Article

J Community Psychol. 2020;48:68–85.wileyonlinelibrary.com/journal/jcop68 | © 2019 Wiley Periodicals, Inc.

Received: 13 February 2019 | Revised: 25 November 2019 | Accepted: 26 November 2019

DOI: 10.1002/jcop.22299

R E S EARCH AR T I C L E

The influence of body‐worn cameras, minority threat, and place on police activity

Thomas W. Hughes1 | Bradley A. Campbell1 | Brian P. Schaefer2

1Department of Criminal Justice, University

of Louisville, Louisville, Kentucky

2School of Criminology and Security Studies,

Indiana State University, Terre Haute, Indiana

Correspondence

Brian P. Schaefer, Indiana State University,

Terre Haute, IN.

Email: [email protected]

Abstract

Police practices evolve and are often shaped by techno-

logical innovation, such as the adoption of body‐worn

cameras (BWCs). While initial research on their impact is

evergrowing, researchers have neglected to examine if

their use is influenced by neighborhood characteristics.

This study examines the influence of a BWC implementa-

tion on police activity and enforcement practices across

neighborhoods, using minority threat hypothesis and

place theory to explain the relationship. We used pre‐ and postimplementation enforcement data to examine

the influence of BWCs and community characteristics on

the actions taken by Louisville Metro Police Department

officers. Ten ordinary least squares models were used to

analyze the enforcement changes including self‐initiated activity, total enforcement, felony arrests, low‐level arrests, and low‐level citations. Our findings indicate

BWCs implementation was associated with a decrease in

low‐level citations; however, self‐initiated activity and

felony and low‐level arrests were unaffected. Also,

concentrated disadvantage was associated with a de-

crease in self‐initiated activity. We also examined the

moderating effects between BWCs and neighborhood

characteristics and found BWCs were correlated with a

decrease in low‐level citations. The implications of the

findings are discussed.

1 | INTRODUCTION

The criminal justice system plays a central role in efforts to maintain social order in the United States. Within this

system, the police are of particular importance. The police in the United States are granted substantial

discretionary authority to intervene in the lives of the public. Police function “as a mechanism for distributing

nonnegotiable coercive force in accordance with an intuitive grasp of situational threats to social order” (Bittner,

1975, p. 46). By design, police are equipped and entitled to use coercion (Bittner, 1985). The exercise of this power

can have a substantial impact on a civilian’s privacy, freedom, or their very life (Goldstein, 1977). Moreover, police

actions largely establish the inputs for the remaining subunits of the criminal justice system (Goldstein, 1959). Thus,

police actions have powerful ramifications at the moment and potent downstream effects on the rest of the

criminal justice system.

Police actions and decisions in the field have been the focus of substantial research. Yet, recent high‐profile incidents of police use of force have generated greater political and social salience to this matter. Flowing from this

have been greater calls for oversight and review of police decisions. Body‐worn cameras (BWCs) are one

organizationally based measure that has been strongly advocated to address these concerns (Wallace, White, Gaub,

& Todak, 2018). Research finds positive outcomes related to BWCs, including reduction in use of force and resident

complaints (see e.g., Ariel, Farrar, & Sutherland, 2015; Hedberg, Katz, & Choate, 2017) and increased prosecution of

intimate partner violence (IPV) cases (Morrow, Katz, & Choate, 2016). A further line of inquiry has examined BWC

effects on police activity, including initiating an activity or making an arrest (Braga, Sousa, Coldren, & Rodriguez,

2018; Ready & Young, 2015; Wallace et al., 2018). The results of this line of inquiry are mixed, suggesting the local

context of the agencies under examination matters in understanding officer’s discretionary decisions to arrest.

One way to explore the impact of this local context is to examine how BWCs are influencing officer activities at

the neighborhood level. While policy and law may structure the conduct of officers, their discretionary decisions in

most microlevel interactions are of low visibility (Schulenberg, 2015). BWCs, through their associated recordings,

have the potential to both expose discretionary decisions made in the field and subject them to review. Policing

necessarily involves the exercise of judgment and the making of choices. Officers are given substantial discretion in

how they respond to calls for service (CFS). Officers possess even greater discretion in conducting unassigned

actions (volitional acts free from CFS) as they are free to determine both the substantive focus of any action as well

as the methods and tactics they will use. The actions are taken and methods used by police officers during their

unassigned times represent a second source of crime policy, a de facto policy flowing from officer discretion and the

aggregation of their street‐level decisions (Famega, Frank, & Mazerolle, 2005).

What might shape such officer derived crime policy? Policing scholarship hypothesizes police practices may be

understood by examining a location’s level of social disorganization, wealth, and racial composition (Smith &

Holmes, 2014). Minority threat hypothesis and place theory are often used to understand the structural conditions

related to police decision‐making and behavior (see e.g., Holmes, 2018; Lautenschlager & Omori, 2019; Parker,

Stults, & Rice, 2005; Smith & Holmes, 2014). Minority threat theory holds those in dominant social groups seek to

defend their position against encroachment by minority populations. One method to maintain the current social

arrangement is the targeted use of crime‐control efforts (Wietzer, 2017). Place theory argues the characteristics of

places are mesolevel attributes influencing a wide variety of policing outcomes. For example, concentrated

disadvantage and segregation are clustered in cities and establish conflicting perceptions and strained patterns of

interactions between police and minority residents. As a result, the police patrolling such areas may more

frequently perceive the need for and deploy the use of coercive force (Smith & Holmes, 2014).

As such, this study seeks to understand the influence of BWCs on a range of police behaviors while accounting

for neighborhood context. Specifically, the study uses the minority threat hypothesis and place theory to

understand neighborhood variation in police activity before and after BWC deployment. The study begins with a

review of existing literature examining the impact of BWCs on policing. Next, minority threat and place theories are

HUGHES ET AL. | 69

explained and their empirical support is reviewed. The study then describes the data and methods utilized, as well

as the results of the study. Finally, there is a discussion of the findings and directions for future research.

2 | LITERATURE REVIEW

2.1 | BWCs and community accountability

Recent years have seen an increase in the political salience of police behavior. Calls for greater police transparency

and accountability have followed several high‐profile deaths of community members involved in police interactions.

BWCs are one policy proposal advocated to enhance community accountability of the police. The diffusion of BWC

technology has been supported politically and through federal funding efforts; however, police have not universally

welcomed adoption of BWCs (Huff, Katz, & Webb, 2018).

BWCs are hypothesized to foster mannerly behavior in the field (Hedberg et al., 2017). The presence of a BWC

may lead officers and civilians to alter their behavior due to having their actions monitored (Farrar & Ariel, 2013).

Cameras may increase the self‐awareness of the parties involved in a police–civilian interaction and thus deter poor

behavior. As a result, officers may be more likely to adhere to departmental policies and civilians are more likely to

avoid negative behavior (e.g., resist officer commands) during interactions with officers (Farrar & Ariel, 2013).

Recordings also enhance the review of police–civilian interactions by providing objective evidence of a specific

encounter (Maskaly, Donner, Jennings, Ariel, & Sutherland, 2017), provided officers comply with departmental

policies and activate their BWCs when required (Annual Report, 2017; Hedberg et al., 2017; McClure et al., 2017).

The initial adoption of BWCs has been studied in a variety of jurisdictions, though findings have been mixed

(Ariel, Farrar, & Sutherland, 2015; Ariel et al., 2016; Yokum, Ravishankar, & Coppock, 2017). In general, the

research shows the adoption of BWCs results in significant declines in civilian complaints against the police and or

police officer use of force incidents (Ariel et al., 2015; Braga et al., 2018; Hedberg et al., 2017; Jennings, Lynch, &

Fridell, 2015; Katz, Choate, Ready, & Nuno, 2014; Schaefer, Campbell, & Hughes, 2018).

A related line of research has begun to examine the impact of BWCs on officer activities beyond their potential

impact on the use of force (Maskaly et al., 2017). Researchers have found mixed results regarding BWCs impact

self‐initiated activity, stop‐and‐frisk practices, the issuance of citations, and arrest decisions (Braga, Coldren, Sousa,

Rodriguez, & Alper, 2017; Morrow et al., 2016; Ready & Young, 2015; Wallace et al., 2018). In a quasi‐experimental

design, Katz et al. (2014) found the implementation of BWCs led to a 17% increase in the number of arrests for

BWC‐wearing officers compared with non‐BWC officers. Ready and Young (2015) conducted a quasi‐experimental

design comparing BWC‐wearing officers with non‐BWC officers by analyzing the number of field contact reports

over a 10‐month period post‐BWC implementation. Their analysis found officers wearing BWCs were less likely to

conduct stop‐and‐frisks or make arrests, but officers with cameras were more likely to give citations and initiate

encounters.

In subsequent research, Braga et al. (2017) also conducted a randomized control trial in Las Vegas and found

BWC‐wearing officers made more arrests and wrote more citations than non‐BWC officers. Furthermore, the

number of arrests and citations increased by 5.2% for officers wearing cameras. Morrow et al. (2016) examined the

influence of BWCs on IPV investigations. Their research found officers with BWCs were more likely to make an

arrest compared to officers without cameras. Furthermore, their findings found IPV cases with BWC footage

increased the likelihood charges were filed, were more likely to have the case furthered by the district attorney,

and result in a conviction. Wallace et al. (2018) examined the effect of BWC implementation across officer self‐ initiated activity and arrests, as well as their response time and time on scene in Spokane, Washington. Using a

random‐control experimental design, the study found no statistically significant difference in activity levels

between BWC‐wearing and non‐BWC‐wearing officers, suggesting camera‐induced depolicing did not occur.

70 | HUGHES ET AL.

To date, our understanding of the impact of BWCs on officer behavior remains limited (Lum, Koper, Merola,

Scherer, & Reioux, 2015; Lum, Stoltz, Koper, & Scherer, 2019). Scholars have called for the study of police behavior

across a wide variety of social contexts (D’Alessio, & Stolzenberg, 2003). One outstanding question regarding

BWCs and police activity is the impact of community context. We know neighborhoods shape police behavior

(Kane, 2002; Klinger, 1997; Mastrofski, Reisig, & McCluskey, 2002; Smith & Holmes, 2014). Furthermore, the

minority threat hypotheses and place theory argue the racial composition and concentrated disadvantage of

neighborhoods influence officer behavior (Smith & Holmes, 2014). Thus, it is important to examine how

neighborhood characteristics influence policy activity before and after BWC implementation.

2.2 | Minority threat hypothesis

Issues surrounding the treatment of minorities have vexed the United States since its inception. Minority groups have

frequently been the target of derision and oppression by members of existing power structures. According to conflict

theory, these actions are the product of attempts to achieve or maintain social power. Those with such power see

minorities as a threat and seek to manipulate the law and its enforcement to maintain their current station (Quinney,

1970; Sellin, 1938; Turk, 1969). Substantial minority populations represent competition for opportunities as well as

potential challenges to the established social hierarchy. In response to this endangerment of social position, political

power is used to vitiate threats posed by minority groups (Holmes, 2000). Flowing from this theoretical position is the

minority threat hypothesis, which posits a relationship between the presence of minorities and levels of crime control

(Blalock, 1967; Weitzer, 2017). Popular stereotypes often cast minorities (ethnic or racial) as perpetrators of crime

(Holmes & Smith, 2008). These views can be reinforced by media representations of crime and victimization

(Bjornstrom, Kaufman, Peterson, & Slater, 2010). As a result, the presence of such minorities is thought to increases

the fear of crime and to generate enhanced crime control (Holmes, 2000; Parker et al., 2005).

Two general explanations of the relationship between minority representation and the potential implementa-

tion of coercive crime‐control efforts targeting minorities have been advanced. Some have advanced a self‐limiting

(curvilinear) model in which, as a minority population initially grows, formal social control targeted against it

increases (Smith & Holmes, 2014). Formal social control can result in increased crime rates as officers detect more

activity that is criminal and as residents stop viewing the police as legitimate authorities (Brunson & Miller, 2006).

However, once a minority representation reaches a political critical mass, mobilization of social control against it

will decline as the minority group may now neutralize such efforts with its motive political power (Smith &

Holmes, 2014).

Another view holds that there is a consistent linear relationship between minority representation and the

distribution of crime‐control efforts irrespective of a minority population representation. Under the linear threat

hypothesis, a minority representation never reaches a political threshold allowing mediation of targeted crime‐ control initiatives (Holmes, 2018). For example, coercive crime‐control actions may flow from the intersection of

the structural disadvantages of places and the established dynamics of intergroup relations between police and

minorities (Blumer, 1958; Holmes & Smith, 2008, Wietzer, 2017). The concerns of police, particularly their

subculture and interests, shape the outcomes of place specific intergroup interactions to drive police actions.

Through this ecological contamination of racially segregated areas, street‐level officers perceive minorities as

threats to their safety (Weitzer, 2017). Officers’ perceptions of minority neighborhoods may flow from and be

reinforced by an areas’ violent crime rate, officer war stories, departmental folklore, and the operation of cognitive

biases. As the percentage of minorities or a particular minority grows in an area, the police perception of risk and

danger is amplified (Smith & Holmes, 2014). This, in turn, may increase the likelihood that police will utilize pre‐ emptive or aggressive tactics in direct relation to minority populations. “Big events,” those “loaded with great

collective significance,” like the killing of an officer or the beating of a minority resident by the police, can shape and

reinforce established group differences between police and minority residents (Blumer, 1958, p. 6). Such events

HUGHES ET AL. | 71

bolster police solidarity, enhance police perception of peril, and shape their policing behavior to circumvent the

political will of ascendant or dominant minority groups. Therefore, the election of police to use coercive methods

may in large part be driven by the police subculture and police interests intersecting with structural disadvantage

and intergroup conflict. If true, police street level decisions are little influenced by larger political forces and a linear

relationship between minority representation and crime‐control can be maintained (Holmes & Smith, 2008; Smith &

Holmes, 2014).

Researchers have found general support for the minority threat hypothesis in relation to police behavior. For

instance, minority threat perspective has been used to explain police force size (Holmes, Smith, Freng, & Muñoz,

2008), the number of police full time employees (Greenberg, Kessler, & Loftin, 1985); per capita expenditures on

policing (Holmes et al., 2008); precinct deployment levels (Kane, 2003); number of civil rights complaints in certain

circumstances (Holmes, 2000; Smith & Holmes, 2003), and police use of force (Holmes, Painter, & Smith, 2018;

Lautenschlager & Omori, 2019).

There is a large body of research examining minority threats on officer enforcement decisions. For instance,

several studies have examined arrest decisions (D’Alessio & Stolzenberg, 2003; Kane, Gustafson, & Bruell, 2013;

Liska & Chamlin, 1984; Ousey & Lee, 2008; Parker et al., 2005; Stolzenberg, D’Alessio, & Eitle, 2004) and traffic

enforcement (Novak & Chamlin, 2012; Petrocelli, Piquero, & Smith, 2003). Misdemeanor arrests are a common and

useful outcome for understanding minority threat, as they are highly discretionary (Ousey & Lee, 2008). Several

studies have used arrests as outcomes in a test of minority threat hypothesis. For example, Eitle and Monahan

(2009) examined police and community‐level factors in 264 US cities, finding racial inequalities were associated

with Black drug arrest rates. Similarly, Ousey and Lee (2008) found higher arrest rates for drug and weapons in

cities with an uneven distribution of Black and White residents. However, this disparity did not exist for violent and

property crime. In a recent study, Morrow, Berthelot, and Vickovic (2018) also examined the racial threat

hypothesis, analyzing 2012 Terry stop data from the New York City Police Department. At the precinct level,

researchers found that percent Black or Hispanic did not predict the likelihood of officer use of force (nonweapon

or weapon) during a Terry interaction. An examination of the interaction between an individual’s race or ethnicity

and the racial or ethnic composition of a precinct found differences in the use of the police force. Specifically, as

percent Black increased in an area, Blacks had lower odds of experiencing a nonweapon use of force relative to

Whites. Yet, as percent Hispanic increased in areas, Hispanics had an increased likelihood or experiencing police

use force (nonweapon and weapon) relative to Whites.

2.3 | Place theories

Place theories recognize that the numerical representation of minorities does not fully explain the perception of

racial threat or its associated coercive responses (Holmes, 2018; Holmes et al., 2018; Smith & Holmes, 2014). In

policing scholarship, scholars argue neighborhoods shape police behavior (Kane, 2002; Klinger, 1997; Mastrofski

et al., 2002; Smith & Holmes, 2003, 2014). Examining neighborhoods allows researchers to consider the unique

intervening contextual forces that may mediate or influence the behavior of the police (Holmes, 2018). Critical to a

full understanding is the influences of the “ecological or spatial characteristics of cities” (Holmes, 2018, p.150). A

variety of social forces, like racial segregation and concentrated disadvantage, create distinct experiences with

police coercion and create neighborhood enclaves within a city (Skogan, 1990). This division and the resulting

variation in the nature of neighborhoods shapes how policing is conducted at both the organizational and street

level, where places vary in their perceived need for crime control and the perception of such a need is often tied to

the race and stereotyped morality of its residents (Holmes & Smith, 2008; Klinger, 1997). Officers learn or develop

cognitive maps regarding the boundaries of such areas and their associated dangers. Organizationally, these areas

may be targeted for more aggressive police models (e.g., broken windows), increasing the likelihood of residents to

come into contact with police via aggressive crime‐control strategies (Brunson & Miller, 2006; Weitzer, 2017).

72 | HUGHES ET AL.

Research shows concentrated disadvantage can influence policing practices. The presence of concentrated

disadvantage can hinder a community’s ability to exercise informal social control (Kornhauser, 1978). As a result,

the police step in as agents of control in the forms of police stops and enforcement actions (Manning, 1978; Parker

et al., 2005; Parker, MacDonald, Alpert, Smith, & Piquero, 2004). Visible signs of disorder and a decrease in informal

social control can increase police presence through objective or subjective perceptions of criminal activity by the

police (Kane, 2002; Parker et al., 2004). Furthermore, neighborhoods that experienced historical patterns of racial

segregation and concentrated disadvantage are also perceived to require additional police presence (Massey &

Denton, 1993). Research shows the police are more active in economically isolated and disadvantage

neighborhoods, as the police perceive these spaces as requiring harsh discipline to eliminate criminal activity

(Fagan, Geller, Davies, & West, 2009). Thus, concentrated disadvantage plays a key role in how law enforcement

strategies and practices are related to the meaning attached to a given neighborhood.

The residents of minority and disadvantaged neighborhoods targeted with aggressive law enforcement

paradigms develop feelings of resentment for increased police surveillance and coercive contact, feelings

potentially manifested in the resistance and avoidance of police (Weitzer & Brunson, 2009). The feelings of

resentment and defiant behavior can result in officers creating stereotypes that all residents of an area are

threatening to officer safety and thus warrant a coercive posture or violent response (Holmes, 2018). With time,

certain places may become so associated with crime and danger that entry into these areas by officers elicits the

conditioned response of fear and a reflexive predisposing toward coercion (Smith & Holmes, 2014). Thus, “the bad

part of town” can receive aggressive and coercive policing from both police organizational decisions and the

exercise of discretion by individual officers on the street (Correll et al., 2007). In sum, place theory posits that

higher levels of coercion in minority areas flow from the complex interplay of variables at differing levels of analysis

(micro, meso, and macro). Increased crime rates or perceived disorder increases the likelihood of proactive policing,

subsequent resentment by residents leads to officers perceiving the area in a negative light, negatively influencing

the cognitive maps officers’ use to police the areas.

Researchers have examined officer enforcement decisions across neighborhoods, looking at the role

concentrated disadvantage plays in shaping officer behavior across communities. For instance, D. A. Smith

(1986) found neighborhoods with greater racial heterogeneity experienced increased stops of suspicious persons.

Similarly, Fagan and Davies (2000) found increases in arrests for persons in greater economically disadvantaged

communities. Furthermore, research finds perceptions of the disorder are racialized, like neighborhoods with high

concentrations of poverty but greater numbers of minority residents are perceived as more disorderly compared to

impoverished neighborhoods with higher White populations (Sampson & Raudenbush, 2004). Parker et al. (2004)

examined racial profiling by policing across communities and found the presence of disorder coincided with

increases in proactive policing. Parker et al. (2004) suggest that the lack of informal social control may increase

crime, which in turn will increase police contact in these neighborhoods. Increased police contacts and proactive

activities can result in increased arrests or use of force in disorderly neighborhoods.

Finally, Parker, MacDonald, Jennings, and Alpert (2005) analyzed data regarding the use of force from 73 cities with a

population of 100,000 residents or more. They explored the relationship between police use of force and variables relating

to racial threat, structural disadvantage, police unionization, and accreditation, as well as a city’s political climate. Their

results indicate that the use of force by police was not directly affected by an increase in the Black population. The analysis

did reveal a positive association between use of force and residential mobility, but no significant direct relationship was

found between a composite measure of disadvantage and police use of force. Interestingly, the presence of Black mayors

and police unions were found to be related to higher aggregate levels of police use of force.

Overall, the literature has found mixed results regarding the impact of the minority threat hypothesis (Weitzer,

2017) and place hypothesis (Smith & Holmes, 2014). One area which has to date not been studied is the potential

influence of BWCs on police activities accounting for community context.

HUGHES ET AL. | 73

3 | METHODS

In the current study, we analyzed data from the Louisville, Kentucky Metropolitan Police Department (LMPD) and

the US Census Bureau to examine the impact of community characteristics and BWC deployment on enforcement

actions by police officers. The LMPD serves a community of 771,158 people and is responsible for covering

approximately 398 square miles. According to the 2010 US Census, LMPD’s jurisdiction was comprised of roughly

75% White and 22% Black residents. The jurisdiction contained more than 287,000 households, of which 30% had

children below the age of 18, and the median household income was just under $40,000 (US Census Bureau, 2015).

In 2010, there were 3,734 violent crimes and 29,551 property crimes reported to the LMPD (Federal Bureau of

Investigation, 2019).

In July of 2015, the LMPD implemented BWCs, mandating that all officers serving in a patrol function wear

BWCs during a regular patrol. More specifically, LMPD policy required that all patrol officers turn on BWCs to

record any interaction with the public for law enforcement purposes (e.g., traffic stop, pedestrian stop, response to

incident, etc.). As discussed previously, research has not examined the impact of BWCs and neighborhood

characteristics on the enforcement action taken by law enforcement officers. Thus, we used both preimplementa-

tion and postimplementation data to assess the impact of BWCs and community characteristics on enforcement

actions taken by LMPD officers. Using these data, we sought to answer the following research questions:

Do BWCs influence officer enforcement practices while controlling for neighborhood characteristics, including

percent minority and concentrated disadvantage?

Do BWCs impact officer self‐initiated activity while controlling for neighborhood characteristics, including percent

minority and concentrated disadvantage?

Does the influence of BWCs on officer behavior differ by neighborhood characteristics?

To answer these research questions, we analyzed community data at the census tract level merged with LMPD

enforcement data. Although the LMPD is the largest police department operating in Louisville, several census tracts are

served by smaller police departments. As such, we included 145 tracts that were patrolled primarily by LMPD. These

145 census tracts accounted for more than 50% of all tracts in the city of Louisville, KY. The LMPD enforcement data

for this study include 1 year of pre‐ and post‐BWC implementation data. Thus, we have 6 months of pre‐BWC data and

6 months of post‐BWC data. Coupled with census data at the tract level, the LMPD enforcement data allow us to

examine any changes in the level of enforcement and self‐initiated activity.1 Below, we describe our dependent and

independent variables, followed by a discussion of our analytic strategy.

3.1 | Dependent variables

In this study, we examine the impact of BWCs and community characteristics on five dependent variables: (a) Self‐ initiated officer activity (e.g., traffic stops and questioning of civilians), (b) overall enforcement activity (e.g., arrests

and citations), (c) felony arrests, (d) lower level arrest (i.e., arrests for misdemeanors and violations), and (e) lower‐ level citations (i.e., citations for misdemeanors and violations). For each of these outcome variables, aggregate

counts of pre‐ and post‐BWC enforcement actions were compiled for each census tract. Pre‐ and post‐BWC counts

for each outcome variable are presented to model the effects of BWCs and neighborhood characteristics on

aggregate counts of self‐initiated activity and enforcement practices. Modeling the data in this manner gives us a

1Based on the nature of these data, we are only able to assess the effects of BWCs on changes in our outcome variables—enforcement practices and self‐ initiated activity—in the short‐term. In other words, we are only able to assess 6 months of post‐BWC data and are unable to examine longer‐term trends

in enforcement and self‐initiated activity.

74 | HUGHES ET AL.

sample of counts for 145 pre‐BWC census tracts and 145 post‐BWC census tracts that are included in our analysis

(N = 290). Descriptive statistics for our dependent variables are displayed in Table 1, including the mean for each

variable during the pre‐ and post‐BWC periods, as well as the overall, mean for our full sample. Descriptive

statistics revealed that all four of the enforcement activities measured in this study decreased following BWC

implementation and self‐initiated activity was the only action that increased following BWC implementation.

Felony and low‐level arrests saw the smallest drop, whereas low‐level citations (misdemeanor and violations) had

considerable reductions in activity levels. Given the increase in self‐initiated activity, the descriptive statistics

would suggest officers were still conducting investigative activities but were not issuing citations for low‐level violations and misdemeanors.

3.2 | Independent variables

To assess the impact of BWCs and minority threat on police activity and enforcement actions, we used data from

the 2010 US Census to create community measures of minority threat and economic disadvantage for each census

tract. Our primary independent variables include the implementation of BWCs in July of 2015 and the percentage

of Black residents—minority threat—residing in each census tract, and concentrated disadvantage—concentrated

disadvantage—which was a composite scale comprised of the percentage of people living below the poverty line

(percent poverty), percent of female‐headed households with children (percent female household), and the percentage

of population receiving Supplemental Nutrition Assistance Program (SNAP) benefits (percent SNAP).2 Finally, we

TABLE 1 Mean pre‐BWC, post‐BWC enforcement actions

Variable

Pre‐BWC Post‐BWC Full sample

(n = 145) (n = 145) (N = 290)

Mean Mean Mean

SD SD SD

(Range) (Range) (Range)

Self‐initiated 384.61 420.08 402.34

292.95 411.69 357.11

(49–2,468) (102–3,810) (49–2,810)

Total enforcement 408.68 353.05 380.86 466.19 390.24 430.06 (0–3,948) (0–3,029) (0–3,948)

Felony arrests 38.01 35.96 36.99

65.21 51.52 59.11

(0–498) (0–468) (0–498)

Low‐level arrests 109.59 101.26 105.42 146.01 128.27 137.25 (0–1,153) (0–941) (0–1,153)

Low‐level citation 200.22 149.02 174.62

243.18 170.26 211.11

(0–1,673) (0–1,111) (0–1,673)

Abbreviations: BWC, body‐worn camera; SD, standard deviation.

2Principal components analysis (PCA) was used to create our concentrated disadvantage scale. We included three measures of concentrated disadvantage

(e.g., percent poverty, percent female household, and percent snap) in our PCA. Results indicated a one‐factor solution with factor scores ranging from

0.553 to 0.743 and an eigenvalue of 1.309.

HUGHES ET AL. | 75

also controlled for the overall crime rate in each of the census tracts, measured by the number of property and

violent crimes per 1,000 residents, and the number of residents residing in each census tract (population).

Descriptive statistics for each independent variable are presented in Table 2. On average, the population of census

tracts included 3,914.32 people and were 27% Black. An average of 35% of households were under the poverty

level, 21% were headed by a female, and 15% received SNAP benefits. Finally, the average crime rate across tracts

was 128.15, including both violent and property crimes.

3.3 | Analytic strategy

To answer our research questions, we estimated 10 ordinary least squares (OLS) models to assess the impact of

LMPD’s implementation of BWCs and neighborhood characteristics on officers’ self‐initiated activity and

enforcement practices. To answer research questions 1 and 2, we present five main effects models, which include

only our primary independent variables. To answer research question 3, we created mean‐centered interaction

terms for all of our neighborhood characteristics (e.g., population, percent Black, concentrated disadvantage, and

crime per 1,000 residents) and regressed them on each dependent variable. Each of these models is presented in

Table 3. The main effects models for each dependent variable are under the “1” column, while the interaction

effects models are under the “2” column. We present the standardized coefficients and effect sizes for each

variable.3

4 | RESULTS

4.1 | Main effects

Table 3 displays the standardized coefficients for each of our five models. For self‐initiated activity, our OLS model

did not find that BWC implementation was significantly correlated with levels of self‐initiated activity; however, the

TABLE 2 Mean descriptive statistics for independent variables

Variables Mean SD Range

BWCs 0.50 0.50 0–1

Population 3,914.32 1,386.86 1,490–7,683

Minority threat

Percent Black 0.27 0.29 0.03–0.99

Concentrated disadvantage 0.69 0.22 0.23–1.23

Percent poverty 0.35 0.16 0.07–0.82

Percent female household 0.21 0.10 0.06–0.56

Percent SNAP 0.15 0.14 0.00–0.71

Crime per 1,000 128.15 111.26 0.18–676.52

Abbreviations: BWCs, body‐worn cameras; SD, standard deviation; SNAP, Supplemental Nutrition Assistance Program.

3To calculate Cohen’s d, or standardized mean difference effect sizes for each of our independent variables, we used Wilson’s Practical Meta‐Analysis Effect Size Calculator (found here http://www.campbellcollaboration.org/escalc/html/EffectSizeCalculator‐SMD‐main.php). Based on Cohen’s (1992)

recommendations for interpreting the magnitude of d, 0.2 is interpreted as a small effect, 0.5 represents a medium effect, and 0.8 is interpreted as a large

effect.

76 | HUGHES ET AL.

T A B L E

3 O LS

re gr es si o n im

p ac t o f B W

C an

d n ei gh

b o rh o o d ch

ar ac te ri st ic s o n o u tc o m e va

ri ab

le s

Se lf ‐in

it ia te d

T o ta l en

fo rc e

F el o n y ar re st

Lo w ‐le

ve l ar re st

Lo w ‐le

ve l ci te

V ar ia b le

1 2

1 2

1 2

1 2

1 2

B (d )

B (d )

B (d )

B (d )

B (d )

B (d )

B (d )

B (d )

B (d )

B (d )

B o d y‐ w o rn

ca m er a

va ri ab

le s (B W

C )

0 .0 5 (0 .1 0 )

0 .0 5 (0 .1 0 )

− 0 .0 7 † (− 0 .1 4 )

− 0 .0 5 (− 0 .1 0 )

− 0 .0 2 (− 0 .0 4 )

− 0 .0 2 (− 0 .0 4 )

− 0 .0 3 (− 0 .0 6 )

− 0 .0 2 (− 0 .0 4 )

− 0 .1 2 * (− 0 .2 4 )

− 0 .1 0 * (− 0 .2 0 )

P o p u la ti o n (P o p )

0 .3 3 * (0 .7 0 )

0 .3 2 * (0 .6 8 )

0 .3 1 * (0 .6 5 )

0 .3 3 * (0 .7 0 )

0 .2 6 * (0 .5 4 )

0 .2 6 * (0 .5 4 )

0 .3 2 * (0 .6 8 )

0 .3 5 * (0 .7 5 )

0 .2 9 * (0 .6 1 )

0 .3 0 * (0 .6 3 )

P er ce n t B la ck

(P B )

0 .0 9 † (0 .1 8 )

− 0 .0 2 (− 0 .0 4 )

− 0 .0 7 (− 0 .1 4 )

− 0 .0 9 (− 0 .1 8 )

0 .0 8 † (0 .1 6 )

0 .2 1 * (0 .4 3 )

− 0 .0 1 (− 0 .0 2 )

0 .0 1 (0 .0 2 )

− 0 .1 1 † (− 0 .2 2 )

0 .1 6 † (0 .3 3 )

C o n ce n tr at ed

d is ad

va n ta ge

(C D )

− 0. 0 9 * (− 0 .1 8 )

− 0 .0 3 (− 0 .0 6 )

− 0 .0 6 † (− 0 .1 2 )

− 0 .0 8 (− 0 .1 6 )

− 0 .0 2 (− 0 .0 4 )

− 0 .0 7 (− 0 .1 4 )

− 0 .0 2 (0 .0 4 )

− 0 .0 3 (− 0 .0 6 )

− 0 .1 2 * (− 0 .2 4 )

− 0 .1 6 * (− 0 .3 3 )

C ri m e ra te

(C R )

0 .7 3 * (2 .1 4 )

0 .7 5 * (2 .2 8 )

0 .9 1 * (4 .4 3 )

0 .9 9 * (1 5 .4 3 )

0 .7 8 * (2 .5 0 )

0 .7 4 * (2 .2 1 )

0 .9 3 * (5 .1 3 )

0 .9 7 * (8 .2 2 )

0 .7 0 * (1 .9 7 )

0 .8 4 * (3 .1 2 )

P o p × B W

C –

0 .0 3 (0 .0 6 )

– − 0 .0 2 (− 0 .0 4 )

– − 0 .0 1 (− 0 .0 2 )

– − 0 .0 4 (− 0 .0 8 )

– − 0 .1 6 (− 0 .3 3 )

P B × B W

C –

0 .1 5 * (0 .3 0 )

– 0 .0 3 (0 .0 6 )

– − 0 .1 8 * (− 0 .3 7 )

– − 0 .0 1 (− 0 .0 2 )

– 0 .0 7 (0 .1 4 )

C D × B W

C –

− 0 .0 9 (− 0 .1 8 )

– 0 .0 3 (0 .0 6 )

– 0 .0 7 (0 .1 4 )

– 0 .0 2 (0 .0 4 )

– 0 .0 6 (0 .1 2 )

C R × B W

C –

− 0 .0 2 (− 0 .0 4 )

– 0 .1 2 † (0 .2 4 )

– 0 .0 5 (0 .1 0 )

– − 0 .0 7 (− 0 .1 4 )

– − 0 .2 0 * (0 .4 1 )

F 5 8 .2 7

3 3 .3 0

1 0 7 .7 9

6 0 .2 7

7 7 .4 4

4 4 .6 4

1 6 6 .9 3

9 2 .4 0

3 2 .8 8 .3 7

1 9 .1 0

R 2

.5 1

.5 2

.6 6

.6 6

.5 8

.5 9

.7 5

.7 5

.3 8

N ot e:

B = St an

d ar d iz ed

co ef fi ci en

ts ; d = C o h en

’s d.

*p < .0 5 .

† p < .1 0 .

HUGHES ET AL. | 77

model did reveal four significant findings. Specifically, population (B = 0.33; p < .05; Cohen’s d = 0.70), and crimes

per 1,000 residents (B = 0.73; p < .05; Cohen’s d = 2.14) significantly increased the amount of self‐initiated activity

by patrol officers, while the percentage of Black residents (B = 0.09; p < .10; Cohen’s d = 0.18) approached

significance. Conversely, concentrated disadvantage (B = −0.09; p < .05; Cohen’s d = −0.18) was correlated with a

significant reduction in the number of self‐initiated activities.

BWC implementation (B = −0.065; p < .10; Cohen’s d = −0.1305) approached significant with trends indicating a

decrease in the total number of enforcement actions. In addition, a concentrated disadvantage (B = −0.06; p < .10;

Cohen’s d = −0.06) approached significance for a decrease in total enforcement. Total enforcement significantly

increased as population (B = 0.31; p < .05; Cohen’s d = 0.65) and crimes per 1,000 residents (B = 0.91; p < .05;

Cohen’s d = 4.43) increased. The percentage of Black residents was not correlated with total enforcement activity.

In regard to felony arrests, BWC implementation and concentrated disadvantage did not significantly influence

the number of felony arrests by officers. However, census tracts with a higher population (B = 0.26; p < .05; Cohen’s

d = 0.54) and a higher rate of crime (B = 0.78; p < .05; Cohen’s d = 2.50) were correlated with a higher frequency of

felony arrest, while a larger percentage of Black residents (B = 0.08; p < .10; Cohen’s d = 0.16) approached

significance for increasing felony arrests.

In terms of arrest for low‐level offenses, BWC implementation (B = −0.12; p < .05; Cohen’s d = −0.24) was

associated with a decrease in the number of misdemeanor citations but was not significantly related to

misdemeanor arrests. Concentrated disadvantage (B = −0.12; p < .05; Cohen’s d = −0.24) also exerted a significant

negative correlation with the number of misdemeanor citations at the census tract level, whereas the percentage of

black residents (B = −0.11; p < .10; Cohen’s d = −0.22) approached a significant negative correlation. Population

(B = 0.32; p < .05; Cohen’s d = 0.68) and crimes per 1,000 residents (B = 0.93; p < .05; Cohen’s d = 5.13) significantly

increased the number of misdemeanor arrests at the tract level. Similarly, population (B = 0.29; p < .05; Cohen’s

d = 0.61) and crime rates (B = 0.70; p < .05; Cohen’s d = 1.97) increased the number of low‐level citations.

4.2 | Interaction effects

To answer research question 3, regarding differences in the impact of BWCs by neighborhood characteristics,

we also estimated models that regressed interaction terms (BWC × neighborhood characteristics) to assess any

moderating effects between our independent variables and the impact of BWCs on our outcome measures. As

shown in Table 3, for self‐initiated activity, only the interaction between percentage of Black residents and BWC

implementation (B = 0.15; p < .05; Cohen’s d = 0.30)—PB × BWC—revealed a statistically significant increase in

self‐initiated activities for officers. In our total enforcement model, the interaction between crimes per 1,000

residents and BWC implementation (B = 0.12; p < .10; Cohen’s d = −0.24)—CR × BWC—approached a signifi-

cantly correlated relationship with higher rates of total enforcement, indicating crime rates and BWC

implementation increased the total number of enforcement activities. In the felony arrest model, the percentage

of Black residents and BWC implementation interaction term was negatively correlated with felony arrests

(B = −0.18; p < .05; Cohen’s d = −0.37), suggesting that BWC implementation and the percentage of Black

residents interact to reduce the number of felony arrests at the tract level. Finally, no interaction terms were

significantly correlated with low‐level arrests, however, the interaction between crimes per 1,000 residents and

BWC implementation exerted a significant negative relationship with low‐level citations (B = −0.20; p < .05;

Cohen’s d = −0.41). This finding suggests that fewer citations were issued in lower crime census tracts after

BWCs were implemented.

Our third research question explored whether there were moderating effects between BWC implementation and

neighborhood characteristics. In sum, the analyses of interaction effects found that crime per 1,000 residents is the

strongest predictor of enforcement, followed by population. In each of our models, these variables had the largest

effect size and exerted a significant positive relationship with self‐initiated activity and enforcement practices. In our

78 | HUGHES ET AL.

main effects models, percentage of Black residents significantly increased the number of self‐initiated activity and

felony arrests, but was correlated with a significant decrease in low‐level citations. Concentrated disadvantage was

correlated with less self‐initiated activity, less total enforcement actions, and fewer low‐level citations. In addition,

BWC implementation had a negative effect on total enforcement and low‐level citations. Finally, our interaction

effects revealed that the impact of BWC implementation on felony arrest might be moderated by the percentage of

Black residents, while crime rates may moderate the impact of BWCs on low‐level citations.

5 | DISCUSSION

Police scholarship consistently finds neighborhood characteristics influence officer activity, especially regarding

discretionary activity such as arrests (Lum, 2011; Ousey & Lee, 2008). In this study, we used census tract data for a

single city to examine changes in officer activity and enforcement following the implementation of BWCs. The

study adds to the larger BWC literature by finding a marginally significant reduction in total enforcement,

misdemeanor citations, and traffic violation citations following the deployment of BWCs at the neighborhood level.

The findings suggest that officers were less likely to give citations for minor infractions after BWC implementation;

however, officers’ decisions to arrest for more serious crimes or engage in self‐initiated activity remained

unaffected by the BWCs. It is important to note these findings did not happen in a vacuum. Recent research

examined 8 years of enforcement actions in Louisville and revealed a general decline in that total enforcement

actions beginning in 2013 for the jurisdiction (Schaefer, Hughes, & Jude, 2018).4

Our findings are counter to previous literature where studies have found decreases in arrests (Ready & Young,

2015; Wallace et al., 2018) and increases in self‐initiated activity (Braga et al., 2017; Lum et al., 2019). One

explanation for the mixed findings regarding BWCs is related to our inclusion of alternative theoretical frameworks

to account for percent of Black residents and concentrated disadvantage on officer activity. The study argues

examination of BWCs needs to occur at the neighborhood level, and in doing so, researchers must take into account

other community characteristics when analyzing outcomes, as policing practices vary between neighborhoods

within a single city (Terrill & Reisig, 2003).

In general, the minority threat hypothesis posits the existence of intractable divisions in American society and

hypothesize that officers will increase their activity in communities with high concentrations of minority

residents. Our findings indicate the minority threat hypothesis was partially supported. The analysis revealed

that the percent of Black residents, exerted a significant positive relationship on self‐initiated activity, however,

citations for misdemeanor and violation offenses were significantly less likely in tracts with a higher percentage

of Black residents. There are two possible explanations for the mixed findings regarding minority threat. First, it

is possible the police are adopting a legalistic model to determine coercive activities in the neighborhoods they

patrol. Following BWC implementation, officers maintained levels of emphasis on serious offenses (felonies) and

deprioritized less serious crime (misdemeanor citations). The increase in self‐initiated activity may reflect the

department‐wide emphasis on proactive policing to reduce violent crimes, and therefore, officers continued to

use their discretion to seek out serious crime, but under‐enforced minor crimes in tracts with a higher proportion

of Black residents. The second possible explanation is that depolicing occurred with the exception of major

offenses. Practitioners and scholars have suggested that the adoption of BWCs could lead officers to reduce their

activity in response to increased scrutiny (Brunson & Miller, 2006; Rushin & Edwards, 2017). The implementation

of BWCs altered the dynamics of intergroup relations between police and minorities (Blumer, 1958; Weitzer,

2017) and therefore the concerns of the police were no longer the only factor driving intergroup interactions in

minority communities. Despite these findings, it should be noted few studies have examined BWCs, depolicing,

4The research examined felony arrests, misdemeanor arrests and citations, moving violation arrests and citations, and bench warrant arrests. Traffic stop

data were not included in the analysis as only 2 years of data were available (Schaefer et al., 2018).

HUGHES ET AL. | 79

and police activity (Shjarback, Pyrooz, Wolfe, & Decker, 2017; Wallace et al., 2018). Wallace et al. (2018)

examined the degree to which BWCs contribute to depolicing on officer‐initiated calls and arrests and found

officers assigned BWCs were more active than officers without BWCs; however, they did not examine depolicing

at the neighborhood level, which may explain their findings. Tension between the police and communities is not

universal across neighborhoods and is, to an extent, dependent on perceptions of legitimacy (Wolfe & Nix, 2016).

In addition to examining the influence of the percent of Black residents, we also examined the influence of

place on officer activity, specifically measures of concentrated disadvantage. The presence of concentrated

disadvantage is thought to decrease the ability to create informal social control, resulting in higher crime and a

greater likelihood the police presence increases in these neighborhoods (D. A. Smith, 1986). Extant research

shows that macrolevel concentrated disadvantage is related to officer behavior (Kane, 2002; Klinger, 1997; D. A.

Smith, 1986; Terrill & Reisig, 2003). Police are more likely to engage in proactive policing in communities where

they perceive there to be a lack of informal social control and where crime is high (Parker et al., 2004). Whereas,

our concentrated disadvantage measures were not related to arrests. One possible explanation for the increase

in proactive policing is related to the relationship between concentrated disadvantage and officer perception of

the area, in particular the presence of poverty may result in officers working to create formal social control

(Parker et al., 2004). It is possible that the decrease in overall enforcement and especially citations were an

avoidance of arresting poor individuals or avoidance with interacting with persons whom they believe are

unworthy of police attention (Blumer, 1958). This finding supports prior research that blacks have unique

experiences with racial economic disadvantage (Parker et al., 2004, 2005). In particular, it is possible that the

combination of Black economic disadvantage and racial concentration influences Black arrests because these

factors tend to amplify perceived group differences.

Finally, it is important to note the strongest finding in the models is the relationship between crime rates and

enforcement activities. This finding held when accounting for BWC implementation, percent of Black residents, and

concentrated disadvantage, suggesting police officers’ primary enforcement concern was the presence of criminal

activity. Contemporary police practices are oriented towards policing high‐crime places and high‐risk individuals

(NASEM, 2018). Prior research shows these strategies can be effective in reducing crime (Braga & Weisburd, 2012;

Braga, Papachristos, & Hureau, 2014). The emphasis on high‐crime places and people are also used to justify the

over‐presence of police in low‐income and minority communities, where crime is often concentrated (NASEM,

2018). Yet, there is a large body of research noting the problems associated with enforcement in high‐crime areas

and the wide range of consequences associated with arrests, especially for low‐level offenses and drug offenses

(Helfgott, Parkin, & Fisher, 2019; Slocum, Greene, Huebner, & Rosenfeld, 2019).

This study is not without limitations that may provide greater insight into the impact of BWCs,

neighborhood characteristics, and officer activity. One limitation to this study is the lack of intervening

mechanisms examining these relationships. As a result, our study allows us to make inferences regarding the

observed relationship and theoretical framework, but not state causal relationships. Relatedly, this study did

not examine all structural theories of police behavior that could inform the findings. For instance, the study did

not examine all aspects of the place hypothesis, which suggest the concentration of minorities is insufficient to

understand variation in police behavior (Smith & Holmes, 2014). Rather, the place hypothesis argues that

residential segregation of minority populations is central to explaining coercive policing strategies (Brunson &

Miller, 2006; Smith & Holmes, 2014). Such segregation acts to cluster minority populations in areas of

concentrated disadvantage. These areas may be viewed as a threat to the larger economic superstructure and

thus warrant management (Bass, 2001; Spitzer, 1975). In addition, officers who patrol these areas may

perceive minority residents as especially threatening to their safety. The police in such areas may, therefore, be

more likely to employ force against minority community members (Brunson & Miller, 2006; Holmes et al., 2018;

Smith & Holmes, 2014). Such perceived threats may well be more influential on police actions as they are more

proximate than threats to the larger social order (Holmes, 2000). Residential segregation could also exacerbate

disparities in police practices through benign neglect of minority victims (Liska & Chamlin, 1984). Under this

80 | HUGHES ET AL.

theory, changes in a community’s racial composition influence the nature of criminal incidents. In effect, crime

becomes more intraracial than interracial. Such a change in crime may alter the application of formal social

control, resulting in minorities receiving less crime‐control resources (Myer & Chamlin, 2011; Ousey & Lee,

2008). Such a result is thought to flow from two sources. First, minority groups living in areas of concentrated

disadvantage lack the political power to mobilize social resources to address issues of concern. Second, crime

involving minority offenders and victims may be seen as more personal and less deserving of formal social

intervention (Liska & Chamlin, 1984). As a result, the police may less stringently enforce the law in minority

neighborhoods. Our inability to include a measure of racial segregation prevents us from fully examining the

place hypothesis.

Second, prior research has established police decision‐making is also influenced by office and situational

characteristics, which were not captured in this study (Klinger, 1997; Terrill & Reisig, 2003). However, we are

unable to address these issues due to the nature of our data, which provided no information about individual

officers or situational variables. Studies combining macro and micro factors would provide greater insight into how

police react to BWCs across communities. For instance, Klinger (1997) proposed the ecological theory of police

behavior to explain neighborhood variation in police responses. Klinger acknowledges the role police organizations,

crime, and disorder play in police practices, but also argues officer workload, perceptions of victim deservedness,

and policy cynicism can also influence police responses. One consequence of these factors is officers take less

vigorous actions in neighborhoods with higher crime due to the aforementioned factors. Thus, future studies that

include measures of officer perceptions of how “deserving” places are of service may find different outcomes

related to BWC implementation and neighborhood characteristics.

Third, the study examines a single department. The focus on a single agency limits the generalizability to

other populations, as the outcomes of BWC implementation are strongly influenced by local conditions

(Wallace et al., 2018). In addition, we acknowledge our span of observation is limited. As such, our data reflect a

limited point in time and therefore cannot determine the extent to which pre‐ and post‐BWC differences are

affected by long‐term changes in enforcement patterns. This is particularly important as overall enforcement

rates were declining in Louisville before BWC deployment (Schaefer et al., 2018). Next, the study uses official

data for the outcomes, which is often criticized for not being entirely accurate or complete (Manning, 2009).

Finally, our study did not use an experimental or quasi‐experimental design. The research was limited by the

department’s decision to roll out cameras division by division. Using data from a random‐control trial to

understand neighborhood variation would allow researchers to understand officer‐level changes in activity

within similarly diverse neighborhoods and allow for causal inferences.

6 | CONCLUSION

BWCs have the potential to alter officer self‐initiated activity and enforcement practices. We examined the influence of

BWC implementation while accounting for community characteristics, finding partial support for minority threat

hypotheses and place theory. However, we also find that rather than increasing enforcement as the percent of Black

residents would hypothesize, the presence of BWCs, and the potential to increase unwanted accountability, decreased

officer activity and certain enforcement activities leading to a depolicing effect.

ACKNOWLEDGMENTS

We would like to thank Louisville Metro Police Department (LMPD) for sharing their data, and members of their

command staff who provided input on the project. Any findings and conclusions expressed in this manuscript are

those of the authors and do not necessarily reflect the views of LMPD.

HUGHES ET AL. | 81

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How to cite this article: Hughes TW, Campbell BA, Schaefer BP. The influence of body‐worn cameras,

minority threat, and place on police activity. J Community Psychol. 2020;48:68–85.

https://doi.org/10.1002/jcop.22299

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