Crime, Neighborhoods, and Units of Analysis: Putting Space in Its Place

Tita, George E.; Greenbaum, Robert T.

doi:10.1007/978-0-387-09688-9_7

Cited by 48 publications

(29 citation statements)

References 46 publications

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“…M. Kennedy et al, 1997;Papachristos, 2009;Papachristos et al, 2013;Tita & Greenbaum, 2009;Tita & Radil, 2011). Indeed, conflicts are often retaliatory in nature (Decker, 1996), and groups use violence as a form of justice to reciprocate a transgression or to respond to a threat by another group (Chinnici & Santino, 1989;Hopkins et al, 2013;Papachristos, 2009;Papachristos et al, 2013).…”

Section: Organized Crime-and Gang-related Violencementioning

confidence: 99%

Forecasting Organized Crime Homicides: Risk Terrain Modeling of Camorra Violence in Naples, Italy

Dugato

Calderoni

Berlusconi

2017

J Interpers Violence

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Mafia homicides are usually committed for retaliation, economic profit, or rivalry among groups. The variety of possible reasons suggests the inefficacy of a preventive approach. However, like most violent crimes, mafia homicides concentrate in space due to place-specific social and environmental features. Starting from the existing literature, this study applies the Risk Terrain Modeling approach to forecast the Camorra homicides in Naples, Italy. This approach is based on the identification and evaluation of the underlying risk factors able to affect the risk of a homicide. This information is then used to predict the most likely location of future events. The findings of this study demonstrate that past homicides, drug dealing, confiscated assets, and rivalries among groups make it possible to predict up to 85% of 2012 mafia homicides, identifying 11% of city areas at highest risk. By contrast, variables controlling for the socio-economic conditions of areas are not significantly related to the risk of homicide. Moreover, this study shows that, even in a restricted space, the same risk factors may combine in different ways, giving rise to areas of equal risk but requiring targeted remedies. These results provide an effective basis for short-and long-term targeted policing strategies against organized crime-and gang-related violence. A similar approach may also provide practitioners, policy makers, and local administrators in other countries with significant support in understanding and counteracting also other forms of violent behavior by gangs or organized crime groups.

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Section: Organized Crime-and Gang-related Violencementioning

confidence: 99%

Forecasting Organized Crime Homicides: Risk Terrain Modeling of Camorra Violence in Naples, Italy

Dugato

Calderoni

Berlusconi

2017

J Interpers Violence

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“…Spatial dynamics are arguably important in explaining the dynamic relationship between concentrated disadvantage, collective efficacy and violence and evidence suggests that disadvantaged neighborhoods with high levels of violence tend to co-exist in space (Morenoff et al, 2001;Mears and Bhati, 2006;Sampson, 2012;Tita and Greenbaum, 2009). …”

Section: Poverty Collective Efficacy and Violence: Their Spatial Andmentioning

confidence: 99%

Violence in Urban Neighborhoods: A Longitudinal Study of Collective Efficacy and Violent Crime

Hipp

Wickes

2016

J Quant Criminol

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A longitudinal study of collective efficacy and violent crime 2 Biography John R. Hipp is a Professor in the departments of Criminology, Law and Society, and Sociology, at the University of California Irvine. His research interests focus on how neighborhoods change over time, how that change both affects and is affected by neighborhood crime, and the role networks and institutions play in that change. He approaches these questions using quantitative methods as well as social network analysis. He has published substantive work in such journals as American Sociological Review, Criminology, American Journal of Public Health, Social Forces, Social Problems, Social Networks, Journal Objectives: Cross-sectional studies consistently find that neighborhoods with higher levels of collective efficacy experience fewer social problems. Particularly robust is the relationship between collective efficacy and violent crime, which holds regardless of the socio-structural conditions of neighborhoods.Yet due to the limited availability of neighborhood panel data, the temporal relationship between neighborhood structure, collective efficacy and crime is less well understood.Methods: In this paper, we provide an empirical test of the collective efficacy-crime association over time by bringing together multiple waves of survey and census data and counts of violent crime incident data collected across 148 neighborhoods in Brisbane, Australia. Utilizing three different longitudinal models that make different assumptions about the temporal nature of these relationships, we examine the reciprocal relationships between neighborhood features and collective efficacy with violent crime.We also consider the spatial embeddedness of these neighborhood characteristics and their association with collective efficacy and the concentration of violence longitudinally.Results: Notably, our findings reveal no direct relationship between collective efficacy and violent crime over time. However, we find a strong reciprocal relationship between collective efficacy and disadvantage and between disadvantage and violence, indicating an indirect relationship between collective efficacy and violence.Conclusions: The null direct effects for collective efficacy on crime in a longitudinal design suggest that this relationship may not be as straightforward as presumed in the literature. More longitudinal research is needed to understand the dynamics of disadvantage, collective efficacy, and violence in neighborhoods.

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“…Even though the network approach might be seen as a rival to gravity models, explicitly acknowledging and exploiting the interdependence of observations when explaining a construct of interest makes network models useful both methodologically (as an additional means to measure and control spatial effects) and theoretically. For further discussion about the application of this perspective on crime research, see Papachristos (2006) and Tita and Greenbaum (2009).…”

Section: Reasons To Expect Greater Attention To Be Paid To Spatial Aumentioning

confidence: 99%

“…Considerable empirical evidence exists indicating that ''place matters'' (Tita and Greenbaum 2009), and that often areal level variables are found to poorly explain the dependent variable in question. This is not so much of a surprise because many of the predictors of crime and criminality (e.g., poverty, unemployment, ethnic heterogeneity) are spatially autocorrelated.…”

Section: Types Of Studies Of Spatial Influence In Criminologymentioning

confidence: 99%

“…In the 1990s, a burgeoning research program unfolded about violence in North America (examples include: Morenoff and Sampson 1997;Cohen and Tita 1999;Messner et al 1999;Rosenfeld, Bray, and Egley 1999;Smith, Frazee, and Davison 2000). Tita and Greenbaum (2009) provide a cogent summary of this research, but conclude about the ecological tradition that ''though many plausible explanations have been offered, the empirical findings offer little in the way of supporting definitive statements on the exact nature of the processes that influence crime patterns across space'' (p. 146).…”

Section: Reasons Spatial Autocorrelation Has Had Limited Impact In Crmentioning

confidence: 99%

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Spatial Autocorrelation and Impacts on Criminology

Townsley

2009

Geographical Analysis

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Despite criminology's widespread application of geography, the full implications of Cliff and Ord's article have yet to be realized. In this essay the major types of spatial studies in criminology are outlined, followed by a depiction of the context of criminological research at the time the article was published. Next the major changes to the field occurring after the publication of Cliff and Ord's paper, focusing on technology advances and theory, are set out. Fortunately these changes mean the discipline is well placed to move beyond seeing the presence of spatial autocorrelation as a methodological issue that needs to be explained away.

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Crime, Neighborhoods, and Units of Analysis: Putting Space in Its Place

Cited by 48 publications

References 46 publications

Forecasting Organized Crime Homicides: Risk Terrain Modeling of Camorra Violence in Naples, Italy

Forecasting Organized Crime Homicides: Risk Terrain Modeling of Camorra Violence in Naples, Italy

Violence in Urban Neighborhoods: A Longitudinal Study of Collective Efficacy and Violent Crime

Spatial Autocorrelation and Impacts on Criminology

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