A Sense of Injustice Loosens the Moral Bind of Law

Abstract

Existing literature demonstrates a clear connection between perceptions of procedural injustice and offending behaviors. Despite this connection, the mechanisms through which procedural injustice influences offending remain theoretically underdeveloped. To address this gap, the current study proposes that techniques of neutralization can be used to further develop our understanding of the connection between procedural injustice and criminal behavior. Using longitudinal data from the Gang Resistance Education and Training (GREAT) program, the links between procedural injustice, techniques of neutralization, and offending are explored. Results show that the effect of procedural injustice on offending is partially mediated by individuals’ neutralization attitudes. This finding expands the scope of procedural justice theory by demonstrating that procedural injustice is associated with attitudes conducive to criminal behavior rather than only the behavior itself.

Keywords

procedural justice techniques of neutralization criminal behavior offending police legitimacy

Tyler’s (1990) normative model of justice suggests that people are more likely to obey the law when they view authority figures such as the police as legitimate. The framework—often referred to as procedural justice theory or the process-based model of regulation—suggests that police legitimacy and compliance with the law are obtained not through threats of force or punishment, but through fair procedures that emphasize honesty and respect during officer decision-making processes and interactions with the public (Lind & Tyler, 1988; Thibaut & Walker, 1975; Tyler & Blader, 2003). The theory has been shown to explain a wide range of outcomes including cooperation with the police, compliance with officer directives, and positive evaluations of law enforcement (see, for example, Kochel, Parks, & Mastrofski, 2013; Murphy, Tyler, & Curtis, 2009; Reisig & Lloyd, 2009; Sunshine & Tyler, 2003). Of particular relevance to criminologists, Tyler’s framework has become an often-tested and routinely supported theory of criminal behavior over the past decade (Paternoster, Brame, Bachman, & Sherman, 1997; Reisig, Bratton, & Gertz, 2007; Reisig, Wolfe, & Holtfreter, 2011; Tyler & Fagan, 2008).

Procedural justice theory proposes that the perception of fair police treatment decreases offending behavior—at least in part due to its impact on legitimacy evaluations. A consistent theme in the literature, however, reveals that procedural justice has an independent effect on offending behavior even after accounting for perceptions of legitimacy (Murphy et al., 2009; Paternoster et al., 1997). In other words, a perceived sense of injustice at the hands of the police is shown to increase criminal behavior. What is more, emerging literature provides strong evidence that procedural justice may simply be a component of legitimacy evaluations (rather than an antecedent), suggesting that procedural injustice has both a theoretically justified and empirically supported connection with offending (see, for example, Tankebe, 2013).

The problem, however, is that the impact of procedural injustice on criminal behavior has been theoretically underdeveloped to date. Little attention has been devoted to specifying potential mechanisms that link a sense of injustice to greater offending. To address this gap, we propose that Sykes and Matza’s (1957) techniques of neutralization can help explain why procedural injustice is associated with criminal offending. Specifically, we explore how a sense of injustice makes an individual more likely to utilize Sykes and Matza’s techniques to neutralize their normative values. During the period of “drift” that results from the neutralization of conventional values, an individual is more likely to engage in criminal behavior (Matza, 1964).

The present study uses three waves of panel data from the Gang Resistance Education and Training (GREAT) study to test the hypothesis that techniques of neutralization play an important mediating role in explaining procedural injustice’s impact on offending. In doing so, this study demonstrates that perceptions of police procedural injustice are associated with greater use of neutralization techniques and that the relationship between procedural injustice and criminal behavior is mediated by the use of such neutralizations.

Procedural Justice Theory

Procedural justice theory is fundamentally a control-based framework. According to Tyler’s (1990) model, perceptions of procedural justice increase evaluations of legitimacy and make people less likely to break the law. If authority figures such as the police are perceived to behave in manners consistent with our normative expectations—treating people with respect, honesty, and fairness—individuals’ commitment to conventional behaviors, such as compliance with the law, is reinforced (Tyler, 1990). In other words, procedurally fair policing increases citizens’ commitment to societal norms. The perception of procedural fairness can, therefore, be viewed as a bonding mechanism that inhibits engagement in deviant or criminal behavior. Perceptions of procedural injustice violate normative expectations concerning police behavior and, therefore, may erode individuals’ commitment to conventional values and actions. People who perceive procedural injustice—officers behaving in manners that run counter to society’s expectations—may be more likely to question whether they should respect police authority or the laws the police represent (Jackson, Hough, Bradford, Hohl, & Kuha, 2012). In short, perceptions of procedural injustice may loosen the bond of normative values concerning legal compliance and, thereby, open the door for criminal behavior.

Tyler and Blader’s (2003) group engagement model is useful for explaining in further detail how procedural justice impacts an individual’s attachment to the norms and values of society. According to the model, an individual’s perception of procedural justice influences his or her social identity. Perceived procedural justice reaffirms an individual’s status and position in the group and reinforces the idea that he or she is a valued member of society. In contrast, perceptions of procedural injustice communicate to individuals that they are not of equal status to the authority figure (i.e., the police officer) and send the message that they are not valued members of society. These evaluations of social identity then influence the degree to which the person will continue to engage in the group dynamic. From a larger societal view, this implies that an individual who perceives procedural injustice at the hands of the police will have their social identity compromised and be less likely to align themselves with societal norms and values (Bradford, 2012; Murphy, 2013).

This theoretical argument, although important for further specifying the link between procedural injustice and increased criminality, still leaves a gap regarding the causal mechanisms that may underlie the relationship. Although a compromised social identity resulting from perceived injustice may result in withdrawal from group values and norms, the manner in which this may influence criminal behavior is left vague by the theory. In response to this issue, scholars have recently begun examining the importance of procedural justice when variables from other criminological theories are added to the analytical model (A. R. Piquero, Gomez-Smith, & Langton, 2004; Reisig et al., 2011; Sherman, 1993; Wolfe, 2011). This work, however, has largely been limited to examining how procedural justice interacts with and relates to these other theories. In other words, the body of work examines the conditions under which procedural justice predicts offending behaviors rather than specifying the mechanism through which procedural justice influences offending. This is an important distinction as the former evaluates the predictive power of procedural justice whereas the latter helps to inform the causal theoretical model. An important exception to this trend was a recent study by Barkworth and Murphy (2015) who utilized Agnew’s general strain theory to demonstrate that negative emotion is an important mediator of procedural justice’s impact on compliant behavior. In other words, procedural injustice tends to arouse anger and resentment, which ultimately leads to greater criminal involvement. This finding is encouraging because it suggests that continued research attempting to explore the connection between procedural injustice and offending may prove fruitful.

Sykes and Matza’s (1957) neutralization theory has a logical fit with procedural justice theory because it is consistent with Tyler’s (1990) normative framework. First, the framework proposes that individuals engage in crime as a function of normative values and beliefs rather than instrumental concerns regarding the costs and benefits of crime—similar to Tyler’s theory. Second, neutralization theory is also a control framework, arguing that juveniles engage in delinquency when their normative values are neutralized (i.e., when the normative control is lifted). Neutralization theory and its link with procedural justice theory are explored in greater detail below.

Techniques of Neutralization

In contrast to subcultural theories of delinquency, Sykes and Matza’s (1957) techniques of neutralization suggest that juveniles do not engage in delinquency as a result of having different normative values and beliefs from society at large. Instead, “the juvenile delinquent would appear to be at least partially committed to the dominant social order” (Sykes & Matza, 1957, p. 666). According to the theory, juveniles engage in delinquency when they successfully neutralize their normative beliefs concerning conformity. Sykes and Matza suggest that juveniles neutralize their normative beliefs through one of five techniques: denial of responsibility (e.g., the individual had no choice but to commit the crime), denial of injury (e.g., the individual feels no real harm resulted from his or her action), denial of the victim (e.g., the individual felt the victim had it coming), condemnation of the condemners (e.g., everyone does it, so why is it wrong for the individual to do it), or appeal to higher loyalties (e.g., the individual committed a crime to protect friends or to save his or her reputation). Such attitudes allow people to neutralize their normative beliefs concerning respect for authority figures and obeying the law. By engaging these neutralizations, the normative beliefs that typically constrain delinquency are rendered ineffective and the juvenile is able to engage in offending without compromising his or her values. Neutralizations have been shown to be important in understanding behaviors as diverse as rape proclivity (Bohner et al., 1998), white-collar criminality (A. R. Piquero, Tibbetts, & Blankenship, 2005; Vieraitis, Piquero, Piquero, Tibbetts, & Blankenship, 2012), and employee theft (Hollinger, 1991). Maruna and Copes (2005), for example, highlighted the importance of techniques of neutralization in a summary of nearly 50 years of research. Importantly, however, Maruna and Copes also provided a convincing argument that, despite wide support for the key elements of the framework, it has yet to experience much theoretical refinement.

Similar to procedural justice theory, aspects of neutralization theory are left vague by its theorists. Specifically, Sykes and Matza (1957) did not fully explain the mechanisms by which an individual engages techniques of neutralization. For example, they argue that neutralization techniques are learned but provide no discussion on how or why such neutralizations manifest (Sykes & Matza, 1957). In related work, Matza (1964) attempted to explain delinquency as a function of drift which is defined as an “episodic release from moral constraint” (p. 69) that is made possible by the implementation of neutralizations. As Matza (1964) succinctly puts it, “Neutralization enables drift” (p. 176). Accordingly, the source of neutralization techniques that allow drift into offending behavior is an important topic. One source of neutralizing attitudes may be the perception of injustice at the hands of the police—a topic we turn to next.

Techniques of Neutralization and Procedural Injustice

Matza’s (1964) explanation of drift and delinquency provides a theoretical foundation for linking procedural injustice and techniques of neutralization. Specifically, in describing the conditions under which drift is likely to occur, Matza (1964) stated that “the moral bind of law is loosened whenever a sense of injustice prevails” (p. 102). In other words, the normative control that law exerts is weakened when an individual perceives that injustice exists at the hands of those who represent the law. Bradford, Murphy, and Jackson (2014) further connected neutralizations and drift to procedural justice by noting that a procedurally unjust perception may result in a compromised social identity, which then “result(s) in a sense of anomie or drift (Matza, 1964), and a loosening of normative constraints on behavior” (p. 529).

Given these existing ideas, merging the key propositions contained in procedural justice theory and neutralization theory is easily accomplished. The sense of injustice previously noted by Matza is specifically in reference to criminal justice officials. As he notes, “Antagonism takes the form of a jaundiced view of officials, a view which holds that their primary function is not the administration of justice, but the perpetration of injustice” (Matza, 1964, pp. 101-102). This attitude toward criminal justice officials closely matches the perceptions that Tyler (1990) described as procedural injustice. Tyler highlighted how judgments regarding the legitimacy of legal authorities are linked to whether criminal justice officials are viewed as honest, free of bias, and polite. Alternatively, illegitimacy is linked to perceptions of officials as rude, biased, and dishonest—perpetrators of injustice.

It is important to note that Sykes and Matza’s (1957) original presentation of neutralization theory suggested that perceptions of injustice in the form of condemnation of the condemners—“The police are corrupt, stupid, and brutal” (p. 668)—is itself a neutralization technique. The problem, however, is that this attitude does not inherently allow for the neutralization of conventional values. Viewing the police as unfair (or even corrupt) is not condemning the condemners in a manner that allows drift. Rather, this attitude may set the stage for techniques of neutralization that allow drift into delinquency. Matza’s (1964) refinement of the theory addresses this issue by suggesting that perceptions of injustice are actually a precursor to neutralization techniques. As Matza (1964) argued, “Injustice is the underlying condition of drift. It is . . . a preface to the assertion of irresponsibility . . .” (p. 104). Thus, the perception of police procedural injustice may lead an individual to be more likely to engage in techniques of neutralization resulting in a state of drift that increases the individual’s tendency to engage in criminal activity. Interestingly, the organizational behavior literature on workplace deviance has examined the link between procedural justice and neutralization techniques and would anticipate such a theoretical and empirical connection in the context of criminal behavior.

Techniques of Neutralization, Procedural Injustice, and Organizational Studies

The concepts of procedural justice and legitimacy, along with an emphasis on decision-making processes rather than outcomes, have roots in the field of social psychology (Lind & Tyler, 1988; Thibaut & Walker, 1975). Scholars have examined how unfair treatment by supervisors or employers is a potential cause of workplace deviance (Aquino, Lewis, & Bradfield, 1999; Greenberg, 1990; Skarlicki & Folger, 1997; Wolfe & Piquero, 2011). For example, being treated unfairly by authority figures at work causes individuals to become dissatisfied with their work situation. Dissatisfaction, in turn, leads to counterproductive work behaviors (Aquino et al., 1999). Furthermore, some research has used the neutralization framework to understand employee deviance, such as theft from the workplace, and production deviance—counterproductive work behaviors such as taking unauthorized breaks or excessive expense account reimbursement (Dabney, 1995; Hollinger, 1991).

Recognizing the success of both theories in explaining workplace deviance, Lim (2002) evaluated Internet abuse in the workplace using the frameworks of organizational justice (which include procedural justice) and neutralization techniques. Lim argued that employees who are treated less fairly by their employer are more likely to utilize a neutralization technique called the metaphor of the ledger (a belief that individuals are entitled to engage in deviant behavior because the company owes them), and subsequently engage in cyberloafing—using the Internet at work for personal as opposed to business-related tasks. Supporting these arguments, Lim found that workers who viewed their organization as less procedurally fair were more likely to adhere to the metaphor of the ledger. This technique of neutralization was measured by asking the workers their level of agreement to the following questions:

In my opinion it is alright for me to use the internet for non-job related reasons if I: (a) have to put in extra work because I do not receive enough help and equipment; (b) were asked to do excessive amounts of work; and (c) have to put in extra time at work to get the job done. (Lim, 2002, pp. 684-685)

It is important to note that these neutralization measures capture perceptions rather than actual behavior. In turn, these neutralization techniques were related to higher levels of self-reported cyberloafing behavior. Thus, perceptions of organizational injustice were associated with greater use of neutralization techniques, which in turn were associated with deviant behavior.

In further support of the importance of neutralization techniques, follow-up interviews presented by Lim (2002) demonstrated that many respondents who utilized the techniques and engaged in cyberloafing still found the behavior to be wrong in principle. This is consistent with the argument put forth by Sykes and Matza (1957) and Matza (1964) that offenders have the same normative values as nonoffenders but are able to neutralize those values to engage in deviant behavior. Despite Lim’s success in demonstrating links between procedural injustice, techniques of neutralization, and cyberloafing, there is a surprising gap in the literature concerning how these concepts impact other deviant behaviors including criminal activity. Importantly, however, this line of inquiry clearly suggests that such a link may exist.

Current Focus

The present study attempts to specify a mechanism by which perceptions of procedural injustice are associated with offending. As discussed above, techniques of neutralization provide a theoretical framework for specifying this connection. Drawing on the theoretical work of Sykes and Matza (1957) and Matza (1964) and the empirical evidence from organizational researchers such as Lim (2002), we examine the following question: Do techniques of neutralization mediate the effect of procedural injustice on criminal behavior? Addressing this question is important because it will help clarify the pathway by which perceptions of procedural injustice influence criminal involvement. In addition, evidence pertaining to this issue may help extend the scope of procedural justice theory by revealing that not only does it account for offending behaviors but also attitudes conducive to the commission of delinquent acts.

Method

Data

Data for the present study come from the longitudinal survey component of the GREAT program (Esbensen, 2003). This data set is well suited for examining our research question because it includes measures regarding individuals’ perceptions of the police that are consistent with the literature on procedural justice, items concerning individuals’ attitudes toward several techniques of neutralization, and measures capturing self-reported offending behaviors. In addition, this data set allows for the correct temporal ordering of our variables of interest. The GREAT study selected 22 schools in six different cities—Phoenix (Arizona), Lincoln (Nebraska), Omaha (Nebraska), Las Cruces (New Mexico), Portland (Oregon), and Philadelphia (Pennsylvania)—to collect data. The longitudinal interview portion of the study surveyed more than 3,000 middle school students over 6 years. For the current study, we utilized three waves of panel data from the longitudinal portion of the GREAT study. Specifically, Waves 2, 3, and 4 (hereafter referred to as Times 1, 2, and 3, respectively) were used in the analysis.¹ The key independent variable, procedural injustice, was measured at Time 1; the key mediator variable, techniques of neutralization, was captured at Time 2; and the dependent variable, offending, was assessed at Time 3. Retention rates were 76%, 69%, and 67% for Times 1, 2, and 3, respectively (see Esbensen et al., 2001).

This allowed for the temporal ordering necessary to evaluate the potential mediating effect of neutralization techniques on the relationship between perceptions of procedural injustice and offending. Multiple imputation by chained equations (MICE) was used to deal with missing data (available in Stata 13; 10 iterations were performed). Multiple imputation has been shown to provide more valid results than either listwise deletion or single imputation strategies (see Acock, 2005; Allison, 2001; Carlin, Galati, & Royston, 2008; Gmel, 2001; Johnson & Young, 2011; Royston, 2005).

Measures

Offending

To capture offending behaviors, participants were asked how many times in the past 6 months they committed 16 different crimes. These offenses ranged in severity from “illegally spray painted a wall or building” to “used a weapon or force to get money or things from people” (Esbensen, 2003; see the appendix for a full list of items). Offending was operationalized as a variety score of the 16 items. Specifically, positive responses on each of the items were coded as a 1, and all items were then summed to create a count of the number of different crimes that an individual had committed in the 6 months leading up to the Time 3 interview (α = .86). Variety scores have been shown to be highly correlated with frequency scores, especially among adolescents who are unlikely to be specialized offenders (Monahan & Piquero, 2009), and tend to be the preferred measurement strategy (Sweeten, 2012). Table 1 provides descriptive statistics for all variables used in the current analyses.

Table 1:

Descriptive Statistics

	M or %	SD	Minimum	Maximum
Dependent variable
Offending variety score_(T3)	2.31	2.96	0.00	16.00
Key independent variables
Procedural injustice_(T1)	16.12	4.80	6.00	30.00
Neutralization techniques_(T2)	26.14	7.35	9.00	45.00
Control variables
Low self-control_(T1)	22.51	5.86	8.00	40.00
Parental supervision_(T1)	15.37	3.14	4.00	20.00
Delinquent peers^a_(T1)	2.94	0.35	2.64	4.25
Male	49%	—	0.00	1.00
Age_(T1)	12.33	0.68	10.00	19.00
Black	17%	—	0.00	1.00
Latino/a	21%	—	0.00	1.00
Other minority	16%	—	0.00	1.00
Gang membership	4%	—	0.00	1.00

Natural log transformation.

T3 = Time 3. T2 = Time 2. T1 = Time 1.

Procedural Injustice

Perceptions of procedural injustice were measured by asking respondents how much they agreed on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree) with the following statements: “Police officers are honest” (reverse coded), “Most police officers are usually rude,” “Most police officers are usually friendly” (reverse coded), “Police officers are usually courteous” (reverse coded), “Police officers are respectful toward people like me” (reverse coded), and “Police officers are prejudiced against minority persons.” These items captured key aspects of procedural justice such as neutrality, respect, and trustworthiness. The items demonstrated strong internal consistency and were summed to create an additive scale (α = .84). Higher values on the scale indicate greater perceived procedural injustice.

Techniques of Neutralization

Individuals’ techniques of neutralization were captured by asking respondents how much they agreed with a series of nine statements (1 = strongly disagree to 5 = strongly agree). A variety of neutralizations were measured including those that tap into denial of injury (“It’s okay to steal something from someone who is rich and can easily replace it”), denial of responsibility (“It’s okay to steal something if that’s the only way you could ever get it”), denial of victim (“It’s okay to get into a physical fight with someone if they hit you first”), and appeal to higher loyalties (“It’s okay to lie if it will keep your friends from getting in trouble with parents, teachers, or police”; see the appendix for a full list of items). The items revealed strong internal consistency and were combined into an additive scale (α = .88). The scale was coded so that higher values indicate attitudes consistent with neutralization techniques.

Control Variables

To avoid observing potentially spurious relationships, several important statistical control variables measured at Time 1 were included in all multivariate models presented below. Low self-control was accounted for due to its demonstrated relationship with procedural injustice (see A. R. Piquero et al., 2004; Reisig et al., 2011; Wolfe, 2011), as well as its power in predicting criminal offending (see Pratt & Cullen, 2000). Low Self-Control is an eight-item summated scale that measures an individual’s tendency to act impulsively, be shortsighted, pursue immediate gratification, and take risks (e.g., “I often act on the spur of the moment without stopping to think”). All items were measured on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree; see the appendix for a full list of items). The items demonstrated strong internal consistency, and the scale was coded so higher values indicate lower levels of self-control (α = .83).

In addition, a measure of parental supervision was used due to the well-documented parenting effect on delinquent behavior among juveniles (Kemp, Scholte, Overbeek, & Engels, 2006; Miller, Esbensen, & Freng, 1999). Parental supervision was measured by asking respondents how much they agreed with four statements regarding their parents’ monitoring behaviors (e.g., “My parents know where I am when I am not at home or at school”; see the appendix for full list of items). Items were measured on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). The items were summed to create a four-item scale with higher values indicating greater parental supervision (α = .73).

A measure of delinquent peer association was also included in the analysis given its documented connection with offending, both broadly and within the GREAT data set (Higgins, Ricketts, Marcum, & Mahoney, 2010; Thomas & McGloin, 2013). The adolescents’ association with delinquent peers was assessed by asking them how many of their friends engaged in each of 14 illegal activities. Items ranged in severity from “Purposely damaged or destroyed property that did not belong to them?” to “Used a weapon or force to get money or things from people?” (see the appendix for a full list of items). Response categories on each item were anchored by 1 (none of them) and 5 (all of them). The items demonstrated strong internal consistency and were summed to create a scale with higher values indicating more delinquent peers associations (α = .94). A natural log transformation was used to induce normality (skewness = 1.41).

In addition to the controls listed above, the models accounted for several demographic characteristics including male (1 = yes) and age (in years). Participant race and ethnicity were accounted for by using three dummy variables: Black (1 = yes), Latino/a (1 = yes), and Other minority (1 = yes). White served as the reference category. Consistent with previous studies using the GREAT data set, we also controlled for whether the adolescents self-reported gang membership (1 = yes; see, for example, Turanovic & Pratt, 2013, 2014).

Analytic Strategy

The analysis proceeds in a series of steps. First, we examine the extent to which perceptions of procedural injustice are associated with individuals’ attitudes concerning techniques of neutralization. Ordinary least squares (OLS) regression is used to estimate this model because the outcome—techniques of neutralization—is well behaved and approximates a normal distribution (skewness = 0.05). This step of the analysis is important because it allows us to determine whether individuals who perceive procedural injustice are more likely to hold attitudes favorable toward techniques of neutralization. Furthermore, this will establish a necessary condition for detecting mediation in later steps of the analysis (i.e., the independent variable is correlated with the hypothesized mediator variable; see Baron & Kenny, 1986). In the second stage of the analysis, we estimate two negative binomial regression equations. The influence of procedural injustice on offending, net of statistical controls, is assessed in the first model. This provides a baseline estimate of the procedural injustice effect on criminal behavior. The techniques of neutralization scale is added to the equation in the second model. This segment of the analysis allows us to test the primary research question of the present study:

Research Question 1: To what extent do neutralizations mediate the connection between procedural injustice and offending?

Negative binomial regression is used to estimate each of these models because descriptive statistics indicate that the offending scale is overdispersed (M = 2.31, variance = 8.76).² Robust standard errors that adjust for the clustering on respondent classroom are used in all equations.

Results

The first question of interest is whether individual perceptions of procedural injustice are associated with techniques of neutralization among adolescents in this sample. The OLS model featured in Table 2 addresses this issue. The measure of joint association indicates that the specified model provides better prediction of the dependent variable than a constant-only model (F test = 42.32, p < .01). The variables also account for a moderate level of the variation in neutralization techniques (R² = .31). Consistent with expectations, the procedural injustice estimate is statistically significant at the .01 level (b = 0.24). This finding conforms to our expectation: Individuals who perceive higher levels of police procedural injustice hold more attitudes favorable to neutralization techniques. It appears that procedurally unfair police behaviors are associated with a weakening of normative values concerning compliance with the law. In other words, adolescents are more likely to neutralize their conventional norms when they perceive injustice. It is important to note that this relationship was observed while accounting for parental supervision (b = −0.17, p < .05), delinquent peer associations (b = 4.87, p < .01), and low self-control (b = 0.30, p < .01), all of which had statistically significant effects on the neutralization scale in the expected direction. A comparison of the standardized partial regression coefficients reveals that low self-control (β = .24) and delinquent peers (β = .21) have slightly stronger effects than the procedural injustice scale (β = .15). Importantly, however, it is clear that the procedural injustice effect on neutralization techniques is not trivial.

Table 2:

The Procedural Injustice Effect on Techniques of Neutralization

	Techniques of Neutralization^a
Variables	b (SE)	β
Procedural injustice	0.24** (0.04)	.15
Low self-control	0.30** (0.04)	.24
Parental supervision	−0.17* (0.07)	−.07
Delinquent peers	4.87** (0.71)	.21
Male	1.70** (0.38)	.12
Age	0.33 (0.30)	.03
Black	0.92 (0.53)	.04
Latino	1.62** (0.50)	.08
Other minority	0.67 (0.53)	.03
Gang membership	−0.11 (1.16)	.00
Constant	−1.27 (4.02)	—
F test	42.32**
Adjusted R²	.31
n	1,393

Note. Entries are unstandardized partial regression coefficients (b), robust standard errors that adjust for clustering on classroom in parentheses (SE), and standardized partial regression coefficients (β). Adjusted R² and standardized regression coefficients represent the average estimate across all 10 imputations and are obtained using the mibeta command in Stata 13. OLS = ordinary least squares.

OLS regression equation.

p < .05. **p < .01 (two-tailed test).

Table 3 provides the results concerning our primary question of theoretical interest, whether the influence of procedural injustice on offending is mediated by individuals’ techniques of neutralization. In the first negative binomial equation, the criminal offending variety score is regressed onto procedural injustice and the statistical controls (Model 1 in Table 3). This model specification proves superior to a constant-only model in terms of predictive ability (F test = 19.21, p < .01). Perceived procedural injustice is positively and significantly associated with offending (b = 0.02, p < .01). Individuals who believe the police are unfair, dishonest, and disrespectful are more likely to engage in criminal behavior. In fact, the standardized effect presented in Table 3 (% StdX) demonstrates that a one standard deviation increase in the procedural injustice scale increases the expected offending variety count by 10.6%. This finding is consistent with a large number of previous studies on procedural justice and offending and, therefore, increases our confidence in the validity of the data and procedural injustice scale. It is also important to highlight that low self-control (b = 0.02, p < .01), parental supervision (b = −0.04, p < .01), and delinquent peers (b = 0.89, p < .01) were associated with offending in the expected directions, which provide further confidence in the data and analysis. In addition, this equation provides a baseline understanding of the procedural injustice effect to be contrasted with the next model.

Table 3:

The Procedural Injustice Effect on Offending

	Offending^a
	Model 1		Model 2
Variables	b (SE)	% StdX	b (SE)	% StdX
Procedural injustice	0.02** (0.01)	10.6%	0.01 (0.01)	4.7%
Techniques of neutralization	—	—	0.06** (0.01)	59.2%
Low self-control	0.02** (0.01)	13.9%	0.01 (0.01)	4.5%
Parental supervision	−0.04** (0.01)	−11.3%	−0.03* (0.01)	−7.1%
Delinquent peers^b	0.89** (0.14)	33.2%	0.60** (0.14)	21.7%
Male	0.13 (0.07)	7.4%	0.04 (0.07)	1.5%
Age	−0.07 (0.06)	−3.2%	−0.13* (0.06)	−4.6%
Black	−0.10 (0.14)	−3.1%	−0.15 (0.13)	−1.9%
Latino	0.18 (0.09)	9.6%	0.06 (0.09)	3.5%
Other minority	0.17 (0.12)	6.2%	0.12 (0.11)	6.4%
Gang membership	−0.22 (0.17)	−1.9%	−0.15 (0.20)	0.5%
Constant	−1.42 (0.86)	—	−1.06 (0.81)
F test	19.21**		30.89**
n	1,156		1,156

Note. Entries are unstandardized partial regression coefficients (b), robust standard errors that adjust for clustering on classroom in parentheses, and the percentage change in the expected offending variety count for a standard deviation increase in the independent variables (% StdX).

Negative binomial regression models.

Natural log transformation.

p < .05. **p < .01 (two-tailed test).

Model 2 introduces the techniques of neutralization scale to the equation and reveals several important findings. Conforming to expectations and previous literature, individuals with higher scores on the neutralization scale self-reported greater criminal involvement (b = 0.06, p < .01). Most important for the present study, we observe that the effect of procedural injustice is attenuated and drops below the traditional .05 statistical significance level with the inclusion of the neutralization scale. What is more, the standardized effects (% StdX) provide evidence that the neutralization scale clearly dominates the model. Each standard deviation increase in techniques of neutralization is expected to increase the offending variety count by 59%. The standardized effect of procedural injustice drops by more than half after accounting for individuals’ neutralization techniques (Model 1 % StdX = 10.6%; Model 2 % StdX = 4.7%). Importantly, however, a comparison of the maximum-likelihood regression coefficients reveals that the drop in the magnitude of the procedural injustice effect is not statistically significant (z = 1.02; see Brame, Paternoster, Mazerolle, & Piquero, 1998; Clogg, Petkova, & Haritou, 1995). Accordingly, the analyses presented in Table 3 reveal that perceptions of procedural injustice are associated with more criminal activity, and this relationship is partially mediated by neutralization techniques.³ Within this sample, perceived procedural unfairness seems to open the door for attitudes consistent with the neutralization of conventional norms which, in turn, increases participation in criminal behavior.

Discussion

Over the past several decades, social scientists have assessed the connection between perceptions of procedural justice and a wide range of outcomes, including legitimacy evaluations (Braga, Winship, Tyler, Fagan, & Meares, 2014; Jackson, Bradford, Stanko, & Hohl, 2012; Nix, Wolfe, Rojek, & Kaminski, 2015; Tyler, 1990; Wolfe, Nix, Kaminski, & Rojek, 2015), cooperation with the police (Bradford, 2012; Reisig, Tankebe, & Meško, 2012), and empowerment (Sunshine & Tyler, 2003). Compliance and offending are included in this literature as outcomes of interest. Overall, the empirical evidence reveals that individual perceptions of procedural injustice are associated with higher levels of criminal offending (Mazerolle, Bennett, Davis, Sargeant, & Manning, 2013; Tyler, 1990; Tyler & Huo, 2002). The causal connection between procedural injustice and offending, however, has yet to be empirically scrutinized in much detail. Although the relationship between procedural injustice and offending is important in and of itself, understanding the specific mechanisms that link the variables together can help improve procedural justice theory. The current study sought to overcome this gap. Using panel data from the GREAT program evaluation, the regression analyses provided four primary findings: (a) procedural injustice is positively linked with neutralization attitudes, (b) procedural injustice is associated with a greater variety of offending behaviors, (c) techniques of neutralizations are related to greater offending variety, and (d) the relationship between procedural injustice and offending is partially mediated by neutralization techniques. With these results in mind, several issues warrant further discussion.

Of primary concern to our study was the extent to which techniques of neutralization account for the effect of procedural injustice on offending. Among participants in our sample, we revealed that greater feelings of procedural injustice are associated with more criminal involvement. Answering our key question of theoretical interest, however, the data demonstrated that this connection is partially mediated by adolescents’ attitudes concerning neutralization techniques. This finding helps move the literature surrounding Tyler’s (1990) theory forward by specifying a potential causal mechanism by which perceptions of procedural injustice influence offending behaviors. Tyler’s (1990) conceptualization of procedural justice emphasizes normative commitment through legitimacy, as well as through personal morality. Normative commitment through legitimacy has been extensively explored in prior literature, yet Tyler argues that normative commitment through personal morality can also be effective at ensuring law-abiding behavior. The connection between techniques of neutralization and procedural injustice is consistent with Tyler’s normative commitment through personal morality. That is, perceptions of procedural injustice seem to make young people more likely to engage in techniques of neutralization, thus loosening “the moral bind of law” and allowing individuals to drift into criminal behavior (Matza, 1964, p. 102). In this way, procedural injustice at the hands of authority figures may not necessarily change individuals’ moral beliefs. Rather, such perceptions appear to weaken one’s attachment to authority figures, thereby hindering the social control function such a bond normally exerts. By acting in manners inconsistent with normative expectations, police officers who are procedurally unfair may make it easier for adolescents to neutralize their otherwise legally compliant values, thus paving the way for more criminal behavior.

The temporally ordered nature of the data used in the current study supports this potential causal sequence of events. However, more work must be done before definitive conclusions concerning the causal connection between these variables can be established. For one, we examined adolescents’ perceptions of police procedural fairness and were unable to disentangle whether these views were based on personal or vicarious experiences (e.g., observations, stories from friends, news stories, etc.). Given the differences sometimes observed between individuals who base their evaluations of the police on personal encounters rather than vicarious experiences (see, for example, Rosenbaum, Schuck, Costello, Hawkins, & Ring, 2005), future research needs to capture evaluations of procedural justice stemming from people’s direct encounters with the police. Such research would help shed more light on the degree to which procedurally unfair treatment causes individuals to use techniques of neutralization which, in turn, produce greater risk of criminal activity. Quasi-experimental designs may also help in this regard given the problems associated with longitudinal data collection capable of assessing these questions and the obvious issues related to random assignment in this line of inquiry (see Braga et al., 2014). Relatedly, future work based on the current study’s findings would be wise to capture evaluations of police legitimacy as well. We only measured procedural injustice in the current study, which neglects the potentially important mediating role of legitimacy on the offending link. As discussed earlier, recent research reveals that procedural justice may simply be a component of legitimacy or, at the least, has a significant relationship with offending after controlling for measures of legitimacy (Murphy et al., 2009; Paternoster et al., 1997; Tankebe, 2013). Still, research capable of capturing survey items that tap into Tyler and others’ conceptualizations of legitimacy may further illuminate the causal mechanisms relevant to procedural justice theory (Jackson, Bradford, et al., 2012; Tankebe, 2013; Tyler, 1990).

Next, the finding that procedural injustice is positively related to techniques of neutralization advances both neutralization theory and procedural justice theory. The finding is consistent with Matza’s (1964) argument that feelings of injustice are an important precursor to the activation of neutralization techniques that ultimately loosen individuals’ commitment to conventional values. This result fills an empirical and theoretical gap in the neutralization literature concerning the forces behind the manifestation of neutralization techniques. Procedural injustice appears to be an important precursor to the use of neutralization techniques. In short, where injustice is perceived, the moral bind to the law is weakened. Importantly, this observation also expands the scope of procedural justice theory by demonstrating that procedural injustice is associated with attitudes conducive to criminal behavior rather than only the behavior itself. In other words, perceptions of procedural injustice appear to be tied to individual attitudinal risk factors for criminal activity (Maruna & Copes, 2005). Future research could benefit from exploring the connection between procedural injustice and other important attitudes, such as definitions favorable to breaking the law (Akers, 2011; Sutherland, 1947), moral beliefs (Wikström, 2006), or commitment to conventional lines of action (Hirschi, 1969), to name a few. For example, the experience of procedural justice could serve as a teachable moment within the legal socialization process by reinforcing individuals’ attitudes favorable to legal compliance (A. R. Piquero, Fagan, et al., 2005; Reisig et al., 2011; Sampson & Bartusch, 1998; Tyler, 2011; Tyler, Fagan, & Geller, 2014).

Finally, from a policing standpoint, these findings further underscore the importance of procedurally fair policing. Procedurally just experiences can increase citizens’ social identity and suppress potential disengagement from societal norms. If perceptions of procedural injustice loosen an individual’s commitment to normative values, perceptions of procedural justice may tighten such a commitment. Strengthening conventional values and inhibiting disengagement from societal norms can prevent individuals from engaging in neutralizations and entering a state of drift. Importantly, this suggestion is wholly consistent with Tyler’s (2009) argument that procedural justice produces self-regulatory behavior. Thus, procedurally fair policing can extend social control over criminal activity.

In the end, we have shown that it is important for procedural justice scholars to push the envelope of the theory and explore the potential mechanisms by which procedural injustice is associated with offending. The current empirical status of procedural justice theory highlights its importance as a concept related to increased compliance and cooperation with criminal justice authorities, such as the police, court officials, and correctional officers. It is our hope that future researchers will continue to test the scope of the theory by further developing procedural justice’s explanatory power as a criminological framework. In addition, future researchers should continue to explore procedural justice’s relationship with other key outcomes such as cooperation and empowerment while leveraging other criminological theories. Theoretical development and empirical evidence that specify the mechanisms by which procedural justice influences such outcomes will help further our understanding of this important concept.

Footnotes

Appendix

Acknowledgements

The authors would like to thank Justin Nix for comments on an earlier draft of this article.

Notes

Kyle McLean is a doctoral student at the University of South Carolina. He received his master’s degree in criminology and criminal justice from the University of South Carolina. His research interests are in criminological theory, policing, and perceptions of crime and justice.

Scott E. Wolfe is an assistant professor in the Department of Criminology and Criminal Justice at the University of South Carolina. He received his PhD from Arizona State University in 2012. His research has appeared in a variety of scholarly journals, including Crime & Delinquency, Criminal Justice and Behavior, and Journal of Quantitative Criminology.

References

Acock

A. C.

(2005). Working with missing values. Journal of Marriage and Family, 67, 1012-1028.

Akers

R. L.

(2011). Social learning and social structure: A general theory of crime and deviance. Piscataway, NJ: Transaction Publishers.

Allison

P. D.

(2001). Missing data. Thousand Oaks, CA: SAGE.

Aquino

Lewis

M. U.

Bradfield

(1999). Justice constructs, negative affectivity, and employee deviance: A proposed model and empirical test. Journal of Organizational Behavior, 20, 1073-1091.

Barkworth

Murphy

(2015). Procedural justice policing and citizen compliance behavior: The importance of emotion. Psychology, Crime & Law, 21, 254-273.

Baron

R. M.

Kenny

D. A.

(1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182.

Bohner

Reinhard

Rutz

Sturm

Kerschbaum

Effler

(1998). Rape myths as neutralizing cognitions: Evidence for a causal impact of anti-victim attitudes on men’s self-reported likelihood of raping. European Journal of Social Psychology, 28, 257-268.

Bradford

(2012). Policing and social identity: Procedural justice, inclusion and cooperation between police and public. Policing & Society, 24, 22-43.

Bradford

Murphy

Jackson

(2014). Officers as mirrors: Policing, procedural justice and the (re)production of social identity. British Journal of Criminology, 54, 527-550.

10.

Braga

A. A.

Winship

Tyler

T. R.

Fagan

Meares

T. L.

(2014). The salience of social contextual factors in appraisals of police interactions with citizens: A randomized factorial experiment. Journal of Quantitative Criminology, 30, 599-627.

11.

Brame

Paternoster

Mazerolle

Piquero

(1998). Testing for the equality of maximum-likelihood regression coefficients between two independent equations. Journal of Quantitative Criminology, 14, 245-261.

12.

Carlin

J. B.

Galati

J. C.

Royston

(2008). A new framework for managing and analyzing multiply imputed data in Stata. Stata Journal, 8, 49-67.

13.

Clogg

C. C.

Petkova

Haritou

(1995). Statistical methods for comparing regression coefficients between models. American Journal of Sociology, 100, 1261-1293.

14.

Dabney

(1995). Neutralization and deviance in the workplace: Theft of supplies and medicines by hospital nurses. Deviant Behavior: An Interdisciplinary Journal, 16, 313-331.

15.

Esbensen

F.-A.

(2003). Evaluation of the Gang Resistance Education and Training (GREAT) program in the United States 1995-1999 (2nd ICPSR version). Omaha: University of Nebraska at Omaha [producer], 2002. Ann Arbor: University of Michigan, Inter-university Consortium for Political and Social Research [distributor].

16.

Esbensen

F.-A.

Osgood

D. W.

Taylor

T. J.

Peterson

Freng

(2001). How great is G.R.E.A.T.? Results from a longitudinal quasi-experimental design. Criminology & Public Policy, 1, 87-118.

17.

Freedman

L. S.

Schatzkin

(1992). Sample size for studying intermediate endpoints within intervention trials of observational studies. American Journal of Epidemiology, 136, 1148-1159.

18.

Gmel

(2001). Imputation of missing values in the case of a multiple item instrument measuring alcohol consumption. Statistics in Medicine, 20, 2369-2381.

19.

Greenberg

(1990). Employee theft as a reaction to underpayment inequity: The hidden cost of pay cuts. Journal of Applied Psychology, 75, 561-568.

20.

Higgins

G. E.

Ricketts

M. L.

Marcum

C. D.

Mahoney

(2010). Primary socialization theory: An exploratory study of delinquent trajectories. Criminal Justice Studies, 23, 133-146.

21.

Hirschi

(1969). Causes of delinquency. Berkeley: University of California.

22.

Hollinger

R. C.

(1991). Neutralizing in the workplace: An empirical analysis of property theft and production deviance. Deviant Behavior: An Interdisciplinary Journal, 12, 169-202.

23.

Jackson

Bradford

Stanko

E. A.

Hohl

(2012). Just authority? Trust in the police in England and Wales. Oxford, UK: Routledge.

24.

Jackson

Hough

Bradford

Hohl

Kuha

(2012). Policing by consent: Understanding the dynamics of police power and legitimacy. European Social Survey. Retrieved from http://ssrn.com/abstract=2168702

25.

Johnson

D. R.

Young

(2011). Toward best practices in analyzing datasets with missing data: Comparisons and recommendations. Journal of Marriage and Family, 73, 926-945.

26.

Kemp

R. A. T.

Scholte

R. H. J.

Overbeek

Engels

R. C. M. E

. (2006). Early adolescent delinquency: The role of parents and best friends. Criminal Justice and Behavior, 33, 488-510.

27.

Kochel

T. R.

Parks

Mastrofski

S. D.

(2013). Examining police effectiveness as a precursor to legitimacy and cooperation with police. Justice Quarterly, 30, 895-925.

28.

Lim

V. K. G.

(2002). The IT way of loafing on the job: Cyberloafing, neutralizing and organizational justice. Journal of Organizational Behavior, 23, 675-694.

29.

Lind

E. A.

Tyler

T. R.

(1988). The social psychology of procedural justice. New York, NY: Plenum Press.

30.

MacKinnon

D. P.

Lockwood

C. M.

Hoffman

J. M.

West

S. G.

Sheets

(2002). A comparison of methods to test mediation and other intervening variable effects. Psychological Methods, 7, 83-104.

31.

Maruna

Copes

(2005). What have we learned from five decades of neutralization research? Crime and Justice, 32, 221-320.

32.

Matza

(1964). Delinquency and drift. New York, NY: John Wiley.

33.

Mazerolle

Bennett

Davis

Sargeant

Manning

(2013). Procedural justice and police legitimacy: A systematic review of the research evidence. Journal of Experimental Criminology, 9, 245-274.

34.

Miller

M. H.

Esbensen

F.-A.

Freng

(1999). Parental attachment, parental supervision and adolescent deviance in intact and non-intact families. Journal of Crime & Justice, 22, 1-29.

35.

Monahan

K. C.

Piquero

A. R.

(2009). Investigating the longitudinal relation between offending frequency and offending variety. Criminal Justice and Behavior, 36, 653-673.

36.

Murphy

(2013). Policing at the margins: Fostering trust and cooperation among ethnic minority groups. Journal of Policing, Intelligence and Counter Terrorism, 8, 184-199.

37.

Murphy

Tyler

T. R.

Curtis

(2009). Nurturing regulatory compliance: Is procedural justice effective when people question the legitimacy of the law? Regulation & Governance, 3, 1-26.

38.

Nix

Wolfe

S. E.

Rojek

Kaminski

R. J.

(2015). Trust in the police the influence of procedural justice and perceived collective efficacy. Crime & Delinquency, 61, 610-640.

39.

Paternoster

Brame

Bachman

Sherman

L. W.

(1997). Do fair procedures matter? The effect of procedural justice on spouse assault. Law & Society Review, 31, 163-204.

40.

Piquero

A. R.

Fagan

Mulvey

E. P.

Steinberg

Odgers

(2005). Developmental trajectories of legal socialization among serious adolescent offenders. The Journal of Criminal Law and Criminology, 96, 267-298.

41.

Piquero

A. R.

Gomez-Smith

Langton

(2004). Discerning unfairness where others may not: Low self-control and unfair sanction perceptions. Criminology, 42, 699-733.

42.

Piquero

N. L.

Tibbetts

S. G.

Blankenship

M. B.

(2005). Examining the role of differential association and techniques of neutralization in explaining corporate crime. Deviant Behavior, 26, 159-188.

43.

Pratt

T. C.

Cullen

F. T.

(2000). The empirical status of Gottfredson and Hirschi’s general theory of crime: A meta-analysis. Criminology, 38, 931-964.

44.

Reisig

M. D.

Bratton

Gertz

M. G.

(2007). The construct validity and refinement of process-based policing measures. Criminal Justice and Behavior, 34, 1005-1028.

45.

Reisig

M. D.

Lloyd

(2009). Procedural justice, police legitimacy, and helping the police fight crime: Results from a survey of Jamaican adolescents. Police Quarterly, 12, 42-62.

46.

Reisig

M. D.

Tankebe

Meško

(2012). Procedural justice, police legitimacy, and public cooperation with the police among young Slovene adults. Journal of Criminal Justice and Security, 2, 147-164.

47.

Reisig

M. D.

Wolfe

S. E.

Holtfreter

(2011). Legal cynicism, legitimacy, and criminal offending: The nonconfounding effect of low self-control. Criminal Justice and Behavior, 38, 1265-1279.

48.

Rosenbaum

D. P.

Schuck

A. M.

Costello

S. K.

Hawkins

D. F.

Ring

M. K.

(2005). Attitudes toward the police: The effects of direct and vicarious experience. Police Quarterly, 8, 343-365.

49.

Royston

(2005). Multiple imputation of missing values: Update of ice. Stata Journal, 5, 527-536.

50.

Sampson

R. J.

Bartusch

D. J.

(1998). Legal cynicism and (subcultural?) tolerance of deviance: The neighborhood context of racial differences. Law & Society Review, 32, 777-804.

51.

Sherman

L. W.

(1993). Defiance, deterrence, and irrelevance: A theory of the criminal sanction. Journal of Research in Crime & Delinquency, 30, 445-473.

52.

Skarlicki

D. P.

Folger

(1997). Retaliation in the workplace: The roles of distributive, procedural, and interactional justice. Journal of Applied Psychology, 82, 434-443.

53.

Sunshine

Tyler

T. R.

(2003). The role of procedural justice and legitimacy in shaping public support for policing. Law & Society Review, 37, 513-548.

54.

Sutherland

E. H.

(1947). Principles of criminology. Chicago, IL: Lippincott.

55.

Sweeten

(2012). Scaling criminal offending. Journal of Quantitative Criminology, 28, 533-557.

56.

Sykes

G. M.

Matza

(1957). Techniques of neutralization: A theory of delinquency. American Sociological Review, 22, 664-670.

57.

Tabachnick

B. G.

Fidell

L. S.

(2012). Using multivariate statistics. Boston, MA: Pearson.

58.

Tankebe

(2013). Viewing things differently: The dimensions of public perceptions of police legitimacy. Criminology, 51, 103-135.

59.

Thibaut

Walker

(1975). Procedural justice. Hillsdale, NJ: Lawrence Erlbaum.

60.

Thomas

K. J.

McGloin

J. M.

(2013). A dual-systems approach for understanding differential susceptibility to processes of peer influence. Criminology, 51, 435-474.

61.

Turanovic

J. J.

Pratt

T. C.

(2013). The consequences of maladaptive coping: Integrating general strain and self-control theories to specify a causal pathway between victimization and offending. Journal of Quantitative Criminology, 29, 321-345.

62.

Turanovic

J. J.

Pratt

T. C.

(2014). “Can’t stop, won’t stop”: Self-control, risky lifestyles, and repeat victimization. Journal of Quantitative Criminology, 30, 29-56.

63.

Tyler

T. R.

(1990). Why people obey the law. New Haven, CT: Yale University Press.

64.

Tyler

T. R.

(2009). Legitimacy and criminal justice: The benefits of self-regulation. Ohio State Journal of Criminal Law, 7, 307-359.

65.

Tyler

T. R.

(2011). Trust and legitimacy: Policing in the USA and Europe. European Journal of Criminology, 8, 254-266.

66.

Tyler

T. R.

Blader

S. L.

(2003). The group engagement model: Procedural justice, social identity, and cooperative behavior. Personality and Social Psychology Review, 70, 349-361.

67.

Tyler

T. R.

Fagan

(2008). Legitimacy and cooperation: Why do people help the police fight crime in their communities? Ohio State Journal of Criminal Law, 6, 231-275.

68.

Tyler

T. R.

Fagan

Geller

(2014). Street stops and police legitimacy: Teachable moments in young urban men’s legal socialization. Journal of Empirical Legal Studies, 11, 751-785.

69.

Tyler

T.R.

Huo

Y.J.

(2002). Trust in the law: Encouraging public cooperation with the police and courts. New York, NY: Russell Sage Foundation.

70.

Vieraitis

L. M.

Piquero

N. L.

Piquero

A. R.

Tibbetts

S. G.

Blankenship

(2012). Do women and men differ in their neutralizations of corporate crime? Criminal Justice Review, 37, 478-493.

71.

Wikström

P. O. H.

(2006). Individuals, settings, and acts of crime: Situational mechanisms and the explanation of crime. In Wikström

P. O. H.

Sampson

R. J.

(Eds.), The explanation of crime: Context, mechanisms and development (pp. 61-107).

72.

Wolfe

S. E.

(2011). The effect of low self-control on perceived police legitimacy. Journal of Criminal Justice, 39, 67-74.

73.

Wolfe

S. E.

Nix

Kaminski

Rojek

(2015). Is the effect of procedural justice on police legitimacy invariant? Testing the generality of procedural justice and competing antecedents of legitimacy. Journal of Quantitative Criminology. Advance online publication. doi:10.1007/s10940-015-9263-8

74.

Wolfe

S. E.

Piquero

A. R.

(2011). Organizational justice and police misconduct. Criminal Justice and Behavior, 38, 332-353.