Objective: For this assignment, you should apply ideas from the course to evaluate the depiction of crime, violence, and/or disorder in urban neighborhoods in some form of popular media. Choose one fi

Motivated by this reality, our essay ex- amines the spatial concentration of in- carceration, focusing on its geographic manifestations in the quintessentially American city of Chicago. Assembling census data, crime rates, and court rec- ords into a common geographic refer- ent, we explore rates of community- level incarceration from 1990 to 2006 to probe three general questions:

1. How does incarceration impact neigh- borhoods differentially? What is the nature of spatial inequality in impris- onment rates across communities?

20 Dædalus Summer 2010 Robert J. Sampson & Charles Loeffler Punishment’s place: the local concentration of mass incarceration © 2010 by the American Academy of Arts & Sciences Dædalus Summer 2010 21 2. What is the temporal trend? Have neighborhood patterns changed over time?

3. What are the key correlates? For ex- ample, how do community-level fea- tures such as the crime rate and the concentration of poverty relate to the intensity of incarceration, across time and neighborhoods?

Overall, we demonstrate that mass incarceration is a phenomenon that is experienced locally and that follows a stable pattern over time. Hot spots for incarceration are hardly random; in- stead, they are systematically predicted by key social characteristics. In particu- lar, the combination of poverty, unem- ployment, family disruption, and racial isolation is bound up with high levels of incarceration even when adjusting for the rate of crime that a community experiences. These factors suggest a self-reinforcing cycle that keeps some communities trapped in a negative feedback loop. The stability and place- based nature of incarceration have broad implications for how we think about policy responses.

Is Chicago a unique case or does it fol- low the general pattern of crime and punishment in late-twentieth-century America that has drawn attention from scholars? Figure 1 displays the tempo- ral pattern of imprisonment juxtaposed with the overall crime rate for the pe- riod from 1990 to 2006. We measure the imprisonment rate by dividing the num- ber of unique, Chicago-resident felony defendants sentenced to the Illinois Department of Corrections from the Circuit Court of Cook County by the number of Chicago inhabitants aged eighteen to sixty-four according to the Census. We use “at risk” adults in the denominator in order to rule out varia-tions in the prevalence of children under age eighteen, who are not eligible for prison. Similarly, we exclude older res- idents because, while society is aging, very few prisoners are over the age of sixty-½ve. These data were gathered from the electronic records of the Cir- cuit Court of Cook County. The crime rate is measured by the Uniform Crime Reports ( ucr ) “index” offenses (aggra- vated assault, forcible rape, murder, rob- bery, arson, burglary, larceny-theft, and motor vehicle theft) per 100,000 persons in Chicago.

Mirroring national trends, the Chicago crime rate peaked at the beginning of the 1990s (11,320 offenses per 100,000 per- sons) and then declined throughout the remainder of the 1990s and into the early 2000s. 6As of 2006, the crime rate (5,721 offenses per 100,000 persons) in Chicago was the lowest it had been in at least the previous twenty years. Yet the imprison- ment rate that began its rise in the 1970s (data not shown) continued to increase even after the crime rate peaked, climb- ing rapidly after 1990 and peaking in 1994 at 716 prisoners per 100,000 adult inhab- itants. In just four years, the rate of im- prisonment had increased 60 percent. It subsequently hovered near that all-time high, fluctuating between 600 and 700 prisoners per 100,000 adult inhabitants from 1994 to 2006. These Chicago trends, as depicted in Figure 1, are broadly con- sistent with trends in crime and incar- ceration throughout the United States.

Although the aggregate relationship between incarceration and crime is not the main focus of this paper, Figure 1 permits an overall assessment of the temporal connection. On the one hand, year-to-year changes in crime and im- prisonment rates are not strongly corre- lated with each other when considering short temporal lags over the entire peri- od. If mass incarceration functions as Punish- ment’s place 22 Dædalus Summer 2010 an effective criminal deterrent or tool of incapacitation, then crime decreas- es in years greater than tshould follow imprisonment increases in year t. Yet the actual pattern observed in Figure 1 suggests that increases or decreases in the imprisonment rate do not always lead to short-term decreases orincreas- es in the crime rate, and vice versa, af- ter about 1994. On the other hand, the beginning of the crime drop in the 1990s corresponds to a rapid rise in incarcera- tion. Although the number of cases is too small to reliably detect signi½cance, the crime rate correlates -0.89 with in- carceration from 1990 to 1994. Over the longer term of 1990 to 2006, the pattern yields a negative concurrent relationship (-0.47, p< 0.10); crime decreased steadi-ly as the imprisonment rate increased and then maintained, more or less, a high rate. Therefore, the dynamic rela- tionship between imprisonment and crime from 1990 to 2006 is generally negative. However, the pattern is com- plex, and it is not possible to draw con- clusions about cause and effect. T o what extent is mass incarceration concentrated? Unlike the temporal trends for imprisonment, the answer is unambiguous: punishment is distinctly concentrated by place. Figure 2 displays rates of imprisonment per 100,000 per- sons (aged eighteen to sixty-four) by community areas of Chicago for the period 1990 to 1995. Community areas average populations of approximately Figure 1 Imprisonment and Crime Trends in Chicago, 1990 –2006 Source: Authors’ calculations based on information collected from the Circuit Court of Cook County, the U.S. Census Bureau, and the U.S. Department of Justice. Robert J.

Sampson & Charles L o e ffl e r on mass incarcer- ation Dædalus Summer 2010 23 38,000 persons; they are widely recog- nized by residents and, in most cases, have well-known geographic borders.

Census tracts are nested within com- munity areas and are smaller, averag- ing approximately 4,000 persons. The patterns for tracts (not shown) are nearly identical to community areas.

The basic pattern of concentration is stark. Large swaths of the city, especially in the southwest and northwest, remain relatively untouched by the imprison- ment boom. In these areas, the incarcer-ation rate ranges from nearly zero to less than 500 per 100,000 adult residents. By contrast, there is a dense and spatially contiguous cluster of areas in near-west and south-central Chicago that have rates of incarceration some eight times higher (or more). Note especially the line of communities stretching south from the Loop and west into the sub- urban boundaries of the city (for ex- ample, the community of Austin) that produce a disproportionate share of prisoners.

Figure 2 Spatial Concentration of Incarceration in Chicago, 1990–1995 Source: Authors’ calculations based on information collected from the Circuit Court of Cook County and the U.S. Census Bureau. Punish- ment’s place 24 Dædalus Summer 2010 Does this pattern change over time?

Despite a leveling-off in the overall in- tensity of punishment as foretold by Figure 1, there is a great deal of stabil- ity in the spatial logic of incarceration.

Figure 3 presents imprisonment rates for the most recent period of available data, 2000 to 2005. As in 1990 to 1995, prisoners are primarily from the South and West Sides of Chicago. In fact, at a glance, Figures 2 and 3 reveal very little difference in patterns of incarceration, even with the time gap. The simple cor-relation between the rates across time is greater than 0.90 for community areas and 0.86 for tracts (p< 0.01), an extreme- ly high level of persistence. The Spear- man’s correlation of rank order is 0.97 and 0.92, respectively, for community areas and tracts.

The main difference between the two time periods is that incarceration inten- si½ed its grip on the far West and South Sides of the city. Not surprisingly, some areas that were already at the high end of the crime and incarceration distribu- Figure 3 Spatial Concentration of Incarceration in Chicago, 2000–2005 Source: Authors’ calculations based on information collected from the Circuit Court of Cook County and the U.S. Census Bureau. Robert J.

Sampson & Charles L o e ffl e r on mass incarcer- ation Dædalus Summer 2010 25 tions also saw improvements. Research, and the tendency of many social trends to “regress to the mean,” has shown that the highest-crime neighborhoods in Chicago have experienced the biggest crime drops. 7Nonetheless, the commu- nities of Austin, East Gar½eld Park, and West Gar½eld Park (on the far West Side) experienced the largest relative increases in imprisonment rates, approximately 50 percent, across the two time periods.

By contrast, the areas of Oakland, Grand Boulevard, and Washington Park (on the near- to mid-South Side) each experienced a decline of between 30 and 50 percent.

Perhaps not coincidentally, some of these improving areas (especially Oakland and Grand Boulevard) saw large-scale chang- es or planned interventions that may explain the unexpectedly large declines, such as city investments in mixed-income housing, the demolition of high-rise pub- lic housing projects, and the steady in- migration of the African American mid- dle class. 8Further examination of the consequences of these large-scale chang- es for the social and spatial organization of Chicago (the displacement of crime or the migration of offenders to other neighborhoods, for example) is beyond the scope of this paper but is currently being pursued in other studies.

Overall, the data in Figures 1–3 paint a picture of patterned stability and change in incarceration. Like the rest of the Unit- ed States, Chicago has seen a boom in imprisonment, with rates increasing more than 50 percent from 1990 after a period of prior increases. These in- creases and subsequent temporal var- iations do not appear to track the crime rate closely, although in a broad sense it is clear that at the end of the twentieth century, crime approached record lows as incarceration hovered around its peak.

As noted earlier, whether this occurrence is a causal effect of imprisonment on re-ducing crime or an artifact we cannot say.

We can be certain, however, that against the march of time there is a fundamental inequality in the reach of incarceration across communities. Large areas of Chi- cago have escaped the brunt of the in- carceration regime, while a small band of communities on the West, far West, South, and far South Sides of Chicago are highly affected. This general pattern is stable, with already susceptible com- munities such as West Gar½eld Park and Austin on the West Side undergo- ing dramatic growth beyond preexist- ing vulnerability. The implication of our ½nding is that the concept of “mass” incarceration is potentially quite mis- leading, for its instantiation is experi- enced at a highly local level. W hat is it about “imprisoned commu- nities” that explains their unequal expe- riences? We have demonstrated that im- prisonment is not randomly inscribed across the urban landscape. Both logic and criminal justice “common wisdom” would suggest that the hot spots of pun- ishment are those that generate the most crime. This is in part the case.

To take the most straightforward ex- ample, we calculated the rate of crime disaggregated by those forms that tend to generate the most public attention and that have been implicated in the impris- onment run-up: violence (assault, rape, and homicide), robbery, drug-related offenses, and burglary. At the community level, these crimes cluster together and correlate highly with later incarceration rates. For example, violence and drug crimes during the period 1995 to 2000 are both correlated at greater than 0.70 (p< 0.01) with incarceration rates in 2000 to 2005 across communities. Be- cause prison sentencing does not occur instantaneously following an incidence of crime, we allowed for a lag effect by Punish- ment’s place 26 Dædalus Summer 2010 comparing two intervals of time that include multiple years, simultaneously allowing for variability in temporal lag patterns and reducing measurement error in both crime and incarceration rates. We also created a summary mea- sure that combines information from the four major categories of crime. The results con½rmed that all four crime rates correlate strongly with each other and form a single factor based on a prin- cipal components analysis. To capture the common variance, we calculated the ½rst principal component, which is a simple linear combination of the four crime rates weighted by their association with the common factor. Put simply, the scale reflects the overall “crime propen- sity” of each community.

One might argue that arrest rates are a more direct measure of criminal offender production as opposed to the criminal offenseproduction reflected in the crime rate. But high rates of citizen-reported crime are the more public face of victim- ization and demands for action against crime, and thus may be more relevant in terms of generating demand for punish- ment and reinforcing negative reputa- tions about safety in select communities.

Previous research has also shown that arrest rates and estimates of criminal offending rates are closely related to the crime rate, in large part because offenders tend to commit crimes rela- tively close to home. 9Consistent with this general argument, in the years 1998 and 1999, the total arrest rate is correlat- ed 0.78 (p< 0.01) with the total crime rate across neighborhoods in Chicago.

We do not have arrest data across all relevant years in question that would allow us to pursue this issue further, thus we rely on the summary crime rate for the main analysis. We ½nd that incarceration rates are very tightly con- nected–at the neighborhood level–withprior rates of crime. Speci½cally, consis- tent with our expectations, the crime factor correlates 0.72 (p< 0.01) with the later incarceration rate.

This pattern does not mean that the social features of communities can be set aside in thinking about communities’ risk for incarceration. There is a line of theoretical work arguing that concen- trated inequality exacerbates existing patterns of criminal justice punishment.

In particular, the attributions and per- ceptions of dangerousness attached to stigmatized and spatially concentrated minority groups have been hypothesized to increase the intensity of both unof½- cial beliefs about social disorder 10 and of½cial decisions to punish through in- carceration. 11 According to this argu- ment, offenders from communities of concentrated disadvantage are them- selves stigmatized and are more likely to be incarcerated when compared to those in less disadvantaged communi- ties with similar crime rates.

We examined the broad contours of this thesis by estimating the relation- ship between dimensions of concen- trated poverty and later incarceration, adjusting for the crime rate. Prior work on the Chicago data, and on national ½gures as well, has shown that correlat- ed aspects of urban disadvantage tend to cluster, particularly the percentage of the population that is in poverty, unemployed, on welfare, and in single- parent, female-headed families. All of these factors are more prevalent in seg- regated African American areas (as in- dicated by the percentage of African Americans).

12 Whether tracts or com- munity areas, these social characteris- tics thus cluster together, de½ning a factor we label “concentrated disad- vantage.” 13 The correlation between concentrated disadvantage in 2000 and the incarceration rate in 2000 to Robert J.

Sampson & Charles L o e ffl e r on mass incarcer- ation Dædalus Summer 2010 27 2005 is signi½cant: 0.78 (p< 0.01).

But disadvantage also co-varies with the crime rate; in fact, the correlation between disadvantage and the crime rate is equal to that of disadvantage and incarceration (0.78). Under these conditions, it is dif½cult to estimate independent associations other than with a simple model in which both the crime rate and disadvantage are allowed to predict later incarceration.

Nevertheless, this ½nding suggests that both factors have explanatory relevance, especially at the tract level, where we have more cases and, as a consequence, greater statistical power.

Figure 4 evaluates our claim, visually reflecting the magnitude of associations.

The incarceration rate per 100,000 is graphed on the left axis. The bars refer to the indicators of the crime rate (com- bined six-year average of burglary, rob- bery, violence, and drugs) and the 2000 concentrated disadvantage scale, each split into equal thirds. At each level of the crime rate, incarceration rates in- crease monotonically with concentrated disadvantage. Note that at the very high- est level of crime, those communities most “at risk” for punishment in the classic criminal-punishment sense are nonetheless clearly differentiated. In fact, communities that experienced high disadvantage experienced incarceration rates more than three times higherthan communities with a similar crime rate.

At all levels of concentrated disadvan- tage, crime rates signi½cantly predict later incarceration as well. Thus it is not that incarceration is somehow “irration- al,” rather it is increased in certain social contexts in ways that cannot be explained by crime. Analysis not shown con½rmed that this pattern is maintained when ra- cial composition (percent of the popula- tion that is African American) is entered as a separate control and not included inthe disadvantage scale and when the ar- rest rate of neighborhood residents (an indicator of offender production) is controlled.

We also explored the possibility of a reverse pathway of influence, whereby incarceration was speci½ed as a predic- tor of future concentrated disadvantage independent of the crime rate leading up to that point. Our data (not shown) re- vealed that the incarceration rate in 1990 to 1995 strongly predicts concentrated disadvantage in 2000 when we control for the crime rate in 1995 to 2000 (p< 0.01), a strict test given that the crime rate is measured afterthe imprisonment rate and thus has presumably reaped any deflection from deterrent or incapacita- tion effects. The magnitude of the pre- dictive association between incarcera- tion and future disadvantage was simi- lar to that of crime and disadvantage, and again, the relationship held when racial composition was considered as a separate control from the disadvantage factor.

What we appear to observe, then, is a mutually reinforcing social process: dis- advantage and crime work together to drive up the incarceration rate. This combined influence in turn deepens the spatial concentration of disadvan- tage, even if at the same time it reduces crime through incapacitation. In such a reinforcing system with possible coun- tervailing effects at the aggregate tempo- ral scale, it is dif½cult, if not impossible, to estimate the overall net effect of in- carceration. Moreover, one can argue that there is measurement error or mis- speci½cation in the nature of our crime rate control, a reality we acknowledge and have discussed above. But we have measured those offenses that are known to the criminal justice system and that have been shown to drive public opinion and, we suggest, incarceration decisions. Punish- ment’s place 28 Dædalus Summer 2010 Recent data from Chicago also show that arrest rates closely track crime rates and that offenders are highly constrained by spatial proximity and racial segregation in choosing crime locations. 14 And when we directly control for the arrest rate of residents, we obtain the same results for concentrated disadvantage.

Thus, although the entire pathway from crime to offender to prison sen- tence is indeed unobserved in our data, it is hard to imagine relevant character- istics that could diminish the signi½cance of incarceration rates that differ by three- fold or more. It seems more likely that while crime leads to incarceration up to a point, there is much more “input” tothe system in the way of social cues and systematic community-level or contex- tual effects. 15 In other words, crime and incarceration are partially decoupled at the community level. We suggest that the cluster of features reflected in concentrat- ed disadvantageis a prime candidate for the source, but possibly also the conse- quence, of incarceration. M ass incarceration has drawn much interest, but with few exceptions, little rigorous attention has been paid to the way that incarceration shapes and is shaped by local communities. Some claim that incarceration depletes social capital and thereby harms already disad- Figure 4 Incarceration by Concentrated Disadvantage and Crime, 1995–2005 Source: Authors’ calculations based on information collected from the Circuit Court of Cook County, the U.S. Census Bureau, and the U.S. Department of Justice. Robert J.

Sampson & Charles L o e ffl e r on mass incarcer- ation Dædalus Summer 2010 29 vantaged communities. 16 Others claim that deterrent or incapacitation effects of incarceration reduce crime and there- by improve human well-being, especial- ly in disadvantaged communities that initially had the highest crime rates and have since witnessed the largest decreas- es in crime. 17 As recently suggested by a systematic review of the available evi- dence on criminal recidivism, these ap- parently dueling arguments are not nec- essarily mutually exclusive. Imprison- ment may be criminogenic even as the threat of punishment by con½nement is a deterrent. 18 We have investigated the spatial con- centration of imprisonment in Chicago as well as the possibility that concentrat- ed disadvantage is implicated in the spa- tial concentration of punishment beyond its contribution to criminal offending or arrest production. We do not claim to have set up a strict test of causality, and our data are limited as data always are.

But the patterns we uncovered are con- sistent with our theoretical framework, are large in magnitude, and make con- ceptual sense at different levels of analy- sis. Speci½cally, while there seems to be little doubt that crime decreases have followed increased incarceration rates in recent years, the nature of this rela- tionship is complex; aggregate trends in crime and imprisonment mask the mag- nitude of neighborhood concentration and the deep penetration of incarceration in high-rate communities (Figures 2–3).

High levels of concentrated imprison- ment, year after year, would seem un- likely to contribute to social-capital formation or other social processes that foster healthy communities.

We have also shown evidence consis- tent with the thesis that concentrated disadvantage strongly predicts later in- carceration (adjusting for crime) and that incarceration strongly predicts later dis-advantage (again adjusting for crime).

The results are not simply attributable to the racial makeup of areas; although African Americans are both poorer and more likely to be incarcerated than whites or Hispanics, the association of concen- trated disadvantage with incarceration is robust and therefore appears to be contextual rather than compositional in nature.

There are two implications from these ½ndings. One is the likely reciprocal in- teraction whereby community vulnera- bility and incarceration are involved in a negative-feedback loop. Disadvantaged communities are more likely to be high- ly incarcerated communities, which in- creases their likelihood of becoming even more disadvantaged in the future. The second implication concerns the flip side of prisoner production. If communities disproportionately produce prisoners, they will disproportionately draw them back upon release. After all, even when imprisonment rates have soared, most prisoners return to a home community. 19 These twin feedback loops need further testing, but conceptually they may help explain both the high degree of stability and the fundamental dilemma of highly imprisoned communities. Unless an al- ternative policy is implemented, the evi- dence suggests, a subset of communities will continue to produce concentrated disadvantage, concentrated crime, and concentrated imprisonment.

The logic of our essay is consistent with recent calls for a community-level approach to penal reform. Such an ap- proach seeks to reintegrate offenders and help counteract the hardships–includ- ing high crime–that already disadvan- taged neighborhoods face when unem- ployed ex-felons return home. The maps of Figures 2 and 3 paint a particularly stark picture of communities on the edge.

Concentrated incarceration may have the Punish- ment’s place 30 Dædalus Summer 2010 unintended consequence of increasing crime rates through its negative impact on the labor market and social-capital prospects of former prisoners. 20 What is more, evidence shows that neighbor- hood context plays a major role in the recidivism rates of ex-prisoners.

21 The integration of prisoner release programsand efforts to build community capacity are important steps for policy. 22 Along with policy reform, efforts to destigma- tize and achieve justice for communities are crucial to overcoming the vicious cycle of crime production, victimization, incapacitation, and disadvantage. endnotes 1 Alfred Blumstein and Jacqueline Cohen, “Theory of the Stability of Punishment,” Journal of Criminal Law and Criminology64 (1973): 198–207.

2 Bureau of Justice Statistics, “Prisoners in 2008,” (Washington, D.C.: U.S. Department of Justice, 2009), http://bjs.ojp.usdoj.gov/content/glance/incrt.cfm.

3 Becky Pettit and Bruce Western, “Mass Imprisonment and the Life Course: Race and Class Inequality in U.S. Incarceration,” American Sociological Review69 (2004): 151–169.

4 Bruce Western, Punishment and Inequality in America(New York: Russell Sage Foundation, 2006).

5 Todd R. Clear, Imprisoning Communities: How Mass Incarceration Makes Disadvantaged Neigh- borhoods Worse(New York: Oxford University Press, 2007).

6 Alfred Blumstein and Joel Wallman, The Crime Drop in America(New York: Cambridge University Press, 2000).

7 Wesley Skogan, Police and Community in Chicago: A Tale of Three Cities(New York: Oxford University Press, 2006).

8 Mary E. Pattillo, Black on the Block: The Politics of Race and Class in the City(Chicago: Univer- sity of Chicago Press, 2007); Robert J. Sampson, Neighborhood Effects: Social Structure and Community in the American City(Chicago: University of Chicago Press, forthcoming 2011).

9 Wim Bernasco and Richard Block, “Where Offenders Choose to Attack: A Discrete Choice Model of Robberies in Chicago,” Criminology47 (2009): 93 –130.

10 Robert J. Sampson, “Disparity and Diversity in the Contemporary City: Social (Dis)Order Revisited,”British Journal of Sociology60 (2009): 1 –31.

11 Robert J. Sampson and John H. Laub, “Structural Variations in Juvenile Court Processing:

Inequality, the Underclass, and Social Control,” Law and Society Review27 (1993): 285 –311.

12 Douglas S. Massey and Nancy Denton, American Apartheid: Segregation and the Making of the Underclass(Cambridge, Mass.: Harvard University Press, 1993); William J. Wilson, The Truly Disadvantaged: The Inner City, the Underclass, and Public Policy(Chicago: University of Chicago Press, 1987).

13 Robert J. Sampson, Stephen W. Raudenbush, and Felton Earls, “Neighborhoods and Vio- lent Crime: A Multilevel Study of Collective Ef½cacy,” Science277 (1997): 918 –924.

14 Bernasco and Block, “Where Offenders Choose to Attack.” 15 Sampson, “Disparity and Diversity in the Contemporary City.” 16 Western, Punishment and Inequality in America; Clear, Imprisoning Communities.

17 Skogan, Police and Community in Chicago; Thomas Marvell and Carlisle Moody, “Prison Population Growth and Crime Reduction,” Journal of Quantitative Criminology10 (1994):

109 –140. Robert J.

Sampson & Charles L o e ffl e r on mass incarcer- ation Dædalus Summer 2010 31 Punish- ment’s place 18 Daniel S. Nagin, Francis T. Cullen, and Cheryl Lero Jonson, “Imprisonment and Reoffend- ing,” in Crime and Justice, vol. 38, ed. Michael Tonry (Chicago: University of Chicago Press, 2009), 115 –200.

19 Jeremy Travis, But They All Come Back: Facing the Challenges of Prisoner Reentry(Washington, D.C.: Urban Institute Press, 2005).

20 Western, Punishment and Inequality in America; Todd R. Clear, Dina R. Rose, and Judith A.

Ryder, “Incarceration and Community: The Problem of Removing and Returning Offend- ers,” Crime and Delinquency47 (2001): 335 –351.

21 John R. Hipp, Joan Petersilia, and Susan Turner, “Parolee Recidivism in California: The Effect of Neighborhood Context and Social Service Agency Characteristics,” Criminology 48 (forthcoming 2010).

22 Clear, Rose, and Ryder, “Incarceration and Community.”