Social disorganization and police arrest trajectories
| Author | Ivan T Wong,John L Worrall |
| DOI | http://doi.org/10.1177/0032258X211032116 |
| Published date | 01 March 2023 |
| Date | 01 March 2023 |
| Subject Matter | Articles |
Article
The Police Journal:
Theory, Practice and Principles
2023, Vol. 96(1) 3–25
© The Author(s) 2021
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DOI: 10.1177/0032258X211032116
journals.sagepub.com/home/pjx
Social disorganization and
police arrest trajectories
Ivan T Wong
United States Army, Richardson, TX, USA
John L Worrall
University of Texas at Dallas, Richardson, TX, USA
Abstract
Prior police decision-making research is limited by (1) its emphasis on individual and
organizational predictors and (2) cross-sectional designs, which fail to account for the
time-varying aspects of police activities and the factors explaining them. Using group-
based trajectory modeling, this study tested the ability of social disorganization theory to
explain arrest activity at the Census block group level in Dallas, Texas. Social disor ga-
nization variables helped predict certain arrest trajectories, but not all of them. Spe-
cifically, socio-economic status was significant in low and medium arrest trajectory
groups. An interaction between racial heterogeneity and family disruption was also
significant in the medium arrest trajectory group. Theoretical implications are discussed.
Keywords
Arrest, social disorganization, group-based trajectory modeling
Social disorganization and police arrest trajectories
Researchers have long examined the correlates of police decision-making (e.g.,
Khruakham and Hoover, 2012;Paoline and Terrill, 2005;Worden, 1996). Most studies
have focused on officer-, suspect-, and situational- and organizational-level variables.
Comparatively fewer studies have looked at higher-level contextual factors, including
community conditions (e.g., Fagan and Davies, 2000;Terrill and Reisig, 2003). This
shortcoming is important because the National Research Council in 2004 reported that
community-level factors may be more significant in explaining police decision-making
Corresponding author:
John L Worrall, University of Texas at Dallas, 800 West Campbell Road, GR31, Richardson, TX 75080, USA.
Email: worrall@utdallas.edu
than lower-level factors (e.g., officer personalities, department policies, and suspect
demeanor). As such, there is a need for further exploration and identification of the
community-level (i.e., meso- and macro-level) correlates of officer decision-
making.
In an early study, Smith (1986) analyzed 60 U.S. neighborhoods and found that police
officers were more likely to make arrests in the lowest income neighborhoods. Moreover,
officers were more inclined to use force in racially heterogeneous neighborhoods. These
findings were echoed in the work of Terrill and Reisig (2003), who found that police
officers used force disproportionately in high-crime, disadvantaged neighborhoods. See
also Sun et al. (2008) continued in the same vein, finding that “police vigor”was driven in
large part by neighborhood conditions. Most recently, Martin and Kaminski (2021)
examined “police coercive actions”and found that certain indicators of social disor-
ganization were associated with officers’activities.
Some studies, however, have challenged the notion that ecological factors drive police
decision-making. For example, Klinger (1997) argued that police officers may be less
inclined to use coercive actions in disadvantaged neighborhoods because residents are
accustomed to crime in those areas. Similarly, officers working in disadvantagedareas
may be overworked and, as such, unable to target minor criminal events, even if they
wanted to, due to time constraints. Klinger’s thesis has received a measure of empirical
support in the work of Khruakham and Hoover (2012), who found that officers were
less likely to make arrests in disadvantaged areas. Other studies of Klinger’s“police
vigor”thesis report similar findings (e.g., Lautenschlager and Omori, 2018).
Recent advances notwithstanding, the research in this area remains rather underde-
veloped. For example, criminological research calls attention to the importance of time in
the relationship between ecological factors and crime (and by extension police decision-
making). In The Criminology of Place,Weisburd et al. (2012) argued that there are clearly
distinctive crime patterns over time. Using 16 years of crime data, they indeed found that
crime trends rise and fall over time. Their study developed crime trajectories at low levels
of analysis. To the extent crime and law enforcement activity are linked to one another, a
similar approach could shed light police decision-making.
Indeed, researchers have recently begun to explore trajectories of police productivity
over time. Worrall (2019) uncovered distinct trajectories of agencies’crime clearance
rates. Likewise, Scott et al. (2019) found there was considerable variation in crime
clearance rates over time. Combining this work with that of Weisburd et al. (2012),it
stands to reason that patterns of social disorganization and police coercive action also vary
over time. The current study explores this possibility with a focus on arrest trajectories and
their association with measures of social disorganization. In other words, we add a time
dimension to the recent and growing body of scholarship examining the ecological
correlates of police arrest activities.
To be sure, other criminological theories may explain police coercive actions. Col-
lective efficacy, for example, is a prime candidate. However, since most of the research on
higher-level predictors of police activity invokes social disorganization theory, we do the
same in the current study.
4The Police Journal: Theory, Practice and Principles 96(1)
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