Disorder or Disadvantage: Investigating the Tension Between Neighborhood Social Structure and the Physical Environment on Local Violence

Published date01 June 2021
Date01 June 2021
Subject MatterArticles
Disorder or Disadvantage:
Investigating the Tension
Between Neighborhood Social
Structure and the Physical
Environment on Local Violence
Michael S. Barton
, Matthew A. Valasik
and Elizabeth Brault
A renewed interest in understanding the relationship of the built environment with neighborhood
crime patterns has encouraged researchers to utilize novel methods (e.g., risk terrain modeling) to
better examine the influence of environmental risk factors on types of crime. The current study
engages with this research by operationalizing neighborhoods using Hipp and Boessen’s egohood
strategy and using Drawve’s aggregate neighborhood risk of crime measure to assess the rela-
tionship of a neighborhood’s physical environment with its spatial vulnerability of experiencing a
homicide. Findings demonstrate that the physical environment was a significant predictor of
neighborhood homicide; however, social structural neighborhood characteristics were more
important. This suggests crime prevention strategies like crime prevention though environmental
design or blight remediation may provide prudent and straightforward methods to inhibit lethal
violence in a community in the short run, but that addressing a neighborhood’s social structural
characteristics may be more effective at reducing homicides in the long term.
environmental criminology, neighborhoods and crime, risk terrain modeling, egohoods, homicide
Municipalities across the country have increasingly sought to address the root causes of crime with
strategies that target environmental factors associated with crime such as blight (Braga et al., 2015;
Wilcox et al., 2018). The broader research on neighborhood correlates of crime has drawn upon
Department of Sociology, Louisiana State University, Baton Rouge, LA, USA
Department of Criminology and Criminal Justice, Merrimack College, North Andover, MA, USA
Corresponding Author:
Michael S. Barton, Department of Sociology, Louisiana State University, Baton Rouge, LA, USA.
Email: mbarto3@lsu.edu
Criminal Justice Review
2021, Vol. 46(2) 134-155
ª2021 Georgia State University
Article reuse guidelines:
DOI: 10.1177/0734016821996798
several theoretical frameworks including the social disorganization framework, the broken windows
thesis, crime pattern theory, and routine activity theory to explain neighborhood crime patterns.
These frameworks differ regarding the specific predictors of higher neighborhood crime, but broadly
speaking argue that neighborhood crime levels were a function of a combination of socioeconomic
disadvantage as measured through population characteristics and opportunities to engage in crime
measured through environmental risk factors (Wilcox et al., 2018). These frameworks were often
assessed in competition with each other, which has led to questions about whether social charac-
teristics of neighborhood populations and environmental factors (such as blight or disorder) were
equal predictors of crime (Kim & Hipp, 2019; Sampson, 2012; Wilcox et al, 2018).
The discrepancies in findings were likely a function of variation in the operationalization of
neighborhood characteristics but may also be due to how neighborhoods were conceptualized.
For example, research on neighborhood correlates of crime operationalized neighborhoods
through census-based areal units (i.e., tracts, block groups, or blocks; Hipp, 20 07), community
areas (Skogan, 1990), neighborhood clusters (Sampson & Raudenbush, 1999), a four-block radius
of survey respondents (Rountree et al., 1994), and more recently egohoods (Hipp & Boessen, 2013;
Kim & Hipp, 2019). The variation in the unit of analysis was potentially important for two reasons.
First, neighborhood borders perceived by residents may not match well with administrative bound-
aries (Hipp & Boessen, 2013; Hipp, Wiliams & Boessen, 2018; Kirk & Laub, 2010). Second, recent
neighborhood-level research discussed the modifiable areal unit problem (MAUP), which refers to
the potential for relationships to operate differently depending on the unit of analysis used (Kim &
Hipp, 2019; Tita & Radil, 2010; Vogel, 2016).
The current study draws upon the broad range of theories of neighborhood correlates of crime to
examine whether social structural characteristics or environmental features of neighborhoods were
more strongly associated with homicides in Baton Rouge, LA. We make several contributions to the
research on neighborhood correlates of crime. First, we employ Drawve’s (2016; Thomas &
Drawve, 2018) aggregate neighborhood risk of crime (ANROC), by way of Caplan and Kennedy’s
(2016) risk terrain modeling (RTM), to examine the relationship of social structural characteristics
and environmental features with homicide. Second, we operationalize neighborhoods using Hipp
and Boessen’s (2013) egohood approach, which are created by drawing overlapping conce ntric
buffers around census blocks. We chose egohoods over other types of areal units of analysis because
they better approximate resident perceptions of neighborhood boundaries and therefore are more
useful for assessing the relationship of localized phenomenon with violent crime (Hipp & Bates,
2018; Kim & Hipp, 2019). The use of egohoods helps us to engage with the MAUP because they
provide a conceptual bridge across traditional census units including blocks, block groups, and
tracts. Finally, we expand research on neighborhood correlates of violence in medium size cities.
Literature Review
The spatial concentration of violence in cities has been well established (MacDonald & Stokes,
2020; Sampson, 2012; Valasik et al., 2019; Wilcox et al., 2018). The most used explanations for the
spatial concentration of violence included the social disorganization framework, geometry of crime/
routine activity perspective, and the broken windows thesis (McDonald & Stokes, 2020; Sampson,
2012; Wilcox et al., 2018). These frameworks emphasize the importance of different aspects of
neighborhoods, but all generally highlight the importance of population characteristics and oppor-
tunities for violence within neighborhoods.
The social disorganization framework highlighted the importance of the spatial distribution of
population characteristics. Specificall y, this framework argues crime and violence are sp atially
correlated with poverty, residential instability, and racial/ethnic heterogeneity because they lead
to tenuous social ties that decrease the effectiveness of informal social control (Sampson, 2012;
Barton et al. 135

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