Person:

Sampson, Robert

This article examines the connection of immigration and diversity to homicide by advancing a recently developed approach to modeling spatial dynamics—geographically weighted regression (GWR). In contrast to traditional global averaging, we argue on substantive grounds that neighborhood characteristics vary in their effects across neighborhood space, a process of “spatial heterogeneity.” Much like treatment-effect heterogeneity and distinct from spatial spillover, our analysis finds considerable evidence that neighborhood characteristics in Chicago vary significantly in predicting homicide, in some cases showing countervailing effects depending on spatial location. In general, however, immigrant concentration is either unrelated or inversely related to homicide, whereas language diversity is consistently linked to lower homicide. The results shed new light on the immigration-homicide nexus and suggest the pitfalls of global averaging models that hide the reality of a highly diversified and spatially stratified metropolis.

Research Summary 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.

Policy Implications Evidence, even if causal, does not necessarily inform policy. In fact, the question of “what works,” the focus of the growing evidence-based movement in criminology, turns out to be a different question than, “what will work?” Evidence-based policy research must therefore be concerned with much more than providing policymakers with research on causal effects, however precisely measured. The implication is that we must separate criminology’s increasing focus on causality from its policy turn and formally recognize that the latter requires a different standard of theory and evidence than does the former. In particular, criminologists interested in making policy claims must ask hard questions about the potential mechanisms through which a treatment influences an outcome, heterogeneous effects across people and time, contextual variations, and all of the real-world phenomena to which these challenges give rise—such as unintended consequences, policies that change incentive and opportunity structures, and the scale at which policies change in meaning. Theoretically guided causal graphs enhance this goal and help inform policy in a causally uncertain world. Translational criminology is ultimately a process that entails the constant interplay of theory, research, and practice.

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.

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.

Two landmark policy interventions to improve the lives of youth through neighborhood mobility—the Gautreaux program in Chicago and the Moving to Opportunity (MTO) experiments in five cities—have produced conflicting results and have created a puzzle with broad implications: Do residential moves between neighborhoods increase or decrease violence, or both? To address this question, we analyze data from a subsample of adolescents ages 9–12 years from the Project on Human Development in Chicago Neighborhoods, a longitudinal study of children and their families that began in Chicago—the site of the original Gautreaux program and one of the MTO experiments. We propose a dynamic modeling strategy to separate the effects of residential moving across three waves of the study from dimensions of neighborhood change and metropolitan location. The results reveal countervailing effects of mobility on trajectories of violence; whereas neighborhood moves within Chicago lead to an increased risk of violence, moves outside the city reduce violent offending and exposure to violence. The gap in violence between movers within and outside Chicago is explained not only by the racial and economic composition of the destination neighborhoods but also by the quality of school contexts, adolescents' perceived control over their new environment, and fear. These findings highlight the need to simultaneously consider residential mobility, mechanisms of neighborhood change, and the wider geography of structural opportunity.

Twenty-five years ago, William J. Wilson drew widespread attention to increases in the concentration of poverty in the United States and the diminished life chances of “the truly disadvantaged”. The hypothesis that growing up in a severely deprived neighborhood threatens well-being is rooted in a long scientific tradition. From Victorian London to present-day America, research has shown links between neighborhood poverty and outcomes such as crime, economic dependency, poor physical health, teenage pregnancy, and school dropout. But could the characteristics of individuals living in deprived neighborhoods explain these observed associations rather than the characteristics of the neighborhood itself? On page 1505 of this issue, Ludwig et al. address this question by analyzing the results of a policy project that supported neighborhood relocation.

Background: 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. Method: 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. Results: 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. Conclusions: 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.