybody I know who’s keeping it real [being honest] has gotten fucked up so bad that they just don’t wanna get fucked up


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no more. So that’s why they act the way they act.” Two themes emerged in this analysis: (1) individuals start status-deprived and (2) establishing status requires public performance. The process was described as a kind of “who’s who” of the street by our sample, in essence a way of identifying potential threats and resources within neighborhood associations. Participation in violent social interactions, provides young men with information about the abilities and potential of others with whom they share social space and time. This public performance allow others to classify and categorize males in terms of threat, power, “heart,” and status. Peer groups play a significant role in defining social identities. Belonging to a clique or street corner group may fulfill a variety of needs for the young men including: protection, income generation, adventure, companionship, love, identity affirmation, partying, and drug/alcohol consumption in a social atmosphere. The social network, among other contexts, enables hegemonic masculine views to take shape. Groups also take on social identity and group affiliation brings with it privileges and obligations. According to our sample, criminals and males who exhibit tough qualities and behavior are the “populars” and get the most attention from others. The pressure among peers to “be part of the scene” or to “prove that you are capable of using violence to fit in” to the street life was very great. Group influence seemed especially important in establishing one’s identity. One respondent (ENYN17) described how peers made assumptions about him based upon the type of household he lived in. His belief that others felt that “shit was sweet in a private house” made him feel like an outsider. Boys from the projects intensified this distinction by teasing and threatening the respondent. The respondent had to prove he was “status worthy” and did so by being the first kid on the block with a gun. The gun was used strategically to demonstrate the respondent’s capacity for violence. Identity challenges occurred when the status of others was unknown or when


38

the situation calls for definition and classification. Shows of disrespect or “dissing” are often defined by young males as an intentional attack or attempt to downgrade someone else’s identity. These challenges were addressed aggressively. All parties in this type of interaction defined the situation from their reference point which included the collective meanings attached to the action. This identity negotiation or testing process is clearly central to the making, remaking, and breaking of identities. Respondents described the testing process as a necessary part of social development which “made me stronger” and “to this day nobody can’t do that shit to me.”

C. A Hierarchy of Social Identities In this context, identities based on violence were conflated with social status. Gun use was an important part of the status hierarchy. Three broad types of social identities were described by the respondents: being “crazy/wild” (frequent unstable fighter/shooter), “holding your own” (functional fighter/shooter), and being a punk or herb (frequent victim struggling for survival).40 Social identities become more salient through repeated performance. The social meanings attached to each performance determines when and how an actor will be known to others in the neighborhood context, and in turn, subsequent interactions will be defined. Thus an individual’s social identity can both prevent violence from coming (he won’t get picked on) and promote additional violence (other young men will attempt to knock him off his elevated status). The individual who performs poorly becomes known and labeled as being a “punk” or “herb.” The person who has a

40. The three types of social identities described in this paper were most prominent among this sample. Most of the interactions were defined in terms of avoiding being classified as a punk or herb. Respondents did describe other violence-related social identities including: “the avoider” “the nice guy” “the beef handler,” “too cool” for violence, etc.


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“successful” performance gains status and becomes known for “holding his own.” The young man who gives an “extraordinary” performance is labeled as being “wild” or “crazy.” These social identities may be temporary or permanent. This section briefly describes the characteristics of three ideal identity types. The majority of respondents would classify themselves as being someone who “holds his own” at the time of the interview. A small number would be described as fitting into the “crazy,” “wild” or “killer” identity at the time of the interview.

Few, if any, of the

respondents would classify themselves as a punk or herb during the period of the interview. Looking back over their life histories however, most respondents, 78% of those queried (71 of 96 respondents), reported experiencing one or more situations during childhood or adolescence of feeling like a punk or herb as direct result of violence perpetrated against them by older more powerful males. All of the 125 respondents described the importance of using violence to gain social status and personal security.

1. Being Known as “Crazy” “Wild” or “Killer” At the top of the identity hierarchy of the street is the “crazy” “wild” or “killer” social identity. Individuals who perform extraordinary acts of violence are frequently feared and granted a level of respect that others cannot easily attain. A small number of respondents in our sample described themselves or others as being “wild,” “crazy,” or a “killer.” Some took on this identity temporarily or situationally while others described themselves as always that way. The performances are often socially defined as shocking or judged to be beyond what was necessary to handle a situation. Once an individual gives an extraordinary performance he may notice changes in the way others relate to him. He may also start viewing himself differently. This status brings with it a certain level of power and personal fulfillment that may be reinforced by projecting this identity. Future violent


40

performances would enable him to maintain the image of the most violent or toughest on the street. A person who has an identity as someone who is crazy, wild or a killer, gives off the impression that he has extreme heart, is untouchable, and does not care about what happens. He has the capability to use extreme violence and gets respect for dominating others. Others may want to associate with him to benefit from his high status on the street. The identity itself carries privileges, expectations, and obligations which may open the individual to additional opportunities for violence. The powerful identity may be forced downward by someone else’s extraordinary performance.

2. Being Known as “Holding Your Own” Many respondents described the process of “holding their own” in violent situations and how personal identities formed around displays of “doing what you got to do” are generally positive on the street. The majority of our respondents would be classified as “holding their own.” Individuals who “hold their own” are respected on the street although they will eventually face challenges to their ability to do “what it takes” in heated situations and in all likelihood faced numerous challenges on the way up to that status (Strauss, 1996: 90). A person who has an identity as someone who holds his own, gives off the impression that he has the capability to use extreme violence but does so only when necessary. This person will face a challenge directly and is respected for that position. This identity allows an individual to be considered an “insider” with the street world, however, this status can be unstable and may require acts of violence when faced with public attacks on identity. A person who ‘holds his own’ has used violence as a resource for obtaining that status. These young men face the same type of testing process as the punk or herb however it is expected that this class of men will handle their conflicts with violence and it will be effective. If violence was not effective, someone who is


41

known to “hold his own” will be granted respect for putting up a good fight or taking a bullet “like a man.” If this character is situationally “punked” or “herbed” by someone with a lower status, his identity could face a downward slide.

3. Being Known as a “Punk” or a “Herb” At the bottom of the status hierarchy of the street is the punk or herb. Like, the school-based “nerd” or “dweeb” the “punk” or “herb” identity is assigned to those who do not fit into the deemed high status or tough identities. In the inner-city, those who cannot fight or prove of their toughness may be instead stigmatized either temporarily or permanently. Other guys in the neighborhood will act upon that stigma.

The process of punking or herbing someone, as respondents called it,

closely resembled the process of ‘fool-making’ described by Klapp (cited in Strauss, 1996). If someone has the punk or herb identity he is considered “fair game” for attacks and robberies. The attacks are motivated both by the need to restate the dominance hierarchy and as a sort of punishment for not living up to group norms. If a young man does not have a tough identity or at least have close associates or relatives who can protect him either by association or literally, he is a punk. Others in the setting degrade, dominate, and victimize those individuals who have punk or herb characteristics.

The degradation typically involves a direct or implicit

emasculation of the “weaker” males. Punks and herbs are also called “soft” “suckers” “wimps” “pussy” “bitch” “ass” and “chumps.” Given the intensified acceptance of hegemonic masculinity in the inner city context, these messages would have a strong negative impact on a punk or herb’s self-image. Most young men assume that “outsiders” in the neighborhood (and relevant social network) are punks or herbs and the presumed punk or herb must prove otherwise.


42

C. Status Forcing and Situational Identities Negotiating the street requires tests of character, knowledge of the rules of respect, knowledge of the players on the street, and open displays of violence. Since the social identities of actors in the setting are ever changing the testing process appears to be continuous until at least age twenty. The “mixed contacts” between young males of differing social standing provides the clearest context for observing status forcing --thus seeing identity on the way up, the way down, and holding steady. For example those who are attempting to transcend a punk or herb identity must interact with those who “hold their own” or typed as “killers” in order to avail an opportunity for “identity recovery” (see Kinney, 1993). Punks and herbs take all sort of abuse in our inner-city neighborhoods. They get used by more powerful street guys to test their nerve. A young male who “holds his own” may face threats from punks who are attempting to transcend into a higher social identity. The identity shift is also publicly constructed through the reinforcement and praise by those observing and/or hearing about the performance. Observers and others within the neighborhood context offer rewards in the currency of respect for these performances. Violent behavior motivated by other issues may also have side benefits for social identity especially among members of the peer group. Gun use may involve “crossing a line”or giving what an extraordinary performance that shifts one’s view of oneself from a “punk” or even “cool/holding your own” to “crazy” or “wild.” Guns were used by many as a resource for improving performance. The abundance of guns in these neighborhoods increased the severity of violent performances. For the majority of our sample, guns became relevant for conflict resolution around the age of fourteen. The process of identity formation, loss and recovery creates a dynamic of status forcing. Violence is conflated with manhood, and manhood with status and identity. The result is a constant churning of a finite reservoir of status that produces violent events, many


43

involving guns.

D. The Micro-Processes of Social Contagion The dynamics of violent events reflect several processes that illustrate the spread of violence within social structures that exert a contracting influence on social networks of adolescents: (1) achieving a highly valued social identity occurs through extreme displays of violence, (2) achieving a “safe” social identity may also require the use of extreme forms of violence, (3) the ready availability of guns clearly increases the stakes of how one achieves status, (4) much behavior is motivated by avoiding being a punk or herb (sucker or weakling), (5) identities can change from being a punk or herb into a more positive status such as “hold your own,” (6) guns equalize the odds for some smaller young men through the process of “showing nerve,” (7) one can feel like a punk for a specific situation but not take on a punk identity, (8) one can feel like a “crazy” killer in a specific situation but not take on a “crazy” or killer identity. If “compulsive masculinity” or Anderson’s “street orientation” is dominant in public spaces and personal safety as our data suggest, then those who do not conform will be victimized. The reproduction of social identities constructed through violent behavior, and the eclipsing or devaluation of other identities spreads in increasingly socially isolated networks. These identities reinforce the dominance hierarchy built on “toughness” and violence, and its salience devalues other identities. Those unwilling to adopt at least some dimensions of these norms either overtly or symbolically are vulnerable to physical attack. Accordingly, these identities are strategic necessities to navigate through everyday dangers of inner city life. The maintenance and reinforcement of identities supportive of violence is made possible by an effective socio-cultural dynamic that sets forth an age grading pathway to manhood that includes both behaviors and the means of resolving


44

violations of respect. The illustrations in this chapter show the strong influence of street code, similar to the codes identified by Anderson (1994), or the code of honor described by Toch (1969), over the behaviors of young children, adolescents, and young adults. The absence of alternative means of attaining valued masculine identities further compound the problem. The transmission of these social processes occur on both the micro and macro level. Children growing up in this environment learn these codes, or behavioral-affective systems, by navigating their way through interpersonal situations which oftentimes involve violence encounters. One effect of “danger” as a dominant ecological marker is the difficulty that adolescents have in maintaining that duality of behavior and of orientation. The street code has a functional purpose for attaining status and avoiding danger, even for adolescents who harbor conventional attitudes and goals. Negotiating safety within this context is extremely difficult especially when much of the social activity available to young men often involves expressing dominance over others. The effects are a hardening of street codes, and an eclipsing of other avenues for social status and respect. Attempts to reverse this cycle must address its manifestations at both the individual, group, and societal levels.

IV. SOCIAL CONTAGION AND SOCIAL NORMS

The dynamics of social contagion can be accommodated within concepts of social influence and social norms. The social influence concept of behavior borrows from both economics and sociology.41 Its economic component suggests that people will act to maximize their utility, while its sociological dimension suggests that

41. Bernard E. Harcourt, Reflecting on the Subject: A Critique of the Social Influence Conceptions of Deterrence, the Broken Windows Theory, and Order-Maintenance Policing New York Style, 97 Michigan Law Review 291, 305 (1998).


45

conduct is shaped through direct and vicarious social interactions. A simple version of this nexus suggests that the choice of conduct is influenced by observation and practice of the most effective options. Choices are contextualized as well, reflecting both the range of available options and the specific contingencies in which they are applied.42 In the contagious dynamics of violence, the social meaning of violence is constructed through the interrelationship of its action and its context.43 The social meaning in this case involves actions (violence) that have both returns (identity, status, avoidance of attack) and expectations that, within tightly packed networks, are unquestioned or normative. Conduct impregnated with social meaning has influence on the behaviors of others in immediate proximity. The social meaning of violence influences the adaptation of behavioral norms, expected responses (scripts), and even beliefs (memes) about systems of behavior. Social norms are the product of repeated events that demonstrate the meaning and utility of specific forms of conduct. Social influence thus has a dynamic and reciprocal effect on social norms.44 In poor neighborhoods, social interactions are dominated by street codes, or local systems of justice, that reward displays of physical domination and offer social approval for antisocial behavior.45 The endogeneity of social contagion to networks and neighborhoods illustrates the differences in the two types of epidemics. The origins of a contagious epidemic that travels through a population become distal influences on the pathway and dynamics of transmission through populations over time. The setting or context of contagion reflects the susceptibility of populations to the transmission of a socially meaningful behavior, and its exposure to the behavior that has acquired meaning. 42. Fagan, Context and Culpability in Adolescent Violence, at __. 43. Lessig, at 949. 44. Harcourt at 307; Lessig at 1040. 45. Fagan, Context and Culpability in Adolescent Violence, at __; Anderson, Violence and the Inner City Code of the Streets (1999).


46

This can be true both for fashion and art,46 as well as for problematic social behaviors such as drug use,47 teenage pregnancy,48 and violence.49 Recent applications of social influence models to crime control emphasize the seminal role of exogenous influence of “disorder,” where minor crimes signal to would-be criminals that crimes in that area will be tolerated and not reported.50 At first glance, Broken Windows suggests that there is a spread of norms supporting crime that overwhelm norms of orderliness. The spread comes from the continuing signals from disorder. Apart from the problematic nature of this dichotomous categorization of persons,51 Broken Windows medicalizes the conditions of disorder and criminality. It assumes that exposure to the disorder is a constant and recurring process that signals to the motivated offender that crime can succeed. Withdrawal of the signs of disorder will change social norms by allowing the social influence of orderliness to flourish. But this theory is limited by focusing only on the introduction of the original cues or sources of crime, and rely on the causal effects of these exogenous factors. This is analogous to the food poisoning model of epidemics. The dynamics of social contagion instead suggest an endogenous process, where the spread of social norms occurs through the everyday interactions of individuals within networks that are structurally equivalent and closely packed. Here, the ill grows and spreads from the inside, often long after the origins have subsided. This is analogous to influenza contagion, or to the spread of cultural or political thought. 46. Malcolm Gladwell, Cool Hunting, The New Yorker __(1997); James Servin, Cool Hunting with Jane, Harpers Bazaar, February 1999 at 90. 47. Rowe and Rodgers 48. Jonathan Crane 49. Fagan, Context and Culpability; Anderson, Violence and the Inner City Code of the Streets 50. See, Wilson and Kelling, Broken Windows, The Atlantic Monthly, March 1982, at 29; George Kelling and Susan Coles, Fixing Broken Windows (1986), analogizing to water supply contamination as the source of the cholera epidemic in nineteenth century London. See, Edwin Tufte, Visual Displays of Quantitative Information (1995).


47

The concept of contagion neutralizes the categorizations of disorder and order that theoretically inform the new path of deterrence. A literal translation of contagion would emphasize guns as a recurring source of violence, and as an agent in the transmission of violence norms. Because the recent epidemic cycle of violence was in reality a gun homicide epidemic, the case for gun-oriented policing52 strategies is much stronger than practices based the more diffuse and unsupported theory of disorder control and order-maintenance strategies.

While disorder embraces

orderliness, cleanliness, and sobriety,53 violence appears to travel on vectors quite unrelated to that particular set of social norms. 25

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Table 1. Gun and Non-Gun Homicide in New York City, by Sex, 1985-1995a Gun

Non-Gun

Male Year 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

N 747 846 980 1220 1282 1470 1526 1457 1387 1065 722

Female Rate 21.8 24.7 28.6 35.6 37.4 42.9 44.5 42.5 40.4 31.0 21.0

N 87 102 120 111 107 127 146 138 142 95 96

Male Rate 2.2 2.6 3.1 2.9 2.7 3.3 3.8 3.5 3.6 2.4 2.5

N 493 491 417 416 376 474 350 302 309 290 223

Female Rate 14.4 14.3 12.2 12.1 11.0 13.8 10.2 8.8 9.0 8.5 6.5

N 182 183 166 184 190 183 170 138 157 142 146

Rate 4.7 4.7 4.3 4.7 4.9 4.7 4.4 3.5 4.0 3.6 3.8

a. Rate per 100,000 persons within each population group

Table 2. Gun and Non-Gun Homicide in New York City, by Race, 1985-1995a Gun White Year 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

N 386 416 377 506 580 722 742 738 659 492 365

Rate 10.1 10.9 9.8 13.2 15.1 18.8 19.4 19.3 17.2 12.8 9.5

Non-Gun Nonwhite N Rate 448 12.8 532 15.2 723 20.7 825 23.6 809 23.2 875 25.1 930 26.6 849 24.3 856 24.5 658 18.9 446 12.8

a. Rate per 100,000 persons within each population group

White N 306 278 232 246 257 342 246 229 212 219 171

Rate 8.0 7.3 6.1 6.4 6.7 8.9 6.4 6.0 5.5 5.7 4.5

Nonwhite N Rate 369 10.6 396 11.3 351 10.1 354 10.1 309 8.9 315 9.0 274 7.8 209 6.0 251 7.2 201 5.8 191 5.5


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Table 3. Adolescent Gun and Non-Gun Homicide in New York City, by Age, 1985-1995a

Year 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

Under 14 Years N Rate 8 0.6 15 1.1 17 1.2 21 1.5 19 1.3 31 2.2 14 1.0 18 1.3 22 1.6 10 0.7 12 0.8

15-19 Years N Rate 96 20.8 92 19.9 153 33.1 210 45.5 199 43.1 235 50.9 265 57.4 223 48.3 224 48.5 183 39.6 120 26.0

Gun 20-24 Years N Rate 191 34.1 247 44.1 283 50.6 318 56.8 336 60.0 371 66.3 371 66.3 381 68.1 357 63.8 266 47.5 194 34.7

25-34 Years N Rate 290 21.1 351 25.6 347 25.3 460 33.5 520 37.9 579 42.2 579 42.2 587 42.8 514 37.5 411 30.0 248 18.1

Over 35 Years N Rate 249 7.1 243 6.9 300 8.5 322 9.2 315 9.0 381 10.8 443 12.6 386 11.0 412 11.7 290 8.3 244 6.9

25-34 Years N Rate 167 12.2 194 14.1 174 12.7 169 12.3 184 13.4 202 14.7 150 10.9 108 7.9 122 8.9 121 8.8 90 6.6

Over 35 Years N Rate 331 9.4 296 8.4 275 7.8 278 7.9 246 7.0 261 7.4 227 6.5 218 6.2 229 6.5 200 5.7 180 5.1

Non-Gun Year 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

Under 14 Years N Rate 41 2.9 48 3.4 26 1.8 43 3.0 37 2.6 48 3.4 44 3.1 34 2.4 58 4.1 44 3.1 37 2.6

15-19 Years N Rate 48 10.4 37 8.0 29 6.3 28 6.1 30 6.5 59 12.8 37 8.0 32 6.9 18 3.9 28 6.1 24 5.2

a. Rate per 100,000 persons within each age group

20-24 Years N Rate 88 15.7 99 17.7 79 14.1 82 14.6 69 12.3 87 15.5 62 11.1 48 8.6 39 7.0 39 7.0 38 6.8


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Table 4. Age Homogeneity of Gun and Non-Gun Homicides, 1985-95a Gun

Non - Gun

Victim and Offender Age

Victim and Offender Age

Year 1985 1986

15 to 19

20 to 24

25 to 34

15 to 19

20 to 24

25 to 34

26.5

22.9

38.5

25.4

23.0

38.5

25.0

27.1

40.7

15.5

22.5

28.7

1987 1988 1989 1990 1991 1992 1993 1994 1995

28.5

26.8

43.5

17.9

20.9

45.3

37.7

28.6

43.5

9.3

13.0

41.5

33.3

29.7

54.9

11.6

13.9

41.6

26.4

35.8

44.9

19.7

23.2

31.0

34.2

27.0

38.2

29.7

17.1

35.4

34.4

29.4

46.7

24.0

19.0

32.1

35.8

27.5

41.3

18.2

10.0

41.5

37.2

30.7

41.7

19.2

17.6

32.7

15.5

30.9

42.4

18.8

24.2

26.1

a. Percent of homicides within age group. Includes only cases where victim and offender ages are both known. Annual rates adjusted for missing months of data. Source: Supplemental Homicide Reports, 1976-94; New York City Police Department, 1995.


55

_______________________________________________________________________________________ Table 5. Factor Analysis of 1990 STF3A Census Tract Variables (N=2,803) ________________________________________________________________________________________ Final Factors

Composition

Eigenvalue

% Variance Explained

Deprivation

1. Household Gini Index 2. Median Household Income 3. Households Below Poverty 4. Education Ratio 5. Labor Force Participation Ratio 6. Unemployment Rate 7. Skilled Jobs Ratio

6.30

45.0

Population Structure

1. Proportion Nonwhite 2. Separated and Divorced 3. Never Married 4. Female Headed Households

1.52

10.8

Social Control

1. Supervision Ratio 1.09 7.8 2. Residential Mobility 3. Population ________________________________________________________________________________________

________________________________________________________________________________________ Table 6. Repeated Measures Analysis of Adolescent Homicide Rates by Census Tract, New York City, 1985-1995 ________________________________________________________________________________________ t-value Deprivation 8.51 ** Population 9.90 ** Social Control 1.59 ________________________________________________________________________________________ * p < .05 ** p < .001

_________________________________________________________________________________________


56

________________________________________________________________________________________ Table 7. Contagion of Adolescent Homicide from in New York City, 1985-1995 ________________________________________________________________________________________ A. Any Homicide (Lag = 1 Year) Outward Contagion Model 1 t-value At Least One Adolescent Homicide in Neighborhood

13.58 **

Model 2 t-value

Model 3 t-value

Model 4 t-value

24.77 **

At Least One Adolescent Homicide in Surrounding Community Deprivation Population Structure Social Control

Inward Contagion

4.66**

7.31 **

29.53 ** 50.40 ** 2.82 *

20.76 ** 27.23 ** 7.56 **

________________________________________________________________________________________ B. Homicide Rate (Lag = 1 Year) Outward Contagion Model 1 t-value Adolescent Homicide Rate in Neighborhood

12.43 **

Model 2 t-value

Model 3 t-value

Model 4 t-value

5.56 **

Adolescent Homicide Rate in Surrounding Community Deprivation Population Structure Social Control

Inward Contagion

18.55 ** 27.05 ** 53.11 ** -4.78 **

5.48 ** 14.35 ** 25.23 ** -2.71 *

________________________________________________________________________________________ * p < .05 ** p < .001

________________________________________________________________________________________


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________________________________________________________________________________________ Table 8. Outward Contagion of Adolescent Gun Homicide from Neighborhood to Surrounding Community, New York City, 1985-1995 ________________________________________________________________________________________ A. Any Homicide (Lag = 1 Year) Gun Homicide in Surrounding Community Model 1 t-value At Least One Adolescent Gun Homicide in Neighborhood Deprivation Population Structure Social Control

14.96 **

Model 2 t-value

4.26 ** 29.12 ** 50.21 ** 0.37

Non-Gun Homicide in Surrounding Community Model 3 t-value

7.42 **

Model 4 t-value

1.39 13.01 ** 22.50 ** 4.92 **

________________________________________________________________________________________ B. Gun Homicide Rate (Lag = 1 Year)

Gun Homicide in Surrounding Community Model 5 t-value

Model 6 t-value

Non-Gun Homicide in Surrounding Community Model 7 t-value

Model 8 t-value

Adolescent Gun Homicide Rate in Neighborhood 11.53 ** 5.38 ** 8.58 ** 1.39 Deprivation 26.10 ** 16.89 ** Population Structure 59.82 ** 23.95 ** Social Control -8.48 ** 4.15 ** ________________________________________________________________________________________ * p < .05 ** p < .001

________________________________________________________________________________________


58

________________________________________________________________________________________ Table 9. Inward Contagion of Adolescent Gun Homicide in New York City, 1985-1995 ________________________________________________________________________________________ A. Any Homicide (Lag = 1 Year) Neighborhood Gun Homicide Model 1 t-value At Least One Adolescent Gun Homicide in Surrounding Community

Neighborhood Non-Gun Homicide

Model 2 t-value

27.20 **

9.33 **

Deprivation Population Structure Social Control

Model 3 t-value

Model 4 t-value

2.20 *

20.63 ** 29.37 ** 6.72 **

1.01

3.80 ** -.028 .05

________________________________________________________________________________________ B. Homicide Rate (Lag = 1 Year) Neighborhood Gun Homicide Model 5 t-value Adolescent Gun Homicide Rate in Surrounding Community 22.53 **


Neighborhood Non-Gun Homicide

Model 6 t-value

7.73 **

14.23 ** 26.71 ** -4.30 **

Model 7 t-value

2.20 *

Model 8 t-value

1.05

3.70 ** -.028 .07

________________________________________________________________________________________ * p < .05 ** p < .001

________________________________________________________________________________________


59

________________________________________________________________________________________ Table 10. Outward Contagion of Adolescent Non-Gun Homicide in New York City, 1985-1995 ________________________________________________________________________________________ A. Any Homicide (Lag = 1 Year) Non-Gun Homicide in Surrounding Community

At Least One Adolescent Non-Gun Homicide in Neighborhood

Gun Homicide in Surrounding Community

Model 1 t-value

Model 2 t-value

Model 3 t-value

Model 4 t-value

.79

- .59

.70

.35


18.73 ** 31.14 ** 12.39 **

11.92 ** 22.78 ** -3.91 **

________________________________________________________________________________________ B. Homicide Rate (Lag = 1 Year)

Non-Gun Homicide in Surrounding Community Model 5 t-value Adolescent Non-Gun Homicide Rate in Neighborhood Deprivation Population Structure Social Control

- .14

Model 6 t-value

- .24 17.08 ** 24.79 ** 4.11 **

Gun Homicide in Surrounding Community Model 7 t-value

.74

Model 8 t-value

.59 26.44 ** 61.59 ** -8.58 **

________________________________________________________________________________________ * p < .05 ** p < .001

________________________________________________________________________________________


60

________________________________________________________________________________________ Table 11. Inward Contagion of Adolescent Non-Gun Homicide in New York City, 1985-1995 _______________________________________________________________________________________ A. Any Homicide (Lag = 1 Year)

Non-Gun Homicide in Neighborhood Model 1 t-value At Least One Adolescent Non-Gun Homicide in Surrounding Community Deprivation Population Structure Social Control

2.55 *

Model 2 t-value

.69 4.67 ** .55 -1.43

Gun Homicide in Neighborhood Model 3 t-value

Model 4 t-value

-1.15

.46 8.50 ** 15.58 ** -3.26 **

________________________________________________________________________________________ B. Homicide Rate (Lag = 1 Year) Non-Gun Homicide in Neighborhood Model 5 t-value Adolescent Non-Gun Homicide Rate in Surrounding Community


2.27 *

Model 6 t-value

2.31 *

3.73 ** - .26 - .04

Gun Homicide in Neighborhood Model 7 t-value

8.65 **

Model 8 t-value

.98

15.89 ** 31.81 ** -4.75 **

________________________________________________________________________________________ * p < .05 ** p < .001

________________________________________________________________________________________


61

________________________________________________________________________________________ Table 12. Contagion of Adolescent Gun to Total Homicide in New York City, 1985-1995 ________________________________________________________________________________________ A. Logistic Repeated Measures Models (Lag = 1 Year) Outward Contagion Model 1 t-value At Least One Adolescent Gun Homicide in Neighborhood

15.66 **

Model 2 t-value

Inward Contagion Model 3 t-value

Model 4 t-value

4.73 **

At Least One Adolescent Gun Homicide in Community

25.84 **

Poverty Factor Family/Ethnicity Factor Anonymity Factor

8.34 **

29.48 ** 49.91 ** 2.84 **

20.51 ** 26.45 ** 7.72 **

________________________________________________________________________________________ B. Standard Repeated Measures Models (Lag = 1 Year) Outward Contagion Model 1 t-value Adolescent Gun Homicide Rate in Neighborhood Adolescent Gun Homicide Rate in Community

14.23 **

Model 2 t-value


Model 4 t-value

5.81 **

20.76 **

6.38 **

Poverty Factor 27.03 ** 14.06 ** Family/Ethnicity Factor 52.62 ** 24.13 ** Anonymity Factor -4.72 ** -2.53 * ________________________________________________________________________________________ * p < .05 ** p < .001


62

__________________________________________________________________________________________


63

__________________________________________________________________________________________ Table 13. Contagion of Adolescent Non-Gun to Total Homicide in New York City, 1985-1995 ________________________________________________________________________________________ A. Logistic Repeated Measures Models (Lag = 1 Year) Outward Contagion

At Least One Adolescent Non-Gun Homicide in Neighborhood

Model 1 t-value

Model 2 t-value

-0.09

-1.04

At Least One Adolescent Non-Gun Homicide in Community Poverty Factor Family/Ethnicity Factor Anonymity Factor


Model 4 t-value

12.84 **

3.19 21.82 30.17 7.34

30.15 ** 52.14 ** 2.88 **

** ** ** **

________________________________________________________________________________________ B. Standard Repeated Measures Models (Lag = 1 Year) Outward Contagion

Adolescent Non-Gun Homicide Rate in Neighborhood Adolescent Non-Gun Homicide Rate in Community Poverty Factor Family/Ethnicity Factor Anonymity Factor

Model 1 t-value

Model 2 t-value

-1.31

-0.52


9.41 ** 27.49 ** 54.65 ** -4.87 **

Model 4 t-value

2.02 15.41 28.52 -2.95

* ** ** *

________________________________________________________________________________________ * p < .05


64

** p < .001

Appendix A. New York City Mortality Data, 1968-1996 Counts Rates (Base = 1985) Year Gun Non-Gun Total Gun Non-Gun Total 1968 424 537 961 52.02 96.41 70.04 1969 490 521 1011 60.12 93.54 73.69 1970 628 513 1141 77.06 92.10 83.16 1971 806 701 1507 98.90 125.85 109.84 1972 936 756 1692 114.85 135.73 123.32 1973 889 791 1680 109.08 142.01 122.45 1974 811 725 1536 99.51 130.16 111.95 1975 886 707 1593 108.71 126.93 116.11 1976 846 742 1588 103.80 133.21 115.74 1977 918 636 1554 112.64 114.18 113.27 1978 891 660 1551 109.33 118.49 113.05 1979 1039 722 1761 127.48 129.62 128.35 1980 1109 735 1844 136.07 131.96 134.40 1981 1187 673 1860 145.64 120.83 135.57 1982 1056 671 1727 129.57 120.47 125.87 1983 1004 639 1643 123.19 114.72 119.75 1984 884 587 1471 108.47 105.39 107.22 1985 815 557 1372 100 100 100 1986 929 613 1542 113.99 110.05 112.39 1987 1085 565 1650 133.13 101.44 120.26 1988 1310 586 1896 160.74 105.21 138.19 1989 1378 513 1891 169.08 92.10 137.83 1990 1563 616 2179 191.78 110.59 158.82 1991 1644 519 2163 201.72 93.18 157.65 1992 1554 441 1995 190.67 79.17 145.41 1993 1488 468 1956 182.58 84.02 142.57 1994 1160 433 1593 142.33 77.74 116.11 1995 818 369 1187 100.37 66.25 86.52 1996 652 335 987 70.18 54.65 64.01 __________________________________________________________________________________________


65

Appendix B. Means and Standard Deviations for Neighborhood Characteristics (N = 2083 Census Tracts)

Variable

1. Population 2. Separated and Divorced 3. Never Married 4. Racial Composition 5. Residential Mobility 6. Poverty 7. Female Headed Households 8. Unemployment 9. Income 10. Income Equality 11. Supervision Ratio 12. Labor Force Participation Ratio 13. Education Ratio

Operational Definition

Means

Standard Deviation

Valid Cases

3474 11.66 35.55 55.06 63.49 18.11 10.16 9.68 $ 31,419 .38 284.90 59.62

2408 5.57 9.48 36.15 10.05 14.54 9.88 6.38 $14,287 .08 154.77 88.40

2083 2083 2083 2083 2083 2078 2078 2081 2083 2078 2082 2081

% Individuals over 15 who are separated or divorced % Individuals over 15 who have never been married % Individuals Nonwhite % Households that have not moved in the past 5 years % Households below poverty % Households with children under 18 headed by female Unemployment Rate Median Household Income Household Gini Index Proportion individuals aged 25-64 to those aged 5-24 Proportion individuals in labor force to those not in labor force Proportion individuals with some college education to those without completed high school education 132.34 151.60 2081 14. Skilled Jobs Ratio Proportion individuals with professional or managerial jobs to those with non-skilled jobs 18.06 23.26 2072 _________________________________________________________________________________________________________________

19 68 19 69 19 70 19 71 19 72 19 73 19 74 19 75 19 76 19 77 19 78 19 79 19 80 19 81 19 82 19 83 19 84 19 85 19 86 19 87 19 88 19 89 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98

1985 Base = 100


225

200

67

Figure 1 GUN AND NON-GUN HOMICIDE, 1968-1998 GUN

NONGUN

TOTAL

175

150

125

100

75

50

25

Year

Year 19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

98

97

96

95

94

93

92

91

90

89

88

87

86

85

84

83

82

81

80

79

78

77

76

75

74

73

72

71

70

69

68

2000

19

19

19

19

19

19

19

Counts

SOCIAL CONTAGION OF VIOLENCE 68

Figure 2 GUN AND NON-GUN HOMICIDES, 1968-1998

2500

GUN

NONGUN

TOTAL

1500

1000

500


69

Figure 3. DRUG OVERDOSE DEATH AND AGE-SPECIFIC GUN HOMICIDE VICTIMIZATION RATES, 1985-95 80 Drug Overdose Deaths

70

Gun Homicides 15 - 19 Gun Homicides 20 - 24

Age-Specific Rate per 100,000

60

Gun Homicides 25 - 34

50

40

30

20

10

0 1985

1986

1987

1988

1989

1990

Year

1991

1992

1993

1994

1995


70


71

Figure 4a. AGE-SPECIFIC FELONY DRUG ARREST RATES AND GUN HOMICIDE VICTIMIZATION RATES, 1985-95 250

Gun Homicides 15 - 19 Gun Homicides 20 - 24 Gun Homicides 25 - 34

Age-Specific Rate per 100,000

200

Drug Arrests 10-19 Drug Arrests 20 - 24 Drug Arrests 25 - 34

150

100

50

0 1985

1986

1987

1988

1989

1990

Year

1991

1992

1993

1994

1995