This article focuses on stability and change in “mixed middle-income” neighborhoods. We first analyze variation across nearly two decades for all neighborhoods in the United States and in the Chicago area, particularly. We then analyze a new longitudinal study of almost 700 Chicago adolescents over an 18-year span, including the extent to which they are exposed to different neighborhood income dynamics during the transition to young adulthood. The concentration of income extremes is persistent among neighborhoods, generally, but mixed middle-income neighborhoods are more fluid. Persistence also dominates among individuals, though Latino-Americans are much more likely than African Americans or whites to be exposed to mixed middle-income neighborhoods in the first place and to transition into them over time, even when adjusting for immigrant status, education, income, and residential mobility. The results here enhance our knowledge of the dynamics of income inequality at the neighborhood level, and the endurance of concentrated extremes suggests that policies seeking to promote mixed-income neighborhoods face greater odds than commonly thought.
The collection of large-scale administrative records in electronic form by many cities provides a new opportunity for the measurement and longitudinal tracking of neighborhood characteristics, but one that will require novel methodologies that convert such data into research-relevant measures. The authors illustrate these challenges by developing measures of “broken windows” from Boston’s constituent relationship management (CRM) system (aka 311 hotline). A 16-month archive of the CRM database contains more than 300,000 address-based requests for city services, many of which reference physical incivilities (e.g., graffiti removal). The authors carry out three ecometric analyses, each building on the previous one. Analysis 1 examines the content of the measure, identifying 28 items that constitute two independent constructs, private neglect and public denigration. Analysis 2 assesses the validity of the measure by using investigator-initiated neighborhood audits to examine the “civic response rate” across neighborhoods. Indicators of civic response were then extracted from the CRM database so that measurement adjustments could be automated. These adjustments were calibrated against measures of litter from the objective audits. Analysis 3 examines the reliability of the composite measure of physical disorder at different spatiotemporal windows, finding that census tracts can be measured at two-month intervals and census block groups at six-month intervals. The final measures are highly detailed, can be tracked longitudinally, and are virtually costless. This framework thus provides an example of how new forms of large-scale administrative data can yield ecometric measurement for urban science while illustrating the methodological challenges that must be addressed.
There is a paucity of research investigating the relationship of community-level characteristics such as collective efficacy and posttraumatic stress following disasters. We examine the association of collective efficacy with probable posttraumatic stress disorder and posttraumatic stress disorder symptom severity in Florida public health workers (n = 2249) exposed to the 2004 hurricane season using a multilevel approach. Anonymous questionnaires were distributed electronically to all Florida Department of Health personnel nine months after the 2004 hurricane season. The collected data were used to assess posttraumatic stress disorder and collective efficacy measured at both the individual and zip code levels. The majority of participants were female (80.42%), and ages ranged from 20 to 78 years (median = 49 years); 73.91% were European American, 13.25% were African American, and 8.65% were Hispanic. Using multi-level analysis, our data indicate that higher community-level and individual-level collective efficacy were associated with a lower likelihood of having posttraumatic stress disorder (OR = 0.93, CI = 0.88–0.98; and OR = 0.94, CI = 0.92–0.97, respectively), even after adjusting for individual sociodemographic variables, community socioeconomic characteristic variables, individual injury/damage, and community storm damage. Higher levels of community-level collective efficacy and individual-level collective efficacy were also associated with significantly lower posttraumatic stress disorder symptom severity (b = −0.22, p<0.01; and b = −0.17, p<0.01, respectively), after adjusting for the same covariates. Lower rates of posttraumatic stress disorder are associated with communities with higher collective efficacy. Programs enhancing community collective efficacy may be an important part of prevention practices and possibly lead to a reduction in the rate of posttraumatic stress disorder post-disaster.
In this response I focus on two major themes in Wacquant's trilogy: (1) punishment and the state; and (2) territorial stigmatization. I discuss evidence that supports elements of Wacquant's argument, while at the same time demonstrating the need for an account that brings mediating institutional processes of the state, violence, the civil sphere and neighbourhood mechanisms more fully into the larger theoretical picture. I conclude that ‘bottom-up’ processes of inequality must be integrated with ‘top-down’ forces of the state to advance our theoretical understanding of penality and spatial marginality in federated and unitary governments alike.
Gentrification has inspired considerable debate, but direct examination of its uneven evolution across time and space is rare. We address this gap by developing a conceptual framework on the social pathways of gentrification and introducing a method of systematic social observation using Google Street View to detect visible cues of neighborhood change. We argue that a durable racial hierarchy governs residential selection and, in turn, gentrifying neighborhoods. Integrating census data, police records, prior street-level observations, community surveys, proximity to amenities, and city budget data on capital investments, we find that the pace of gentrification in Chicago from 2007 to 2009 was negatively associated with the concentration of blacks and Latinos in neighborhoods that either showed signs of gentrification or were adjacent and still disinvested in 1995. Racial composition has a threshold effect, however, attenuating gentrification when the share of blacks in a neighborhood is greater than 40 percent. Consistent with theories of neighborhood stigma, we also find that collective perceptions of disorder, which are higher in poor minority neighborhoods, deter gentrification, while observed disorder does not. These results help explain the reproduction of neighborhood racial inequality amid urban transformation.
This article reviews the causal turn in the social sciences and accompanying efforts by criminologists to make policy claims more credible. Although there has been much progress in techniques for the estimation of causal effects, we find that the link between evidence and valid policy implications remains elusive. Drawing on criminological theory and research insights from disciplines such as sociology, economics, and statistics, we assess principles and strategies for informing policy in a causally uncertain world. We identify three distinct domains of inquiry that form a part of the translational process from evidence to policy and that complicate the straightforward exportation of causal effects to policy recommendations: (a) mechanisms and causal pathways, (b) effect heterogeneity, and (c) contextualization. We elaborate these three concepts by examining research on broken windows theory, policing, video games and violence, the Moving to Opportunity voucher experiment, incarceration, and especially the rich set of experimental studies on domestic violence that originated in Minneapolis, MN in the early 1980s. We also articulate a set of conceptual tools for advancing the goal of policy translation and offer recommendations for how what we call “policy graphs”—causal graphs used to analyze the policy implications of a system of causal relations—can potentially integrate the theoretical and policy arms of criminology.
I present a theoretical framework and analytic strategy for the study of place as a fundamental context in criminology, with a focus on neighborhood effects. My approach builds on the past 15 years of research from the Project on Human Development in Chicago Neighborhoods and from a recent book unifying the results. I argue that “ecometrics” can be applied at multiple scales, and I elaborate core principles and guiding hypotheses for five problems: 1) legacies of inequality and developmental neighborhood effects; 2) race, crime, and the new diversity; 3) cognition and context, above all the social meaning of disorder; 4) the measurement and sources of collective efficacy in a cosmopolitan world; and 5) higher order structures beyond the neighborhood that arise in complex urban systems. Although conceptually distinct, these hard problems are interdependent and ultimately linked to a frontier in criminology: contextual causality.
Official sanctioning of students by the criminal justice system is a long-hypothesized source of educational disadvantage, but its explanatory status remains unresolved. Few studies of the educational consequences of a criminal record account for alternative explanations such as low self-control, lack of parental supervision, deviant peers, and neighborhood disadvantage. Moreover, virtually no research on the effect of a criminal record has examined the ‘‘black box’’ of mediating mechanisms or the consequence of arrest for postsecondary educational attainment. Analyzing longitudinal data with multiple and independent assessments of theoretically relevant domains, the authors estimate the direct effect of arrest on later high school dropout and college enrollment for adolescents with otherwise equivalent neighborhood, school, family, peer, and individual characteristics as well as similar frequency of criminal offending. The authors present evidence that arrest has a substantively large and robust impact on dropping out of high school among Chicago public school students. They also find a significant gap in four-year college enrollment between arrested and otherwise similar youth without a criminal record. The authors also assess intervening mechanisms hypothesized to explain the process by which arrest disrupts the schooling process and, in turn, produces collateral educational damage. The results imply that institutional responses and disruptions in students’ educational trajectories, rather than social-psychological factors, are responsible for the arrest–education link.
Children growing up in poor versus affluent neighborhoods are more likely to spend time in prison, develop health problems and die at an early age. The question of how neighborhood conditions influence our behavior and health has attracted the attention of public health officials and scholars for generations. Online tools are now providing new opportunities to measure neighborhood features and may provide a cost effective way to advance our understanding of neighborhood effects on child health.
A virtual systematic social observation (SSO) study was conducted to test whether Google Street View could be used to reliably capture the neighborhood conditions of families participating in the Environmental-Risk (E-Risk) Longitudinal Twin Study. Multiple raters coded a subsample of 120 neighborhoods and convergent and discriminant validity was evaluated on the full sample of over 1,000 neighborhoods by linking virtual SSO measures to: (a) consumer based geo-demographic classifications of deprivation and health, (b) local resident surveys of disorder and safety, and (c) parent and teacher assessments of children’s antisocial behavior, prosocial behavior, and body mass index.
High levels of observed agreement were documented for signs of physical disorder, physical decay, dangerousness and street safety. Inter-rater agreement estimates fell within the moderate to substantial range for all of the scales (ICCs ranged from .48 to .91). Negative neighborhood features, including SSO-rated disorder and decay and dangerousness corresponded with local resident reports, demonstrated a graded relationship with census-defined indices of socioeconomic status, and predicted higher levels of antisocial behavior among local children. In addition, positive neighborhood features, including SSO-rated street safety and the percentage of green space, were associated with higher prosocial behavior and healthy weight status among children.
Our results support the use of Google Street View as a reliable and cost effective tool for measuring both negative and positive features of local neighborhoods.