Inequalities Regimes in Policing: Examining the Connection Between Social Exclusion and Order Maintenance Strategies

Abstract

The purpose of this article is to evaluate how the intersection of race, class, and gender within law enforcement influences the utilization of public safety strategies grounded in the broken windows policing philosophy. Drawing from Acker’s inequality regime framework, we hypothesize that greater workplace inequalities produce institutionalized systems of social processes that increase the likelihood that organizations will implement aggressive enforcement of order maintenance offenses as a strategy for sustaining public safety. Using data collected from 1,218 U.S. police departments, the results suggest that stronger inequality regimes are associated with higher arrest rates for disorder offenses, marijuana possession, and liquor law violations. Further, the results suggest that stronger inequality regimes are related to higher arrest rates for Black community members. As many law enforcement agencies across the nation face a legitimacy crisis, prompted by concerns about how police interact with people of color, the results from this study suggest that increasing representation and reducing inequality in law enforcement should result in agencies becoming less reliant on large-scale arrest-driven order maintenance strategies by including more diverse perspectives in the decision-making process and developing alternative models for maintaining public safety.

Keywords

Acker aggressive policing broken widows theory class community policing gender inequality regimes law enforcement race racialized policing

The 2014 deaths of Michael Brown in Ferguson, MO, Eric Garner in Staten Island, NY, and Laquan McDonald in Chicago, IL, exposed the estranged and tumultuous relationship between many local law enforcement agencies and the communities the agencies are sworn to serve, particularly neighborhoods with a large percentage of young men of color. Research generally suggests that Black residents have more negative attitudes toward the police (Durose & Langan, 2007; Rosenbaum, Schuck, Costello, Hawkins, & Ring, 2005; Tuch & Weitzer, 1997; Weitzer, 1999, 2015) and have more negative experiences with the police than White residents (Kochel, Wilson, & Mastrofski, 2011; Stewart, Baumer, Brunson, & Simons, 2009; Zhao, Lai, Ren, & Lawton, 2015). Many young people of color feel that law enforcement officials unfairly target them and that they are treated in a disrespectful and unjust manner during encounters with the police (Brunson, 2007; Brunson & Miller, 2006). Further, many parents of color express fear and concern for their children when they interact with individual officers (Berkel et al., 2009).

Scholars have suggested that increasing the diversity within the law enforcement workforce and promoting more Black and female officers into leadership positions are possible strategies for building justice-centered organizations that are more responsive to the public (Schuck, 2014; Schuck & Rabe-Hemp, 2014; Silvestri, 2007; Weisburd, Greenspan, Hamilton, Williams, & Bryant, 2000). In theory, the differential distribution of power enables the selective use of social control to the advantage of members of the dominant group and to the disadvantage of members of subordinate groups (Blalock, 1967). Increasing equality and the representativeness of arbiters of justice is a perspective not only discussed by scholars but also advocated by the public and policy makers. For example, the President’s Task Force on 21st Century Policing (2015) recommended that the federal government create a law enforcement diversity initiative in order “to create a workforce that contains a broad range of diversity including race, gender, language, life experience, and cultural background to improve understanding and effectiveness in dealing with all communities” (p. 16).

The purpose of this article is to evaluate whether the intersection of race, class, and gender within law enforcement is associated with the utilization of public safety strategies drawn from the broken windows policing philosophy. Although aggressive enforcement of order maintenance offenses remains high, there is growing evidence that these types of practices have a negative impact on people of color, undermine neighborhood processes in minority communities, and reduce the overall legitimacy of the law (Fagan & Davies, 2000; Meares, 2015). Drawing from Acker’s (2006) inequality regimes framework, we hypothesize that greater workplace inequalities produce institutionalized systems of social processes that increase the likelihood that police organizations will utilize large-scale arrest-driven order maintenance strategies and that these patterns of social relations will directly affect people of color.

Background and Literature Review

Inequality Regimes

Acker (2006) introduced the framework of inequality regimes, defined as “loosely interrelated practices, processes, actions, and meanings that result in and maintain class, gender, and racial inequalities within particular organizations” (p. 443), as a way to understand how inequalities that exist in society are reified and reproduced in organizations. In organizations, a significant amount of social and economic inequality is created through the daily activities of employees and how labor is structured. For this reason, Acker (1990, 2006) argued that workplace inequalities are connected to disadvantaging members of certain social and economic groups through processes that socially construct the requirements of work that favor the powerful, support class hierarchies, and facilitate bureaucratic decision-making in which inequalities are reproduced. A small but growing body of empirical research examines how these workplace inequalities are connected to disadvantage in organizations, usually measured through wage disparity, social exclusion, and occupational stress (Charles & Grusky, 2004; Kvande & Rasmussen, 1994; Reskin, 2003; Ridgeway, 1997; Wharton, 2009).

Inequality regimes in the workplace are produced and sustained by a dialect between the structure and social interactions among workers—that is, between the organization and individual actors within the organization (Acker, 2006). This dialect helps define that is valued and rewarded and what is deemed as unacceptable and punished. In the literature, several scholars have identified how the pervasiveness of gender inequalities in law enforcement has contributed to forging institutions of formal social control that legitimize hegemonic masculinity (i.e., practices that advance the dominant social position of men and the subordinate social position of women; for a review, see Shelley, Morabito, & Tobin-Gurley, 2011). This starts with recruitment and hiring in which the images of appropriate gendered bodies advertise perceptions of what the ideal police officer looks like, defined by Davies (1996) as a “masculinist vision” (p. 669). The legitimizing of masculinity is also believed to be why many departments emphasize the role of police as crime fighters and minimize the social service aspects of the profession (Chan, 1996; Martin, 1994; Martin & Jurik, 2006), while segregating women into low visibility, social service roles such as clerical and administrative assistants and specialists in juvenile justice, sexual assault, and domestic violence (Garcia, 2003; Padavic & Reskin, 2002), thus maintaining their secondary status in the police culture (see Wood, Davis, & Rouse, 2004). Departments do this while also implementing formal procedures and informal practices that marginalize offenses that disproportionately affect women, such as those related to the processing of sexual assault and domestic violence cases (Lonsway & Achambault, 2012; Spohn & Tellis, 2012). Finally, masculinity is homogenized in the lack of family-friendly policies prompting many women to leave the occupation following childbirth (Rabe-Hemp & Humiston, 2015; Schulze, 2010).

The literature on the experiences of officers of color, rife with marginalization and discrimination, also confirms that the pervasiveness of inequalities in law enforcement is produced and sustained by a dialect between the structure and social interactions among workers (Brunson & Gau, 2015; Fyfe, 1981; Haarr, 1997; Worden, 1993). Based on overrepresentation in assignment to neighborhoods with higher economic disadvantage, crime rates, and residential mobility, Black officers are less likely to favor selective enforcement of the law (Fyfe, 1981; Worden, 1993). While assigning Black officers to these neighborhoods may relieve racial tensions, it has the unintended consequence of highlighting officer race and further isolating the officer from the police culture. Officers of color are marginalized not only in their beat assignments but also in their academy and field training experiences, segregated to Black field training officers (Haarr, 1997).

In 1982, Crime and Social Justice Associates published a report entitled, The Iron Fist and the Velvet Glove: An Analysis of the US Police, arguing that the police exist to “enforce the class, racial, sexual and cultural oppression that is integral to the development of capitalism in society” (Institute for the Study of Labor and Economic Crisis, 1982, p. 7). The recent string of police shootings has added to the perception that the police are the front lines in the class wars (Weitzer, 2016]). Resistance to increased education requirements for police officers and a maintenance of training mentality maintains the monolithic working-class structure in policing. The fact that many police departments have not raised their educational standards since the 1950s, while access to higher education has increased dramatically, has led many to argue that much of the police-community conflicts were associated with the low quality of police personnel. While there is a link between departments salary and higher levels of education (Stewart, 2006), previous research has not examined the link between officer salary and police strategy which is interesting, given that the push for better salaries has been associated with the professionalization of the police occupation. Taken as a whole, one of the most important reoccurring themes in the gender, race, and class literature is how the hegemonic traditions in law enforcement lead to the production of systematic and structural patterns of social exclusion, which workforce members both resist and reproduce through their interactions with each other and the institutional complex (Oberfield, 2014).

Nevertheless, research also suggests that organizations vary in the degree to which these inequality regimes are present and remind us that they can be challenged and changed. Acker (2006) cited affirmative action and pay equity campaigns as successful campaigns that decreased disparities in organizations. Within policing, there is some evidence that a more diverse police workforce is associated with more reflective policy making regarding leadership, use of force, and adoption of community-oriented policing efforts (Schuck & Rabe-Hemp, 2014; Silvestri, 2007; Weisburd et al., 2000). This research suggests that by changing the composition of the policing workforce, a change in the organizing processes in policing may follow. An examination of how inequality regimes affect workers and how inequality regimes affect the goals of an organization and the means used to carry out the work of the organization situates the production of inequality within the processes that give it shape.

Acker’s (2006) framework differs from other theories of organizational diversity, such as the community accountability theory (Reiss, 1971) and the theory of representative bureaucracy (Meier & Nicholson-Crotty, 2006), in several important ways. First, the inequality regime perspective focuses attention on studying how diversity influences changes in organizational-level mechanisms rather than individual-level behaviors. Much of the current literature tests hypotheses about differences in attitudes, behaviors, and skills between Black and White officers, male and female officers, and officers from different educational or economic backgrounds (Brown & Frank, 2006; Hassell, Archbold, & Stichman, 2011; Novak, Brown, & Frank, 2011; Paterson, 2011; Rabe-Hemp, 2008; Sun & Payne, 2004; for reviews, see Lockwood & Prohaska, 2015; Poteyeva & Sun, 2009).

Second, the inequality regimes framework suggests that the effects of race, class, and gender representation are general and symbiotic, rather than specific and proportional. Currently, much of the literature tests hypotheses about how the bureaucratic representation of a specific group influences the outcomes for that particular group. That is, studying how Black officers may help Black citizens (Brunson & Gau, 2015; Theobald & Haider-Markel, 2009) or how female officers may help female citizens (Meier & Nicholson-Crotty, 2006; Riccucci, Van Ryzin, & Lavena, 2014; Walfield, 2016). This work is based theoretically on the idea that there is a kindred connection between bureaucrat and citizen, and the associated affiliation influences how the official uses his or her discretion to affect outcomes for the clients. Within this context, the effect of representation on outcomes is hypothesized to be specific (i.e., Black officers influence outcomes for Black citizens) and proportional (i.e., the greater the percentage of Black officers in the organization, the greater the effect).

Acker’s (2006) framework suggests that the effects of race, class, and gender are not independent from one another and do not follow a proportional linear growth curve. Instead, the theory suggests that the effects are general and symbiotic with each contributing to the manifestation of the same underlying mechanism. Instead of theorizing that different sociodemographic diversity indicators produce unique, additive, or antagonistic effects, Acker’s (2006) framework focuses scholars’ attention on studying how multiple inequalities in representation and access to power agglomerate to produce a specific set of values that impact organizational-level mechanisms.

Third and last, there are important methodological differences. In general, most scholars include race, class, and gender indicators as independent variables and estimate the unique contribution of each factor. However, under the inequalities framework, the convergence of multiple inequalities is what is important, and thus, researchers should be examining the shared effect of the confluence of several inequality measures when evaluating research questions.

Although some literature exists on the production of inequalities in law enforcement and how they affect public safety personnel, there is far less scholarship on whether inequality regimes within institutions of formal social control influence how police organizations do their work and, in turn, how those decisions affect residents’ experiences of justice. Do inequality regimes in law enforcement affect police organizations’ strategies for achieving public safety, and do those decisions disproportionally affect people of color? Before evaluating these questions, it is important to understand how inequality regimes in policing may be theoretically related to decisions regarding the means of achieving public safety.

Policing Strategies Derived From Broken Widows

In a 1982 article in the Atlantic Monthly, Wilson and Kelling introduced the broken windows theory in which they suggested that targeting minor disorder, such as loitering, public drinking, panhandling, prostitution, littering, graffiti, and abandoned buildings, would help reduce more serious crime. Grounded in the sociological literature on neighborhoods, the broken windows theory posits that minor social and physical disorder attracts more serious crime by signaling to potential criminals that no one is in charge and that offending will not be reported or controlled. Further, to law-abiding residents, these disorderly conditions lead to fear and communicate the need to avoid public places and potentially move out of the community. In the original essay, Wilson and Kelling (1982) did not suggest specific policing policies; however, many executives and policy makers have interpreted the broken windows theory as implying that the most effective way to address serious crime is to increase the number of arrests for misdemeanor offenses (Kelling & Sousa, 2001). A variety of policing strategies have been developed from the basic idea of targeting community disorder to reduce serious crime, including order maintenance policing, zero-tolerance policing, and aggressive policing.

The empirical evidence on the efficacy of strategies drawn from broken widows policing is generally mixed (for a review, see Harcourt & Ludwig, 2006; Rosenfeld, Fornango, & Rengifo, 2007; Skogan & Frydl, 2004). However, in a recent meta-analytic review, Braga, Welsh, and Schnell (2015) identified two categories of disorder strategies: aggressive order maintenance initiatives, which were characterized as large-scale arrest-driven approaches that targeted disorderly individuals, and community problem-solving programs characterized by a small area focus and the engagement of community stakeholders in identifying, developing, and implementing tactics. The difference between these two types of disorder strategies is important. The first type, aggressive order maintenance, is based on the idea that residents cannot police themselves and that law enforcement officials must use their authority and coercive power to resolve community problems (Wilson & Kelling, 1982). Under this model of policing, residents play a passive role while the police reestablish order. Only after the police have reestablished order, do the residents reassume their role regarding the utilization of the community of social control. Community stakeholders are not given the opportunity to work with the police in defining which problems should be addressed or which tactics will be employed. Further, the residents in the neighborhood who are engaging in disorderly behaviors are viewed as criminals who need to be removed from the community before their behaviors lead to more serious crime (Harcourt, 2009).

In contrast, the second type, community problem-solving, is grounded in principles of community policing in which the goal is to organize residents and give them a voice regarding decisions that affect the quality of life in their neighborhood (Rosenbaum & Lurigio, 1994; Trojanowicz & Bucqueroux, 1998). The community policing philosophy promotes the development of community–police partnerships, which are hypothesized to reduce crime and disorder by increasing social control at the parochial and public levels through the creation of new sources of social capital (Meares, 2002). Further, under the community policing paradigm, offenders are part of the community, and to make neighborhoods safer, residents need to take responsibility for crime prevention by increasing social control over law violators (Clear & Karp, 1999; Herbert, 2001). Violators are reminded of the harm they cause and are encouraged to engage in more prosocial behaviors. The community perspective acknowledges that law violators are not outsiders but are instead residents who need to be confronted and redirected toward more positive behaviors.

Braga et al. (2015) concluded that community problem-solving disorder strategies were associated with modest reductions in crime, whereas aggressive order maintenance strategies had no effect. In addition to the questionable impact on serious crime, scholars have raised concerns about the collateral consequences of large-scale arrest-driven order maintenance strategies, including (a) the economic costs associated with the expansion of the criminal justice system (Stuart, 2016); (b) the ramifications for arrested individuals, such as reduced employment and housing opportunities, deportation (Howell, 2009), and negative physical and mental health outcomes (Geller, Fagan, Tyler, & Link, 2014); (c) the disproportionate impact on people of color (Fagan & Davies, 2000); and (d) the effect on the community–police relationship, especially in communities with a significant number of Black and Hispanic residents (Skogan & Frydl, 2004).

Summary and Hypotheses

In summary, policing strategies are rife with assumptions about the best methods for achieving public safety. These assumptions are intertwined with beliefs about the community; the police; and the meaning of race, class, and gender within the larger social structural context of the administration of justice. These assumptions often reproduce inequality structures in the application of formal social control that are unspoken and, in many cases, unintentional. Because large-scale arrest-driven order maintenance strategies are less likely to include residents and community problem-solving than small-scale targeted initiatives (Braga et al., 2015), agencies with strong inequality regimes should be more likely to utilize these strategies to increase public safety than departments with weak inequality regimes due to a lack of diverse perspectives in the decision-making process. Drawing from the inequality regimes framework, we specifically hypothesize that strong inequality regimes in law enforcement will be associated with (a) higher arrest rates for order maintenance offenses, (b) higher arrest rates for Black residents regarding order maintenance offenses, and (c) that these effects will be independent of the serious crime rate.

Method and Measures

Information about the strength of the inequality regime was gathered from the 2013 Law Enforcement Management and Administrative Statistics (LEMAS) survey (U.S. Department of Justice, 2015c). The LEMAS survey is conducted once in every 3–4 years and is designed to be a nationally representative sample of law enforcement agencies in the United States. Various information is collected, including data on personnel, pay and benefits, hires and separations, budgeting and financial issues, technology and information systems, vehicles and pursuits, use of force and officer safety, organizational structures, institutional policies, and community policing.

The inequality regime variable was created using three measures: the percentage of sworn full-time male officers, the percentage of sworn full-time White officers, and the average income for entry-level officers postacademy reversed (by subtracting each salary by the largest salary plus 1). Principal component factor analysis with varimax rotation was used to evaluate the degree to which the measures represent one underlying construct. The results returned a one-factor solution with all three variables producing positive loadings (.667 for male, .730 for White, and .544 for salary [reversed]) in the component matrix. The factor explains about 42% of the variance in the variables. To represent real values for police organizations, the inequality regime variable was created by standardizing and summing the male, White, and income (reversed) measures.¹ Higher scores indicate the presence of a stronger inequality regime (n = 1,218, M = 0, SD = 1.95, range = −8.99–3.97).

Four different types of arrests were used to test the hypotheses: disorder offenses, arrests for marijuana possession, drunkenness, and liquor law violations. These offenses were selected because they are consistent with disorder policing strategies and are not classified as serious Category Part I offenses, a significant number of agencies report these types of arrests to uniform crime reports (UCR) officials, and these offenses have been used by prior researchers (for a review, see Gau & Pratt, 2010). Disorder offenses are defined as “any behavior that tends to disturb the public peace or decorum, scandalize the community, or shock the public sense of morality” (Federal Bureau of Investigation [FBI], 2004, p. 145). Drunkenness includes arrests for individuals who consume enough alcohol to impair their mental functioning and physical coordination, while liquor law arrests include violations of state and local laws prohibiting the sale, purchase, transportation, manufacture, or possession of alcohol (FBI, 2004). Drunkenness and liquor law violations exclude arrests for driving under the influence. Information about the four arrest measures was gathered from the 2013 UCR Program Data: Arrests by Age, Sex, and Race (U.S. Department of Justice, 2015b). The arrest rates were calculated using the population data provided in the file and were calculated per 100,000 persons. Although the number of arrests by race is reported in the UCR file, population data are not reported by race. To accurately calculate the Black arrest rate (per 100,000 persons), the number of Black residents (Black alone and Black for the two races categories) was gathered from the 2014 American Communities Survey (ACS) 5-year estimates (2010–2014; Minnesota Population Center, n.d.). The number of Black residents was matched to agencies using place codes for 84% of the cases. The remaining 193 agencies were matched using county codes. Because of skewness, all of the arrest rates were transformed using the natural log. The descriptive statistics for the arrest rates logged were as follows: disorder offenses (n = 1,126, M = 4.78, SD = 1.37, range = 0.00–9.66), marijuana possession (n = 1,218, M = 4.94, SD = 1.28, range = 0.00–7.92), drunkenness (n = 629, M = 5.22, SD = 1.51, range = 0.19–9.16), liquor law violations (n = 1,041, M = 4.27, SD = 1.49, range = 0.00–10.14), Black arrest rate for disorder offenses (n = 1,118, M = 4.44, SD = 2.74, range = 0.00–11.13), Black arrest rate for marijuana possession (n = 1,199, M = 4.55, SD = 2.87, range = 0.00–11.51), Black arrest rate for drunkenness (n = 622, M = 4.39, SD = 2.83, range = 0.00–11.67), and Black arrest rate for liquor law violations (n = 1,028, M = 3.23, SD = 2.71, range = 0.00–11.43).

To control for the possibility of a spurious relationship, eight other variables were included in the hypothesis tests. Research suggests that the size and complexity of the organization are related to the implementation of different types of policing strategies (Maguire, 1997; Reaves, 2015). Civilianization was measured as the percentage of the full-time workforce that is nonsworn personnel (n = 1,218, M = 18.09, SD = 10.31, range = 0.00–50.75), and the size of the workforce was measured as the number of full-time sworn officers in the department. Because of skewness, the size measure was transformed using the natural log (n = 1,218, M = 3.91, SD = 1.33, range = 1.10–9.20). Vertical differentiation was measured as the difference between the chief’s maximum salary and an entry-level officer’s minimum salary divided by the entry-level officer’s minimum salary (Maguire, 1997; n = 1,218, M = 1.65, SD = 0.93, range = 0.05–7.20). Community policing was measured using 6 items from the community policing section of the LEMAS survey. Police executives were asked to report whether or not (coded no = 0 and yes = 1) they (a) had a mission statement with a community policing component; (b) regularly assigned the same patrol officer to a particular area or beat in the jurisdiction; (c) encouraged patrol officers to engage in scanning, analysis, response, and assessment (SARA)-type problem-solving projects; (d) had problem-solving partnerships or written agreements with any local civic, business, or government organizations; (e) included collaborative problem-solving projects in the evaluation criteria of patrol officers; and (f) utilized information gathered from a survey of local residents regarding crime, fear of crime, or satisfaction with law enforcement. The six measures were summed with higher values indicating greater implementation of policing practices grounded in the community policing philosophy (n = 1,218, M = 3.13, SD = 1.66, range = 0.00–6.00). While these items do not represent all aspects of community policing, they have been used by several researchers as an indicator of community policing and problem-solving activities (see Langworthy, 2002; Matusiak, Campbell, & King, 2014; Reaves, 2015).

Data on the crime rate (per 100,000 persons) were gathered from the 2013 UCR Program Data: Offenses Known and Clearances by Arrest (U.S. Department of Justice, 2015a). The crime measure includes the following types of offenses: criminal homicide, rape, robbery, aggravated assault, burglary, larceny, and motor vehicle theft (n = 1,218, M = 7.92, SD = 0.71, range = 0.00–9.88).² Information on the community was gathered from the 2014 ACS survey 5-year estimates (2010–2014; Minnesota Population Center, n.d.) and matched to the appropriate agency using place codes for the majority of departments (i.e., more than 80%) and county codes for the rest. The percentage Black was calculated using the number of Black residents reporting in the alone category and the number of Black residents reporting in the two-race category divided by the total population times 100. The percent youth was calculated as the percentage of residents in the community between 15 and 25 years old. Because of skewness, percent Black (n = 1,218, M = 2.06, SD = 1.07, range = 0.00–4.51) and percent youth (n = 1,218, M = 2.70, SD = 0.78, range = 1.52–4.26) were log transformed. Drawing from social disorganization theory, data were gathered on the percentage of residents in poverty, the percentage of unemployed residents, the percentage of residents receiving public assistance, the percentage of female-headed families with children, and the percentage of owner-occupied housing in each community. Researchers suggest that these measures are proxies for communities with severe economic disadvantage and less informal social control (Sampson, Raudenbush, & Earls, 1997). To evaluate the dimensionality of the measures, a factor analysis was conducted with the four community variables. The results suggested that the measures load on one dimension. Because the use of these measures is well documented in the literature, a principal component factor analysis with varimax rotation was used as a data reduction technique to extract regression factor scores to use as a control variable. The analysis indicated that the measures load high on one factor (.875 for poverty, .786 for unemployment, .675 for public assistance, .822 for female-headed families, and −.734 for owner-occupied housing) and that factor accounted for approximately 61% of the variance in the original variables (n = 1,218, M = 0, SD = 1, range = −2.39 to 4.72).³

Results

Analysis Strategy

The hypotheses were tested using least squares regression in SPSS 23.0. Before the regression models were estimated, the data were screened following the procedures outlined by Tabachnick and Fidell (2007) to look for problems associated with violating the assumptions of the statistical estimation technique, including normality, outliers, and multicollinearity. Measures that produced skewness scores of greater than 2.00 or less than −2.00 were transformed using the natural log. None of the bivariate correlations between the independent variables exceeded the threshold value of .70, and none of the variance inflation factors produced from the preliminary least squares regression models exceeded a value of 4.00. Regarding outliers, nine agencies had inequality scores that were more than three standard deviations from the mean with negative z-scores ranging from −3.04 to −4.61. All of the nine cases were checked for accuracy, and no mistakes were found. As a consequence, the nine cases that were identified as possible outliers were included in the hypothesis tests.⁴

Bivariate Correlations

The first step in the analysis process was to estimate the bivariate correlations between the inequality regime variable and the arrest rates for the four types of order maintenance offenses (see Table 1). The findings suggest a moderate positive relationship between the strength of the inequality regime and the arrest rate for disorder offenses (n = 1,126, r = .276, p < .001), possession of marijuana (n = 1,218, r = .201, p < .001), and liquor law violations (n = 1,041, r = .273, p < .001). The correlation between the inequality regime measure and the arrest rate for drunkenness was small and not statistically significant (n = 629, r = .044, p = .267). The bivariate correlations for the arrest rates for Blacks results suggested that there is no relationship between the strength of the inequality regime within the policing workforce and disorder offenses (n = 1,118, r = .004, p < .884), marijuana possession (n = 1,199, r = .002, p < .957), or liquor law violations (n = 1,028, r = .001, p < .973). The findings reveal a small to moderate negative relationship between inequality and drunkenness (n = 622, r = −.167, p < .001), suggesting that stronger inequality regimes are associated with lower arrest rates for offenses related to intoxication.

Table 1.

Pairwise Correlations Matrix.

Measures	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16
1. Inequality	1.00
2. Size workforce	−.47	1.00
3. Vertical diff.	−.27	.59	1.00
4. Civilianization	−.29	.33	.18	1.00
5. Community policing	−.31	.47	.32	.25	1.00
6. Crime rate	−.08	.32	.08	.19	.13	1.00
7. Disadv./instability	−.04	.19	.02	.02	.04	.50	1.00
8. Percent Black	−.16	.40	.28	−.02	.12	.29	.44	1.00
9. Percent youth	−.06	.22	.07	.10	.15	.18	.37	.15	1.00
10. Disorder	.28	−.19	−.20	−.25	−.12	.28	.26	.07	.03	1.00
11. Marijuana	.20	−.07	.04	−.13	−.08	.15	.08	.16	−.02	.40	1.00
12. Drunkenness	.04	−.07	−.06	.05	−.06	.26	.14	−.04	.03	.13	.16	1.00
13. Liquor	.27	−.29	−.19	−.08	−.04	.04	−.08	−.25	.05	.45	.39	.06	1.00
14. Black disorder	<.01	.26	.07	<−.01	.12	.35	.19	.23	.07	.55	.24	.14	.20	1.00
15. Black marijuana	<.01	.30	.21	.02	.13	.24	.06	.24	.05	.20	.57	.08	.15	.49	1.00
16. Black drunkenness	−.17	.33	.24	.15	.18	.34	.13	.20	.10	.01	.09	.61	−.05	.46	.37	1.00
17. Black liquor	<.01	.20	.03	.11	.15	.23	.03	.08	.11	.25	.24	.02	.52	.41	.39	.25

Note. Sample sizes vary from 622 to 1,218.

Significant correlations are in bold (p < .05).

Arrest Rates

The next step in the analysis strategy was to evaluate the inequality regime hypothesis on the four order maintenance measures while controlling for the potentially confounding factors described in the measurement section. The results of the regression models are presented in Table 2. Consistent with the hypothesis that inequality regimes in law enforcement are associated with the utilization of large-scale disorder policing strategies, agencies with stronger inequality regimes reported higher arrest rates for disorder offenses, the possession of marijuana, and violations of state and local liquor laws. The results do not support an association between inequality regimes and drunkenness. The coefficients for inequality regimes on the three order maintenance type arrests remained positive and statistically significant even after controlling for other important organization and community factors, including the crime rate, the size and complexity of the organization, and the economic health of the community.

Table 2.

Least Squares Regression Results for Order Maintenance Arrest Rates (per 100,000).

	Disorder Arrests (n = 1,126)		Marijuana Arrests (n = 1,218)		Drunkenness Arrests (n = 629)		Liquor Law Arrests (n = 1,041)
Measures	b	SE	b	SE	b	SE	b	SE
Inequality regime	.120***	.022	.118***	.021	−.014	.033	.130***	.026
Size of the workforce	−.118**	.043	−.144**	.041	−.174	.069	−.306***	.051
Vertical differentia-tion	−.130**	.049	.185***	.047	.006	.091	−.012	.057
Civilianiza-tion	−.027***	.004	−.010**	.004	.007	.006	−.006	.005
Community policing	.020	.025	−.016	.024	−.036	.040	.119***	.029
Crime rate	.621***	.068	.375***	.060	.784***	.119	.491***	.075
Disadvanta-ge and instability	.192***	.048	−.083	.046	.049	.077	−.162**	.056
Percent Black	.008	.041	.215***	.040	−.150	.065	−.251***	.050
Percent youth	−.073	.140	−.082	.138	.040	.229	.721***	.163
Constant	1.131	.644	2.228***	.594	−.204	1.131	−.078	.736
	R ² = .25		R ² = .12		R ² = .11		R ² = .19

*p < .05. **p < .01. ***p < .001.

Turning our attention to control measures, consistent with the idea that serious crime is one of the most important factors in the utilization of strategies drawn from the broken windows philosophy, the crime rates are strongly related to the arrest rates for all four-order maintenance offense types. The size of the organization is negatively related to three of the offense types (disorder, marijuana, and drunkenness), while vertical differentiation and civilianization are related to the disorder and marijuana arrest rate.

Black Arrest Rates

The final step in the analysis strategy was to examine the association between inequality regimes and the arrest rates for Black residents while controlling for organizational and community factors (see Table 3). Consistent with the hypothesis that inequality regimes in police organizations are associated with greater utilization of order maintenance policing with Black residents, the results suggest that there is a moderate positive relationship between the strength of the inequality regime and the arrest rate for Black residents for three of the four order maintenance offenses: disorder, marijuana possession, and liquor law violations. To help put these findings in perspective, because the dependent variables were log transformed, we can interpret the exponentiated regression coefficients as the change in the ratio of the expected geometric means of the order maintenance variables. For example, the results indicate that for a one-unit increase in the strength of the inequality regime, we would expect to see about a 20% increase in the disorder arrest rate for Black residents, a 26% increase in the Black arrest rate for marijuana possession, and a 19% increase in the Black arrest rate for liquor law violations.

Table 3.

Least Squares Regression Results for Black Order Maintenance Arrest Rates (per 100,000).

	Black Disorder Arrests (n = 1,118)		Black Marijuana Arrests (n = 1,199)		Black Drunkenness Arrests (n = 622)		Black Liquor Law Arrests (n = 1,028)
Measures	b	SE	b	SE	b	SE	b	SE
Inequality regime	.183***	.046	.235***	.045	−.067	.061	.172**	.049
Size of the workforce	.580***	.089	.552***	.090	.345**	.124	.391***	.097
Vertical differentiation	−.298**	.102	.152	.103	.080	.162	−.323**	.109
Civilianization	−.022**	.008	−.019*	.008	.009	.011	.011	.009
Community policing	.062	.052	.047	.052	.047	.072	.138*	.056
Crime rate	1.188***	.141	.859***	.132	1.368***	.214	.891***	.144
Disadvantage and instability	−.096	.101	−.462***	.101	−.242	.140	−.463***	.107
Percent Black	.270**	.087	.455***	.088	.195	.119	.093	.096
Percent youth	−.091	.293	.005	.301	.312	.412	.933**	.312
Constant	−6.951***	1.356	−5.458***	1.307	−9.674***	2.048	−8.251***	1.409
	R ² = .19		R ² = .17		R ² = .19		R ² = .11

*p < .05. **p < .01. ***p < .001.

Turning our attention to the control variables, again the results highlight the importance of serious criminal activity in the implementation of disorder policing strategies. The results also suggest that the size of the sworn workforce is strongly related to the arrest rate for the four order maintenance measures. Vertical differentiation was associated with lower arrest rates for disorder offenses and liquor law violations, while community economic disadvantage and instability were associated with fewer arrests for marijuana possession and liquor law violations.⁵

Post Hoc Tests

Post hoc tests were conducted to help determine which control variable was associated with the change in the Black arrest rate results from the bivariate to the multivariate models. It is important to know whether the change in the relationship is because a control variable is functioning as a suppressor (i.e., changes in the relationship are due to the variable reducing the error of the model residuals) or whether the change is a result of a moderated relationship (i.e., an interaction effect where the relationship between inequality and Black arrest rates is different under a third condition). A series of regression models were estimated to determine which control variable was associated with the change. Only the variable for the size of the agency produced significant changes in the estimated relationship between inequality and the Black arrest rate measures. To test for a moderated relationship, the measure for the size of the agency was mean centered and the interaction effect estimated with the inclusion of all other control variables.⁶ The results suggest that there was a statistically significant interaction between inequality and size of the agency for disorder offenses (interaction effect b = .144, SE = .029, p < .001; simple main effect for inequality b = .178, SE = .045, p < .001; simple main effect for size b = .693, SE = .091, p < .001), marijuana possession (interaction effect b = .119, SE = .029, p < .001; simple main effect for inequality b = .248, SE = .045, p < .001; simple main effect for size b = .651, SE = .093, p < .001), and liquor law violations (interaction effect b = .062, SE = .032, p = .049; simple main effect for inequality b = .170, SE = .049, p = .001; simple main effect for size b = .446, SE = .100, p < .001). The interaction coefficients suggest that the effect of inequality regimes on order maintenance policing is significantly stronger for larger organizations.

Discussion

The findings from this study suggest that inequality regimes are institutionalized systems of social processes within U.S. law enforcement agencies that influence the organizing principles regarding the means for achieving public safety. In theory, inequality regimes in policing reflect beliefs about how work should be structured as well as the distribution of resources and the patterns of behavior and interactions necessary for achieving safe and healthy communities. The results of this study suggest that aggressive order maintenance arrests are more likely to be defined as the means for achieving public safety when the organization is characterized by a strong inequality regime, defined as a homogeneous workforce, limited in diversity.

The findings from this study also suggest that the patterns of social relations grounded in inequality and reflected in arrest-driven aggressive order maintenance strategies directly affect people of color. Greater race, class, and gender inequality was associated with higher order maintenance arrest rates of Black residents even after organizational size and complexity, crime rates, and other community-based criminogenic factors were controlled. It is important to emphasize that in this study, we looked at the impact of inequality regimes on the enforcement of relatively minor offenses, but the consequences of being arrested and processed in the criminal justice system are severe. For example, in an influential work, Alexander (2012) discussed how the cycling of young Black men in and out of the U.S. prison system has created a new undercaste of people who are permanently relegated to second-class status by law. The collateral consequences of being involved in the criminal justice system are wide reaching and long lasting and include legal penalties, such as loss of the right to vote, ineligibility for social benefits, and loss of custody of one’s own child, as well as informal ramifications such as being discriminated against regarding employment or housing (Chesney-Lind & Mauer, 2003; Garland, 2001; Travis & Waul, 2003). The decision to utilize large-scale arrest-driven aggressive order maintenance strategies has serious consequences for community members, especially for people of color.

Moving forward, scholars should focus attention on understanding how the idea of social exclusion or social marginalization translates into values that affect police decision-making. For example, the perspective presented in this article calls attention to the idea that the sociodemographic characteristics of the workforce shape how the organization is socially constructed, in terms of how it defines the goals and means for the agency and how it describes its relationship to other stakeholders in the community. One possible perspective is that increasing diversity within the workforce results in an organization that is more inclusive and works with a greater variety of stakeholders in designing and implementing interventions (see Sklansky, 2006). Another possible perspective is that reducing inequality regimes creates a workforce that has more tools for dealing with crime problems in diverse communities. For example, Sun and Payne (2004) found that Black officers were more likely than White officers to engage in supportive actions in predominately Black neighborhoods. Perhaps departments with greater diversity have more organizational capacity for problem-solving strategies than organizations with less equality. Another possible avenue for new research is the perspective that workforce inequality regimes limit organizational learning. Sorenson (2003)] found that vertically integrated companies learn more from their experiences in challenging environments than nonintegrated firms.

In addition to the theoretical contributions, the findings from this study have important practical ramifications for public policy. More resources need to be dedicated to challenging and changing inequalities within police organizations. Although the numerical representation of diversity has increased in U.S. police forces in the past several decades, the reproduction of inequality within agencies and how they do their work has not. Experiences of officer integration suggest that inequalities are increasingly reinforced through employee interactions, divisions of labor and power, and organizational policies and practices (Shelley et al., 2011). According to Acker (2006), change efforts are possible but must target a limited set of inequality-producing mechanisms, have social movement and legislative support outside the organization as well as active support from insiders, and leverage coercion or threat of loss. Applied to policing, there are a few obvious inequality-producing mechanisms with which to initiate the change efforts: The recruitment and promotional processes must be revised to include diverse recruits, policies must be examined to identify exclusionary practices, and finally, the division of labor in the organization that gives rise to the feminization or racialization of police tasks must be challenged. Through everyday interactions, these systematic disparities in power and control are reproduced, reducing the legitimacy of diverse voices and ultimately their impact on policy making in the organization.

Although Acker (2006) cautioned readers that a focus on delimited areas of inequality, such as gender and racial imbalance in job categories, does nothing to address underlying organizational class inequality, she also noted that leaders have the potential to challenge the visibility and legitimacy of gender inequalities. For this reason, police agencies must continue to find ways to encourage a diverse pipeline to leadership. Currently, the basic organization of rank masks and legitimizes inequality, as rank makes visible inequalities perfectly legitimate. Diversity in leadership is important because it not only challenges the legitimacy of inequality but also makes it visible in highly bureaucratic police agencies where paying wages and maintaining supervisory oversight are tasks associated with rank. These efforts must move policing beyond tokenism in promotional representation.

Like all research, this study is not without limitations. Although the data are drawn from a national sample of police departments, some organizations do not report arrests for Part II offenses, and the quality of the information varies across agencies. The calculations for the Black disorder arrest rate were produced using population data from the ACS survey rather than the UCR survey and thus may over- or underestimate the Black population in some jurisdictions. Furthermore, the data in this study represent only one point in time, and inequality is theorized to change over time. Thus, the generalizability of these results over time is not known. Despite these limitations, we believe that the findings from this study are important and meaningful. This research represents one of only a few studies that examine whether inequality regimes within the workforce affect how organizations provide services to their customers.

In conclusion, as many police agencies across the nation face a legitimacy crisis, prompted by national concerns about how police interact with the communities they are sworn to protect, particularly in those neighborhoods with a large percentage of young men of color, the results of this study confirm that police agencies with workforce inequality replicate social exclusion in their public safety strategies. Specifically, stronger inequality regimes are associated with patterns of social relations grounded in inequality and reflected in arrest-driven aggressive order maintenance strategies that directly affect people of color. Acker’s framework of inequality regimes suggests a solution: Law enforcement agencies must begin to examine how increasing race, class, and gender diversity in their workforce may be a catalyst for justice-centered practices and policies that are more responsive to the public they police.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

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