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

• Author: Matthew A. Valasik,Elizabeth Brault,Michael S. Barton
• DOI: 10.1177/0734016821996798
• Published date: 01 June 2021
• Date: 01 June 2021
• Subject Matter: Articles

Article

Disorder or Disadvantage:

Investigating the Tension

Between Neighborhood Social

Structure and the Physical

Environment on Local Violence

Michael S. Barton

1

, Matthew A. Valasik

1

,

and Elizabeth Brault

2

Abstract

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.

Keywords

environmental criminology, neighborhoods and crime, risk terrain modeling, egohoods, homicide

Introduction

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

1

Department of Sociology, Louisiana State University, Baton Rouge, LA, USA

2

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

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DOI: 10.1177/0734016821996798

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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