The Law-In-Between: The Effects of
Organizational Perviousness on the
Policing of Hate Crime
VALERIE JENNESS, University of California, Irvine
RYKEN GRATTET, University of California, Davis
This article examines the characteristics of law enforcement agencies and their environments that affect the
process by which local organizations create and promote operational understandings of law for the purpose of
managing enforcement behavior. Using data on law enforcement agencies in California, logistic and OLS regression models reveal the importance of organizational “perviousness”—that is, susceptibility to environmental
influence and organizational alignment with the proposed innovation—in the process of organizational innovation and policy implementation. We find that perviousness is the strongest predictor of hate crime policy adoption by police organizations. Perviousness is, in turn, influenced by environmental conditions like violent crime
rates and organizational characteristics like resources and size. Given these findings, we argue that organizational perviousness serves as a central intermediary mechanism through which abstract law is translated into
operational policy at the local level of implementation. Scholars have long recognized the importance of examining the “law-on-the-books” and the “law-in-action.” This article points out the importance of the “law-inbetween” as well.
Two features of the U.S. crime control system stand in striking contradiction to one
another. On the one hand, it is relatively easy to create new legislative policies for crime
control that expand the state’s authority, often by enhancing sentences for convicted criminals (Chambliss 1993; Garland 2001). Indeed, policymakers on both the right and the left
recently have promoted crime control legislation that allows them to cultivate a “tough on
crime” image. Conversely, appearing “soft on crime” has become a major liability for leftleaning policymakers, many of whom have adopted sterner stances on crime issues (Currie
1998). This trend has ensured political support for crime control reforms, particularly those
that promote new criminal categories and strengthen punishments for criminal offenses
(Beckett 1994, 1997; Garland 2001; Scheingold 1984; Zimring, Hawkins, and Kamin 2001).
On the other hand, impediments to innovative law enforcement policies—including a resistant organizational culture in law enforcement agencies as well as law enforcement officials’ tendency to be suspicious of new laws and crime control policies—have been welldocumented (Bittner 1980; Brooks 2001; Skolnick 1966; Skolnick and Bayley 1986). Many
officers see the flood of innovative policies as a reflection of political whims, the politicization of law enforcement, and a distraction from basic “good police work.” As a result, law
This research was funded by the California Policy Research Center and was presented at the 2004 annual meeting of
the American Sociological Association in San Francisco, CA. The authors would like to thank Julie Abril, James Basolo,
Susan Bennett, Blaine Bridenball, Patrick Carroll, Ursula Castellano, Jason Hardaker, Calvin Morrill, Kimberly Richman,
Michael Smyth, and Jennifer Sumner for assistance with data collection; Xiaoling Shu, Eric Grodsky, and George Tita for
advice on the data analysis; and Victoria Basolo, Kitty Calavita, Jim Holstein, Paul Jesilow, and Cheryl Maxson for useful
comments on an earlier versions of the article. Direct correspondence to: Valerie Jenness, Department of Criminology, Law
and Society, University of California, Irvine, CA 92697-7080. E-mail: [email protected].
Social Problems, Vol. 52, Issue 3, pp. 337–359, ISSN 0037-7791, electronic ISSN 1533-8533.
© 2005 by Society for the Study of Social Problems, Inc. All rights reserved. Please direct all requests for permission to photocopy or reproduce article content through the University of California Press’s Rights and Permissions website, at http://www.
ucpress.edu/journals/rights.htm.
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enforcement is frequently averse to innovation unless the innovation augments police
authority or power. These differences in the conditions of policymaking and policy enforcing
lead predictably to gaps between law-on-the-books and law-in-action. Put another way, the
“pro-innovation” bias at the policymaking stage often clashes with “anti-innovation” bias of
law enforcers.
Law enforcement agencies are caught in the middle, tensely situated between legislatively mandated crime control policies and the frontline officers who must implement these
policies (Bayley and Shearing 2001; Brooks 2001). Like regulatory agencies, law enforcement
agencies constitute a crucial link in the chain between policy innovation (i.e., the creation of
law) and policy implementation (i.e., the enforcement of law); after all, law enforcement
agencies can facilitate or impede the implementation of innovative crime control policies by
enforcing—or not enforcing—law. It is therefore important to ask: what determines whether
law enforcement agencies actively encourage, if not require, officers to implement innovative
legal reform?
The links between innovation and implementation are currently drawing attention in
relation to hate crime legislation. As we have detailed elsewhere (see Jenness and Grattet
2001), multiple sectors of society beginning in the 1970s called for something to be done
about bias-motivated violence. The cry has emerged most notably from social movement
organizations committed to enhancing the status and welfare of minority communities
(Jacobs and Potter 1998; Jenness and Broad 1997). As a result, partly in the name of “getting
tough on crime,” politicians throughout the 1980s and 1990s at both the federal and state
levels passed legislation that defined the parameters of hate crime law and its enforcement
(Grattet, Jenness, and Curry 1998; Jenness and Grattet 1996), appellate court judges affirmed
the constitutional viability of hate crime law and its enforcement (Phillips and Grattet 2000),
and, most importantly, law enforcement agencies and officials have been charged with the
task of identifying, reporting, and prosecuting hate crime as a special type of violent crime that
warrants enhanced penalties (Bell 2002; Boyd, Berk, and Hamner 1996; Jenness and Grattet
2001; Martin 1995, 1996; McVeigh, Welch, and Bjarnason 2003; Wexler and Marx 1986). In
short, hate crime and efforts to control it are now part of the sociolegal landscape in the United
States and, increasingly, abroad in places as diverse as Britain, Africa, Germany, and Australia
(Gerstenfeld 2003; Perry 2001).
In recent years both national- and state-level law enforcement agencies have increasingly been encouraged to combat bias-motivated violence (Bell 2002; Cogan 2002; Franklin
2002; Kelly 1993; McVeigh et al. 2003). Recognizing that innovation in criminal law does not
automatically compel conformity in officer behavior (Brooks 2001), activist organizations
and governmental agents have requested new policy measures that enhance law enforcement responsiveness to the problem (U.S. Department of Justice 2000:1). Despite these pronouncements, however, enforcing hate crime laws is not always a welcome or easy task. As
others have documented, the mandate to enforce hate crime law introduces definitional
ambiguities related to the parameters of “hate crime” in general and “motive” in particular
(Bell 2002; Boyd et al. 1996; Franklin 2002; Garofalo and Martin 1993; Gerstenfeld 1992,
2003; Martin 1995, 1996; McVeigh et al. 2003); political controversies surrounding hate
crime and its relationship to “political correctness” in both law enforcement agencies and
communities alike (Bell 2002; Boyd et al. 1996; Cogan 2002; Nolan and Akiyama 1999, 2002);
and organizational dilemmas connected to agency structures, resource allocation decisions,
and workplace culture (Balboni and McDevitt 2001; Bell 2002; Finn 1988; Martin 1995,
1996; Nolan and Akiyama 1999, 2002; Walker and Katz 1995; Wexler and Marx 1986). As a
result, the enforcement of hate crime law is often delayed. When such enforcement is forthcoming, it is quite variable (Bell 2002; Franklin 2002; McVeigh et al. 2003).
Several empirical studies published in the 1980s and 1990s highlight how discretionary
law enforcement practices enable individual officers to ignore hate crime law, selectively
enforce hate crime law, and/or define their mission broadly enough to enforce hate crime law
The Law-In-Between
in ways that transcend the parameters of jurisdictionally relevant hate crime statutes (Balboni and McDevitt 2001; Bell 2002; Boyd et al. 1996; Martin 1995, 1996; Nolan and Akiyama
1999, 2002; Wexler and Katz 1995; Wexler and Marx 1986). When combined, this research
identifies institutional, organizational, community, and individual factors that shape variability in the enforcement of hate crime law on the frontlines. Most importantly, this literature,
coupled with research on how hate crime law comes into being and takes shape in the first
place (Jacobs and Potter 1998; Jenness and Grattet 2001), invites an examination of how
local law enforcement agencies—as organizations—promote or hinder the implementation of
hate crime law.
Law enforcement agencies as organizations constitute what we call the “law-in-between”—
organizational structures and policies that provide intermediary linkage between state statutes
and officer discretion. Empirical work suggests that local agency commitment to policing hate
crime is a key factor in determining whether the law is enforced. In their study of bias crime
units, for example, Samuel Walker and Charles M. Katz (1995) argue that the most important factor related to the effective administration of a unit is its commitment to enforcing hate
crime law, which is demonstrated by the existence of training procedures, special policies,
and formal statements made by high-ranking law enforcement officials. Commitment is thus
reflected in changes in organizational structures and the creation of formal policies (Boyd et
al. 1996; Martin 1996). In his work on the administration of hate crime law, James Kelly
(1993) emphasizes the importance of understanding the origins and development of “proactive police policies in communities” as a key component of law enforcement’s “multifaceted
response” to bias-motivated crime (p. 8). Consistently, Chuck Wexler and Gary T. Marx
(1986:2) found that the Boston Police Commissioner’s issuing written guidelines corresponded directly with the “dramatically” altered handling of bias crimes. James J. Nolan and
Yoshio Akiyama (1999) suggest that formal policies operate as “encouragers” that enhance
the likelihood that bias crime will be reported. This research underscores the importance of
agency-level policies in translating between law-on-the-books and law-in-action.
This article examines the role of local law enforcement agencies in the implementation
of hate crime law by asking: “why do some local law enforcement agencies embrace and promote an innovation like hate crime law by adopting formal hate crime policies?” More specifically, we ask: “what types of law enforcement agencies and community environments yield
formal policies designed to articulate an agency’s definition of hate crime, as well as the specific protocols the agency advocates for handling hate crime cases?” By answering these
empirical questions, we provide an assessment of the community-agency context out of
which innovative policy is realized. In doing so, we contribute to the empirical description
of how hate crimes are “made” by both community and organizational factors, not merely
discovered and documented by individual law enforcement officers (see Bell 2002). Thinking
more broadly, we treat the enforcement of hate crime at the organizational (i.e., agency)
level as an opportunity to study how policy implementation unfolds in the American criminal justice system. The development of hate crime policy at the local level provides an opportunity to examine the processes of identifying, naming, and reacting to conduct as hate crime
at the moment following the adoption of legislative mandates (see Jenness and Grattet 2001)
and at the moment prior to taking hate crime reports (see McVeigh et al. 2003).
This study employs multiple sources of data, draws on policy literature, and uses a conceptual framework grounded in organizational theory to offer a model of how community
and organizational factors, especially a condition of perviousness between the community and
law enforcement agencies, influence the creation of innovative policy at the level of the organization. In the sections that follow, we first situate the study in the theoretical literature on
policy implementation in general and in the disjuncture between the law-on-the-books and
the law-in-action in particular. We consider relevant research on the implementation of regulatory policy and emphasize the importance of studying what we call the “law-in-between”
the law-on-the-books and the law-in-action in the realm of criminal law. Next, we provide
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an overview of hate crime policy in California and the sources of data used in this study. Subsequently, we analyze the community and organizational factors that shape organizational
commitment to policing hate crimes, as evidenced by the adoption of a hate crime policy that
alerts officers to the existence of hate crime and instructs officers how to define and identify
hate crime. Finally, we discuss the relevance of our empirical findings regarding community
and organizational factors—as well as the nexus between the two—that shape the implementation and enforcement of hate crime law as both a particular type of innovative policy and,
more importantly, the behavior of the “law-in-between.”
Conceptual Considerations
Since legal realist scholars first identified the so-called gap between law-on-the-books
and law-in-action, a substantial body of research has illustrated the disjuncture between formal rules and enforcement practices. Research suggests that both criminal law and broader
arenas of governmental regulation routinely and predictably experience such gaps. Agencies
and/or other bureaucratic units exist within the gap and operate as “little legislatures”
(Breyer 1982:346) because they frequently make law as well as enforce it (Kagan 1978). One
of the principal means by which agencies make law is through the creation of localized
enforcement policies. Such policies promote “operational” understandings of law.1
Operationalization of law takes place between the law-on-the-books and the law-inaction. As Figure 1 illustrates, the law-in-between refers to an intermediary moment in a
larger process that begins with an innovation (i.e., the adoption of statutes) and ends with
the actual behavior of what Michael Lipsky (1980:3) calls “street level bureaucrats”2 (i.e., the
behavior of law enforcement agents). This crucial phase, which is the focus of this study,
includes the organizational work of making innovations operational. It has received very little
attention in the sociological and criminological literatures (for a rare exception, see Hawkins
and Thomas 1984; and, more recently, see Kramer and Ulmer 2002; Ulmer and Johnson
2004). This lack of attention is surprising because it clearly constitutes a moment in a larger
process in which the putative social conditions referenced by the law are recognized, defined
(and in many cases redefined), and institutionalized as legal problems to be managed by state
agents (see, for example, Grattet and Jenness forthcoming). We argue that understanding
operationalization as an intermediary phase in the larger innovation-implementation process
is, in and of itself, crucial to a broader understanding of how social problems are constructed
in different organizational contexts.3 Accordingly, we isolate the operationalization phase as a
1. Operationalization, as it pertains to both regulatory law and criminal law, refers to an agency-level process
whereby innovations are selected from above (e.g., state and federal legislatures, courts, or other promoters of enforcement standards) and transmitted from the local agency leadership to frontline officials who are the intended adopters of
the innovation. One of the central ways agencies of all sorts, including criminal law enforcement agencies, operationalize innovations is through the creation and dissemination of formal rules. The innovation—which may be anything
from a broad mandate to enforce a new type of criminal law to specific procedures for enforcing existing laws—is
assigned a local operational definition and a description of how it is ideally supposed to apply to the local environment.
In other words, operationalization provides an opportunity for the (re)articulation of a principle, thus the (re)construction of the issue it is designed to address.
2. In his now classic work Street-Level Bureaucracy (1980), Lipsky defines street level bureaucrats as “public service
workers who directly interact with citizens and who have substantial discretion in the execution of their work” (p. 3).
3. This is not to say, of course, that innovations embraced or rejected by an agency are accepted or rejected by
street-level officials working within the agency. Obviously, not all policies are obeyed; ample research suggests innovations are frequently adopted “ceremonially” by leaders who have no intention of subverting established ways of doing
business (Bittner 1980; Brooks 2001; Skolnick 1966). In such cases, ceremonial adoption of an innovation is often
designed to demonstrate that the organization is exercising deep concern about an issue, operating “on the cutting edge”
of its profession, and meeting the expectations of constituencies outside the organization. Thus, in some cases an innovation is adopted not to incite behavioral changes. As discussed in the next section, it can be adopted to marshal legitimacy from particular audiences within an organization’s larger institutional environment (Crank and Langworthy 1992;
Katz 2001). This frequently observed phenomenon of separating policy adoption from changes in actual practices is
referred to as “decoupling” (Edelman 1992; Meyer and Rowan 1977).
The Law-In-Between
Figure 1 • A Model of the Lawmaking Process with the Policy Operationalization in
Law Enforcement Phase Highlighted
key phenomenon to explain, in and of itself, and leave the connections between operationalization and “street-level” enforcement for a subsequent investigation (see Jenness and Grattet
2005).
To focus analytic attention on the law-in-between as sin qua non of a larger policy implementation process, this article moves beyond single case studies and limited qualitative data
that currently dominate the literature on the enforcement of regulatory law and moves
toward a focus on interagency variation in the operationalization of law (see Hutter 1989).
We do so by situating police and sheriffs departments’ organizational policies as a central
intermediary mechanism through which abstract legal codes are translated into instructions
for concrete law enforcement practices. To understand the conditions under which policy
adoption does and does not occur, we examine both community factors and organizational
factors that may shape the formulation, adoption, and institutionalization of organizational
policies. More to the point, we argue that a particular type of nexus between community and
agency factors—what we are referring to as organizational “perviousness”—affects the likelihood that an innovation from above (e.g., state law) will be embraced and operationalized by
agencies (e.g., police and sheriff agencies).
Contextual Factors and Organizational Policies
The decentralized system of American policing ensures law enforcement agencies are
rooted in, and accountable to, local communities (i.e., jurisdictions). Although law enforce-
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ment agencies share common federal and state laws, each agency is autonomous in terms of
how it orients to state statutes, develops policy to enforce the law, and, indeed, actually
enforces the law. Such autonomy grants the agency significant freedom to develop its own
approach to crime control based upon its assessment of the nature of its specific community
problems. Given this decentralized structure, it is useful to examine the degree to which the
structural composition of the jurisdiction and to which social pressure emanating from within
a jurisdiction affect whether an agency devises and promotes a policy designed to operationalize the enforcement of hate crime law.
Borrowing from Elizabeth Boyle (2002; Boyle and Meyer 1998), “functionality” refers to
the local relevance of any policy, especially of state and federal policy. Assuming policies are a
response to the (real or presumed) existence of certain kinds of public problems and human
practices, the relevance of any policy would be contingent upon whether, to what degree,
and how the problem it is designed to address manifests in the community. Although Boyle
argues that functionality is negatively correlated with implementation, in this case communities differ in their “need” for crime control policies insofar as they experience varying crime
rates. Therefore, we anticipate policies are more likely to appear in communities with high
violent crime rates.4
Empirical work on crime and communities also reveals that both the demographic and
economic structure of communities affects the crime problems that emerge therein. In particular, poor communities with heterogeneous populations tend to produce higher rates of violent crime than their counterparts (Bursik and Grasmick 1993; Fingerhut and Kleinman
1990; Massey and Denton 1993; Sampson and Groves 1989). However, considerably less
attention is given to how heterogeneity and socioeconomic conditions might shape the
observed relationship between crime and policy. That is, beyond being a correlate of crime,
heterogeneity and socioeconomic conditions could be seen as characteristics of communities
that are consequential for how crime is experienced and responded to by community members (Nardulli and Stonecash 1981; Riksheim and Chermak 1993; Walker 1991).
If community composition factors highlight the raw potential or need to engage in relevant policy operationalization within a community, then “community demand” factors must
also be considered. Community demand factors are characteristics of the community that can
lead to explicit calls for law enforcement to take action on specific issues of concern, such as
hate crime (for work along these lines, see Bell’s 2002 community study and McVeigh and
associates’ 2003 nationwide study). Organized community groups that express concern about
a social problem and ensure policies designed to ameliorate it may be influential in determining the existence of a policy. Some have referred to this argument as the “democracy-at-work
thesis” because it implies that law enforcement agencies reflect the will of the organized citizenry (Beckett 1997; Garland 1990; Michelowski 1993).
With regard to hate crime control policies, evidence suggests that some types of organizations support hate crime policies more than others do. As our previous work (Jenness and
Grattet 2001; see also Jenness and Broad 1997)—as well as that of James Jacobs and Kimberly Potter (1998), Terry A. Maroney (1998), and most recently Rory McVeigh and associates (2003)—has shown, human relations and human rights groups have played a key role in
the promotion of hate crime law and the enforcement of hate crime policy.5 As the most
4. Substantial research in criminology has failed to consistently find a significant positive relationship between the
occurrence of crime and the development of specific crime control policies and strategies (Beckett 1994, 1997; Fishman
1978; Jenness 2004; Jenness and Grattet 1996; Rafter 1990; Salvesberg 1994; Scheingold 1984). Nonetheless, examining the relationship between the development of hate crime policy and the crime rate can reveal the mediation of other
factors, especially agency perviousness, as described later in this article.
5. In the most comprehensive study of variation in compliance with hate crime policies, McVeigh and associates
(2003) conclude, “the presence of resourceful civil rights organizations in a county can lead to higher numbers of
reported hate crimes, but the influence of a civil rights organization is contingent upon the political context and upon
objective conditions that lend credibility to civil rights framing” (p. 843).
The Law-In-Between
visible watchdogs in the community devoted to combating hate crime, human relations commissions are the best measure of directly expressed community demands. They often express
demands by producing and disseminating annual hate crime reports; developing and circulating legislative updates; maintaining a library on hate crimes, human relations, intergroup
conflict, and police-community relations; providing resources to help communities respond
to hate crime, such as training programs, prevention networks, and conflict resolution and
mediation programs; and, most importantly for our purposes, serving as a liaison between the
community and law enforcement agencies to facilitate law enforcement’s proactive response
to hate crime. In short, hate crime policies are more likely to emerge in communities with
human relations/human rights organizations.
Moving away from well-known community/jurisdictional considerations, neoinstitutionalist scholars in the sociology of organizations suggest that the adoption of formal structures within an organization—what we call operationalization—is driven less by local or
immediate needs for a policy and more by the desire to conform to the dictates or norms of
the interorganizational system or “field” within which the organization—in this case, any
given law enforcement agency—is situated. John P. Crank and Robert Langworthy (1992)—
drawing heavily on the classic work of John W. Meyer and Brian Rowan (1977), Paul DiMaggio (1988), and Walter Powell and Paul J. DiMaggio (1991)—articulate the ways in which an
institutional perspective applies to policing:
The institutional perspective presented here focuses on powerful myths produced by broad processes in police departments’ institutional environments and looks at the influence of these myths
on the formal structure and activities of particular organizational elements of the department. By
successfully incorporating institutional myths into its formal structures and activities, other relevant
actors in its institutional environment perceive that a police department is legitimate. (p. 338)
From this point of view, police departments “accede to the demands of other actors on whom
departments depend for legitimacy, and with the receipt of legitimacy, the continued flow of
resources for organizational survival” (Crank and Langworthy 1992:339). More recently,
Charles M. Katz (2001) has corroborated, and elaborated upon, this view in an effort to
understand why police departments adopt various approaches to law enforcement over time.
He explains:
Institutional theorists argue that organizational structures and operational activities reflect the values
and beliefs that are shared by powerful actors, called sovereigns, who have the capacity to influence
the policies, decisions, and financial resources of the organization. Sovereigns for police agencies
include such actors as the mayor, city council members, police unions, special interest groups, citizens, and other criminal justice agencies. (p. 39)
Sovereigns are defined as external influences on the organization that formally or informally
hold the organization to institutionalized standards of policy and performance. Moreover, organizations successfully secure legitimacy to the degree they can engage in those “activities that
are widely thought to be right, good, and effective” (Katz 2001:40) by various sovereigns.
One way in which this process plays itself out is through the adoption of policies that
(arguably) serve to legitimate the organization. Research has shown this to be the case across
a variety of diverse empirical domains, including: compliance with the 1964 Civil Rights Act
across private firms as well as across colleges and universities (Edelman 1992); the development of state-level hate crime law in the United States (Grattet et al. 1998); the implementation of sentencing reform under new sentencing guidelines (Dixon 1995); and, most recently,
the global circulation, operationalization, and implementation of policies on “female genital
cutting” (Boyle 2002). Consistent with the theoretical underpinning of these studies, Crank
and Langworthy (1992), and more recently Katz (2001), argue that police organizations are
able to survive in a non-competitive environment, regardless of the organization’s ability to
produce a clearly defined or economically marketable product, precisely because they incorpo-
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rate institutional myths6 into their structures, policies, and practices. As Crank and Langworthy
(1992) conclude, “police organizations are so highly institutionalized that issues of efficiency
and effectiveness in the production of technical outputs are virtually irrelevant to their organizational well-being” (p. 262). Consistent with this view, Katz (2001) recently demonstrated
how a police department in the Midwest responded to a “gang problem” by establishing a
gang unit as “a result of pressure placed on the police department by various sovereigns in its
institutional environment, instead of for reasons of technical rationality” (p. 57). In this perspective on organizational behavior, sovereigns can take the form of any outside actor in a
position to pass consequential judgment on the organization (i.e., citizens, review boards, city
councils, human relations commissions, professional groups, and watchdog organizations of
various ilks).
Not all agencies are positioned equally in relation to the institutional environment of law
enforcement; thus, the innovative capacity of any particular agency varies. By innovative
capacity, we refer to the organization’s amenability to adopting a new policy or set of policies.
The innovative capacity of an agency often depends upon two factors: the perviousness of
the boundary between the organization and its environment, and the resources available to
the organization to adopt an innovation once it is committed to doing so.
“Perviousness” refers to an organizational-environmental condition characterized by both
susceptibility to environmental influence and the alignment of the policy innovation with
existing organizational culture and practices. According to Gerald F. Davis and Henrich R.
Greve (1997), susceptibility refers to an individual organization’s exposure to the possibility
of adopting a policy: “The individual actors [organization] may be more or less susceptible to
outside influence, just as individuals may vary in their immunity to a virus” (p. 18). Adding
to this important observation, we treat “alignment of the policy” as an organization’s propensity to adopt the innovation by virtue of its own characteristics, especially its practices and
philosophy and the degree to which the policy innovation resonates with these practices
and philosophy (see Maxson and Klein 1997). Formulated in this way, perviousness refers to
how much an organization is exposed to sources of change and whether or not the change
fits with the structure and workings of the organization.
In the case of law enforcement agencies, the term perviousness is designed to capture
particular features of the organization-community boundary heretofore ignored by both
crime control and organizational experts: (1) exposure to community factors and demands
that amplify or reduce the probability of policy adoption, and (2) the degree to which the
agency is predisposed to incorporate innovations to which it has been exposed, in this case
the degree to which the policy aligns with the agency’s past practices and policies. Consistent
with its literal meaning,7 we use the term “perviousness” to simultaneously capture the degree to which organizations are exposed to external conditions and demands, and the degree
to which they are amenable to addressing external demands for policy.
The common cold can serve as a useful metaphor for explaining and concretizing the
concept of perviousness. For an individual to catch a cold, he or she must first be exposed to
a virus. However, individuals are not equally susceptible as hosts for the virus, due to lifestyle
practices and circumstances, such as having children in daycare or working in a hospital.
Moreover, equally susceptible individuals are not equally likely to get a cold, due to differences in the strength of their individual immune system. Thus, one individual may be more
receptive to a cold even if they have the same exposure and susceptibility as another individual.
6. According to Meyer and Rowan (1977:347), “myths” are constructed with widespread notions of social reality
in mind, including ideas about what the organization “should” do rather than practical considerations of what it actually
does. Crank (1994), for example, describes specific myths related to the institutional environment in which policing
occurs, most notably “the mythos of community policing” and “the watchman and the law enforcer.”
7. According to the Oxford English Dictionary, pervious denotes “affording passage or entrance” and “accessible to
influence or argument.”
The Law-In-Between
These considerations are consequential for how much the cold is able to align with and ultimately find a home in the individual as a potential host. In short, individuals are more or less
pervious with respect to catching a cold. The same holds for law enforcement agencies when
it comes to adopting policy innovations. With both—the law enforcement agency and the
potential viral host—change is dependent upon the types of exchanges that occur between
the entity and its environment as well as constitutional factors.
The final aspect of innovative capacity is whether an organization is able to enact new
policies once it is exposed to the innovation and committed to implementing it. An organization may be highly pervious, but nonetheless have few resources to enact a policy. Indeed, a
large body of research demonstrates that organizational size and wealth affect organizational
innovation, including policy adoption (Champion 2003; Dixon 1995; Edelman 1992; Rogers
1995). Size and organizational wealth are standard measures of organizational capacity in
policing (Champion 2003), so we would expect them to affect agency policy action on hate
crime.
The Study
Research Site
To investigate the contours of policy operationalization, we focus on the implementation
of organizational hate crime policy in the state of California. We chose California because its
state legislature has been at the forefront of hate crime policymaking for the last two decades,
and as a result it arguably has the most comprehensive system of hate crime laws in the
nation (Grattet and Jenness forthcoming). As a result, California law enforcement agencies
have had almost two decades to respond to law-on-the-books. Moreover, they have done so
in ways that capture the variation in agencies throughout the United States. That is, some
agencies have adopted hate crime policies, some have actively conducted training, a few have
created specialized hate crime units, and some have done none of these things. California
claims a leading role in hate crime policing, and the empirical generalizations drawn from it
should be applied cautiously. However, the range of responses nonetheless makes it a suitable
case from which to identify general theoretical processes and the likely paths other states
might follow. In other words, the variation in local law enforcement response in California
encompasses the variation found in other states. California is also a large state with hundreds
of law enforcement agencies, which facilitates the type of data collection and multivariate
analyses described in the next section. At the same time, California is unique in many
respects, thus the generalizability of the empirical findings presented in this article might be
limited even as the conceptual and theoretical contributions are applicable to other cases of
policy operationalization and implementation.
Data
Dependent Variable: Hate Crime Policies. We solicited documents called “general orders”
from all municipal police and county sheriff’s departments in the state of California. These
policies codify an agency’s official policy on a particular law enforcement matter. For example,
law enforcement agencies have policies regarding such things as the “use of force,” “highspeed pursuit,” and “how to catalogue evidence in drug crimes.” In the case of hate crime,
policies provide the departmental definition of hate crime as well as its protocol for dealing
with hate crime incidents. In addition, policies often signal to officers what counts as a hate
crime and who counts as a hate crime victim, as well as why the department is committed to
enforcing hate crime law and what the department’s responsibilities to the community entail
(Grattet and Jenness forthcoming).
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The purpose of departmental policy is to reduce officer discretion and to help officers
prepare for situations they may confront (Brooks 2001). Policies are important elements in
the structure and process of policing for several reasons. First, they serve as a critical link
in the policy chain, one that connects officers with legislative mandates (see Figure 1). They
provide a crucial communication link in the chain of command, from police chief to beat cop.
Indeed, policies are made available to all frontline officers, who can be subjected to disciplinary procedures if they are unaware of the policies or if they fail to comply with the dictates
detailed in the policies. Second, several analysts have argued that policies shape the practice
of hate crime policing (Balboni and McDevitt 2001; Brooks 2001; Martin 1995; Nolan and
Akiyama 2002; Sumner 2002). Third, and most importantly for the purposes of this study,
policies provide a window through which the stated goals and practices of law enforcement
agencies and personnel can be documented.
With this in mind, in 1999 and then again in 2000 and 2001 we requested policies on
hate crime from all 339 municipal police and all 58 sheriff’s agencies in the State of California. Because “each municipal police department and county sheriff’s department in California
has been responsible for developing its own response to hate crime” (Office of the Governor
2000:21), these data provide individual pictures of how each police and sheriff’s department
in the state is responding to the issue of hate crime. Collectively, the data also provide an
aggregate picture of how the state of California is responding to statutory mandates to police
bias-motivated conduct.
Of the 397 police and sheriff’s agencies in the state, 37 did not respond to the three successive requests for hate crime policies. Nonetheless, we achieved a 91 percent response rate.
Comparisons of the mean values for each organizational and community variable in our models
revealed only one significant difference between the responders and the non-responders.
Namely, on average the non-responding agencies were located in communities with lower
socioeconomic conditions. Because this characteristic is associated with not having a hate
policy in place, the sample selectivity introduced by excluding the non-responding cases
implies that most of them would likely not have possessed a policy. Beyond this variable, no
other significant differences existed between responders and non-responders.
Independent Variables: Organizational and Community Factors. To account for the presence
of policies, we gathered organizational and community data corresponding to the factors
described above (see Table 1). The community-level data were drawn from the 1990 U.S.
Census and the 1990 Uniform Crime Reports. We chose the year 1990 because most of the
agencies adopted policies prior to 2000; therefore, 2000 data would not represent conditions
under which policies may or may not have been adopted. We extracted census data at the
city level to correspond to the jurisdiction of the municipal police departments. We compiled
county-level data by subtracting jurisdictions with municipal police departments from county
census figures in order to arrive at a more accurate picture of the sheriff’s jurisdiction than
simple county totals.
We measured specific community variables as follows: the violent crime rate is the
number of violent crimes per 100,000 persons (i.e., murder, aggravated assault, robbery,
forcible rape); ethnic heterogeneity was calculated using the Blau method (1977), which
measures the expected chance that any two individuals drawn from the population are from
two different groups, taking into consideration the number of the groups in the population
and their relative size; and socioeconomic conditions is a factor score based on the unemployment rate, the percent of managerial and professional workers, the median income, and
the percent of college degree holders. In addition, we relied upon information from the
California Association of Human Relations Organizations (CAHRO) for data on the distribution
of human rights and human relations organizations throughout California municipalities.
The organizational data on California law enforcement agencies come from the Law
Enforcement Management Administrative Statistics (LEMAS) survey conducted in 1997 by
The Law-In-Between
the U.S. Bureau of Justice Statistics. The LEMAS survey respondents are composed of all
medium and large agencies in the state and a representative sample of agencies with fewer
than 100 officers. The sample size for the survey in California was 158 municipal police and
sheriff’s agencies. Thus, the multivariate analyses reported in the next section were performed on 158 cases for which we have data on the organizational variables. A comparison of
the full sample with the LEMAS sample reveals frequency distributions for the dependent
variable that are comparable (i.e., 44.7 percent of agencies in California have a policy
whereas 42.2 percent of agencies in the LEMAS sample have a policy). The distribution of the
community composition and crime variables are also similar. However, human relations commissions are more prevalent in the jurisdictions of agencies in the LEMAS sample (i.e., 60
percent of agency jurisdictions in the LEMAS sample have a human relations commission
whereas 47 percent of agencies across the state have commissions). Finally, as a result of the
reduction of sample size from 397 to 158, the findings are weighted in a direction that
increases the influence of the medium and larger departments.8 This is appropriate insofar as
the results reflect the agencies that do most of the policing in the state.
The LEMAS survey provides information relevant to the measurement of organizational
perviousness. As described earlier, capturing perviousness requires measuring both the susceptibility of an agency to community pressures and the alignment of community influences
with the agency philosophy and practices. To measure susceptibility, we used a survey question that tracks the number of community groups with which an agency met during the previous 12 months. These groups include neighborhood associations, tenants’ associations,
youth service organizations, advocacy groups, business groups, religious groups, school
groups, and others. This measure—which varies from 0 to 8—represents the range of audiences with which the agency regularly communicates. Accordingly, it captures what Skolnick
and Bayley (1986) refer to as “police–community reciprocity”9 (p. 212).
To gauge the alignment of hate crime policy with agency practices and philosophy we measured commitment to community policing and workplace heterogeneity, respectively. Community policing is an organizational practice entirely commensurate with the spirit of hate
crime policies (Greene 2000). Six survey items were combined to assess the degree to which an
agency engages in community policing practices, including: (1) training citizens in community policing (e.g., community mobilization, problem solving); (2) giving patrol officers responsibility for specific geographic areas/beats; (3) assigning detectives to cases based on geographic
areas/beats; (4) actively encouraging patrol officers to engage in SARA-type problem-solving
projects10 on their beats; (5) including collaborative problem-solving projects in the evaluation
criteria of patrol officers; and (6) forming problem-solving partnerships with community groups,
municipal agencies, or others through special contracts or written agreements. We assessed workplace heterogeneity by measuring the racial/ethnic/gender diversity of agency employees. Jacobs
and Potter (1998), Jenness and Broad (1997), and Maroney (1998) document minorities’ considerably greater commitment to hate crime law than their counterparts in the broader population. Thus, workplace heterogeneity is a rough measure of the degree of internal support for
policies designed to protect the interests of minority constituencies, such as hate crime policies.
8. Of the 158 cases in the LEMAS data, only four cases were nonresponders (i.e., they refused to respond to our
request for their policy).
9. According to Skolnick and Bayley (1986), “police-community reciprocity means that police must genuinely
feel, and genuinely communicate a feeling, that the public they are serving has something to contribute to the enterprise of policing” (p. 212).
10. SARA is an acronym for Scanning, Analysis, Response, and Assessment. These four respective processes
entail: (1) spotting problems using knowledge, basic data, and electronic maps (i.e., Scanning); (2) using hunches and
information technology to identify and understand the characteristics and underlying causes of crime and disorder (i.e.,
Analysis); (3) devising a solution that entails working with the community wherever and whenever possible (i.e.,
Response); and (4) looking back to see if the solution worked and what lessons can be learned (i.e., Assessment). SARA
has been used for some time in problem-oriented policing as a methodical process for problem solving. For a lengthier
overview of the history, goals, and workings of community policing see Greene’s (2000) review of the topic.
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Table 1 • Summary of Independent Variables
Variable
Functionality
Violent crime rate
Community composition
Ethnic heterogeneity
Socioeconomic
conditions
Community demands
Human relations
commission
Organizational
perviousness
Community group
meetings
Description
Measurement
Violent crime rate in the city/county
in which the law enforcement
agency resides
Ln # of violent crimes per
100,000a; i.e, murder,
aggravated assault,
robbery, forcible rape
Racial/ethnic diversity of the
population over which the law
enforcement agency has
jurisdiction
“Blau Method”b: an index that
measures the expected chance
that any two individuals
drawn from the population
would be of different groups
taking into consideration the
number of groups and their
relative size
An index computed from
the median income,
unemployment rate, percent
of college degree holders,
and percent of managerial
and professional workersc
The social and economic status
of a community
The presence of human relations or
human rights commission in the
community
Presence/absence of human
relations groupsd
“Which of the following groups did
your agency regularly meet with
to address crime problems?”
neighborhood associations; tenants’
associations; youth service
organizations; advocacy groups;
business groups; religious groups;
school groups; other groups.
Total number of groups with
whom agency regularly
meetse
(Continued)
These variables—meetings with community groups, community policing practices, and
workplace hetereogeneity—were combined in a factor score to measure the perviousness of
each agency. Two of these variables—community policing practices and meetings with
community—load highly on the same factor (.850 and .835, respectively). The third variable,
workplace heterogeneity, does not load as highly (.440), but we deemed it necessary to
include it in the factor score in order to be consistent with our theoretical arguments. Two
factor scores—one including all three variables and one omitting the workplace heterogeneity measure—are correlated at .963, suggesting that empirically it matters little whether heterogeneity is included in the score. We emphasize that treating these variables as components
of an interaction term—which assumes a multiplicative effect—is at odds with how we conceptualize perviousness. Specifically, our measure is a composite that assumes a conjunctive
effect between the constituent features of organizational perviousness.
The Law-In-Between
Table 1 (Continued)
Variable
Description
Organizational perviousness (continued)
Community policing
“Which of the following apply to
practices
your agency?”
train citizens in community policing;
give patrol officers and detectives
responsibility for specific areas/beats;
actively encourage officers to engage in
SARA-type problem-solving projects;
including collaborative problem
projects in the evaluation of patrol
officers; form problem-solving
partnerships with community groups,
municipal agencies, etc.
Workplace
Racial/ethnic/gender diversity of
heterogeneity
agency employees
Perviousness index
Organizational capacities
Size
Resources
Organizational susceptibility to
outside influence and alignment
of policy with organizational
practices and philosophy
Measurement
Total number of community
policing practices employed
by the agencye
“Blau Method”b: an index that
measures the expected chance
that any two employees
drawn from the agency would
be of different groups, taking
into consideration the number
of groups and their relative
sizee
An index computed from
“community group meetings,”
“community policing
practices,” and “workplace
heterogeneity”e
Size of the law enforcement agency
Ln Total number of full-time
agency employeese
Organizational expenditures
Ln Per capita expenditures
on wages, salaries,
operationse
a
Uniform Crime Reports, 1990.
Blau, 1977.
U.S. Census, 1990.
d
List of Human Relations/Rights groups in California provided by the California Association of Human Relations
Organizations, 2002.
e
Law Enforcement Management and Administrative Statistics, 1997.
b
c
Finally, we also used LEMAS data to measure the size and resources of agencies. Size was
computed as the number of full-time sworn and non-sworn officers. Resources are the total per
capita amount spent on salaries, wages, and operations.
Method of Analysis
Because we are interested in factors shaping the probability that law enforcement agencies will adopt a hate crime policy, we use logistic regression as our basic modeling strategy
(Aldrich and Nelson 1984; Demaris 1992; Liao 1994; Long 1997). We followed procedures
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outlined by J. Scott Long (1997:62–71) for the computation of predicted probabilities to aid
the substantive interpretation of the results. We report coefficients that express the effects of
the independent variables on the log of the odds ratio as well as the effects on the predicted
probability of having a hate crime policy.
Findings
The analysis that follows is divided into two sections. The first section describes the distribution of hate crime policies in all 397 law enforcement agencies in California and the reasons law enforcement officials give for not having an order. In the second section, we
examine the community and organizational factors that shape the probability of a law
enforcement agency having a hate crime policy.
Hate Crime Policy in California Law Enforcement Agencies
Of the responding police and sheriff’s agencies, 161 (44.7 percent) informed us that they
do not have a hate crime policy. Representatives from these agencies gave a variety of reasons
for not having a policy, including the lack of need for a hate crime policy, an administrative
delay in developing a policy, and an ability to enforce hate crime law with existing policies.
Regarding a lack of need, for example, a sergeant who identified his jurisdiction as “a small,
upper-income community which is purely residential” argued, “We have no businesses, no
houses of worship, no gangs, and the lowest crime rate in the State of California for ten years
straight (for cities of more than 10,000 population). We have been blessed so far with an
absence of hate crimes, and we therefore have no DSOPs [policies] dealing with hate crimes”
(personal correspondence, June 21, 1999). Similarly, a commander from a medium-sized
department explained that his department does not have a hate crime policy because “the
incident [sic] of reported hate crime in this jurisdiction is almost nonexistence [sic]. Over the
last several years an average of two or three incidents per year have been reported and all of
these have been misdemeanor offenses at most” (personal correspondence, June 2, 1999).
Explanations such as these do not recognize the intimate connection between policing,
reporting, and the “discovery” of hate crime in a community (Balboni and McDevitt 2001;
Bell 2002; Kelly 1993; Nolan and Akiyama 1999, 2002). That is, policies may actually help
officers recognize some incidents as hate crime that they otherwise would not. If this is so,
the existence of hate crime in a community could be a product of having an order—the opposite of what these officials contend.
In contrast, other law enforcement agencies that recognize the need for a hate crime policy explained their failure to have one by referencing administrative error. The captain of a
small coastal community’s department, for example, responded to our request for a copy of
his department’s hate crime policy by writing: “I regret to inform you that neither our training manual or [sic] our Procedures manual include a section regarding hate crimes. We appreciate the fact that your inquiry brought this situation to our attention. We will address this
oversight in the near future” (personal correspondence, June 1, 1999). Other law enforcement officials also affirmed the importance of having a hate crime policy and thus took the
time to inform us that they are developing a policy. For example, the Community Services
Officer for an agency in a small northern California city reported to us: “Tracking down the
information on our hate crime policy is proving more difficult than I anticipated. Our old
policy manual of November 1988 does not specifically address hate crimes. I know from
conversations with Chief Brown11 that it is to be included in our new policy manual. How11. As part of our request for information on police and sheriff’s hate crime policies we promised to conceal the
identity of the participating agencies. Although it is not necessary in research on public agencies such as this, we did so
to maximize cooperation with our efforts.
The Law-In-Between
ever, he is away and no one has access to the draft version” (personal correspondence, July
13, 2002).
Finally, some departments told us that policing hate crime is important and thus requires
adherence to policy, but that the development of special policies for the enforcement of hate
crime law is unimportant insofar as general policing procedure is all that is required. As the
chief of police in a California tourist destination explained: “currently our agency does not
have a separate or specific policy for investigation of hate crime. The few hate crimes we have
had reported are investigated as any other complaint received by our agency” (personal correspondence, June 3, 1999). In a considerably lengthier letter, a lieutenant from a department in the Central Valley elaborated along these lines:
The Police Department has not found the need to specifically identify hate crime in any policies,
procedures, or training guides. If you set your standards high enough, adhere to professional investigative standards, and most importantly know your community, your patrol and investigative staff
can effectively and efficiently respond to almost any challenge. However, should the need arise for
specialized assistance, we have the availability of excellent regional resources at the County, State,
and Federal levels. In short, we have chosen not to focus on, or be driven by, the specter of “Hate
Crimes.” . . . We have found success in staying with the basics of good police work. (personal correspondence, May 25, 1999)
From this point of view, hate crime policing is not distinct from policing other crimes; thus,
the development of special policies is unnecessary.
Of the responding police and sheriff’s agencies, 199 (55.2 percent) provided us with a
copy of their general order. This proportion of agencies with policies is considerably higher
than the 37.5 percent of law enforcement agencies that reported having a hate crime policy
in Jennifer Balboni and Jack McDevitt’s (2001:14) work.12 In other words, California police
and sheriff’s departments are above the national average reported in the only published study
documenting the prevalence of hate crime policies among U.S. law enforcement agencies.
Moreover, the policies in our data set come from agencies with jurisdiction over the majority
of the state’s population (68 percent). In other words, two-thirds of Californians live in law
enforcement jurisdictions where a policy exists.
In terms of content, local law enforcement hate crime policies vary, but they contain
similar components and frequently follow the same structure as policies related to other
policing concerns (Grattet and Jenness forthcoming). The majority of the policies begin with
a “purpose” section that describes the aim of the policy. Nearly a third of the policies justify
law enforcement’s responsibility to enforce hate crime law by simply referencing the state
law and/or the U.S. Constitution. In the vast majority of the policies, the justification for
enforcing hate crime law is followed by the definition of hate crime to which officers are supposed to adhere when enforcing the law. All but one of the policies describe the official procedures officers must follow when responding to incidents. Finally, hate crime policies vary in
terms of the degree to which they articulate a mandate to provide victim services and engage
with the community.
Factors Shaping the Adoption of Hate Crime Policy in
California Law Enforcement Agencies
We now turn to our central empirical question: why do some law enforcement agencies
adopt hate crime policies while others do not? Although dichotomizing the dependent variable
in this way prevents us from analyzing the formulation of nuanced substantive differences in
12. This rate is also higher than other parts of law enforcement. For example, McPhail (2003:69) found that only
36 percent of prosecutors’ offices across the United States reported having a hate crime policy in place in 1995.
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policy design, it enables us to focus sharply on factors that influence whether the law-inbetween is being constituted at the organizational level (see Figure 1).
Because of potential interdependencies between community and organizational factors,
we first examine the interrelations between independent variables and then build the full
model in a series of steps that correspond to the conceptual issues presented earlier. The
Appendix presents the zero-order correlation matrix, means, and standard deviations for the
independent variables. There are modest, significant correlations between several variables,
including crime rate and heterogeneity (r 5 .48), and organizational perviousness and agency
size (r 5 .53). In addition, a few other variables correlated above r 5 .3. However, subsequent
regression diagnostics reveal that multicollinearity is not a problem. No variance inflation factor
is above 1.7 (Neter, Wasserman, and Kunter 1990).
The models presented in Table 2 assess the influence of the independent variables under
selected conditions. Model 1 shows that violent crime rate has a statistically significant positive effect on policy adoption, absent controls for other factors (exp(B) 5 1.77). Reported in
Model 2, this effect remains significant and increases when heterogeneity and socioeconomic
conditions are controlled. At the same time, socioeconomic conditions positively and significantly influence adoption (exp(B) 5 1.71). However, the effects of crime and socioeconomic
conditions disappear when the presence or absence of a human relations commission is
Table 2 • Logistic Regression Coefficients for Community and Organizational Influences on the
Presence of a Hate Crime Policy in California Police and Sheriff’s Agencies (N 5 154)
Model 1
Functionality
ln Violent crime rate
.572
(.231)*
Community composition
Ethnic heterogeneity
Socioeconomic conditions
Model 2
Model 3
Model 4
.638
(.317)*
.557
(.303)
.580
(.340)
.480
(.355)
1.952
(1.236)
.538
(.202)*
1.570
(1.244)
.403
(.216)
.973
(1.327)
.399
(.221)
1.334
(1.376)
.343
(.226)
.602
(.386)
.502
(.394)
.573
(.401)
.427
(.198)*
.546
(.232)*
Community demands
Human relations commission
Organizational perviousness
Perviousness
Organizational capacities
ln Size
2.187
(.185)
.543
(.457)
ln Resources
2.661
(.432)
Constant
22 Log likelihood
Model 5
201.382
Model x2
8.352*
d.f.
1
Note: Standard errors are in parentheses.
* p , .05
21.739
(.616)*
21.764
(.616)*
21.447
(.646)*
24.269
(2.496)
192.041
189.63
184.851
183.024
17.693*
3
20.103*
4
24.883*
5
26.710*
7
The Law-In-Between
Table 3 • Probabilities of Having a Hate Crime General Order at Different Contrast Points on
Each Independent Variable
Variable
Violent crime
Ethnic heterogeneity
Socioeconomic conditions
Human relations commissiona
Perviousness
Size
Resources
e(Pr): 25th
Percentile
e(Pr): 75th
Percentile
Change
in e(Pr)
.54
.54
.52
.49
.47
.61
.54
.64
.63
.63
.63
.67
.54
.60
.10
.09
.11
.14
.20
2.07
.06
Note: Each predicted probability is based upon all other variables set to their means.
a
Dummy variable. Contrast points are set at 0 and 1.
introduced into the model, although the human relations commission variable is not significant (see Model 3). Model 4, the most parsimonious model in the table, reveals that a single variable—organizational perviousness—has a significant positive effect on the odds of
having a policy. The size of this significant positive effect increases when two measures of
organizational capacities—agency size and resources—are included in the model. However,
neither agency size nor resources are significant by themselves (see Model 5).
Table 2 reveals that the perviousness effect is consistent across models. At the same time,
functionality, community composition, and community demands are nearly significant and
frequently large. For ease of interpretation, Table 3 reports the predicted probability of having
a hate crime policy in place at different contrast points on each independent variable, when
all other variables are set to their means. Specifically, each predicted probability is computed
for a low value (defined as the 25th percentile point) and a high value (defined as the 75th
percentile point), with all of the other variables set to their means.13 For comparative purposes, the percentage point difference between the low value and a high value is provided in
the final column of Table 3. Table 3 reveals that, across contrast points, perviousness produces
the largest percentage point difference (20), followed by human relations commissions (14),
socioeconomic conditions (11), violent crime (10), and heterogeneity (9). Perviousness is
clearly the best predictor of hate crime policy.14
The above analysis provokes a final empirical question: what conditions influence agencies’ degree of perviousness? To address this question, we estimated OLS models with organizational perviousness as the dependent variable. Model 1 in Table 4 shows that communities
with higher violent crime levels and greater ethnic heterogeneity house agencies with more
perviousness. However, as revealed in Model 2, the ethnic heterogeneity effect disappears
when two measures of organizational capacity are controlled. Specifically, agencies with
more employees proportionate to the population they serve and agencies with lower per capita expenditures are generally more pervious. The organizational wealth effect—which is
negative—suggests agencies with fewer resources are more pervious even when controlling
for agency size and community crime rate. This finding suggests that when financial resources
are scarce, agencies are open to involving the community in policing activities. Doing so may
13. This set of thresholds is more conservative than the highest and lowest values on each variable recommended
by Long (1997).
14. Given the centrality of perviousness in this analysis, a test for interaction effects between perviousness and
other factors, especially human relations commission, socioeconomic conditions, and crimes, was worthwhile. Despite
the plausibility that each of these factors may have had greater influence on policy creation in highly pervious agencies,
no evidence was found to support interaction effects.
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Table 4 • OLS Coefficients for Community and Organizational Influences on Organizational
Perviousness (N 5 154)
Model 1
Functionality
ln Violent crime rate
Community composition
Ethnic heterogeneity
Socioeconomic conditions
Community demands
Human relations commission
Organizational capacities
ln Size (employees per 1,000 population)
Ln Resources (expenditures)
Constant
R
2
Model 2
.216 (.088)*
.268 (.078)*
1.197 (.508)*
.109 (.090)
.215 (.460)
.112 (.079)
.224 (.173)
.062 (.151)
—
—
.401 (.056)*
2.416 (.152)*
21.099 (.238)*
1.377 (.829)
.157
.378
Note: Standard errors are in parentheses.
* p , .05
facilitate informal social control when resources constrain the available formal mechanisms
for control. Taken together, these findings suggest that perviousness is influenced by what we
called “functionality” (i.e., the “need” for the policy) and the organizational capacities required
to respond to that need.
Our key finding, then, is that organizational perviousness is the strongest predictor of
policy innovation at the local law enforcement level. Organizational perviousness is, in turn,
a product of functionality and organizational capacity. Put simply, community characteristics
shape the kind of law enforcement agency a community develops, which in turn affects the
probability of having a local hate crime enforcement policy.
Perviousness, Context, and the Law-In-Between
Legal statutes created at the highest levels are often decoupled (see note 3) from the behavior of frontline enforcement officials. In the arena of crime policy, the disjuncture between
policymaking and policy implementation is especially pronounced given the pro-innovation
leanings of legislatures and the anti-innovation tendencies of many law enforcement officers.
However, between these levels are law enforcement agencies and local communities that
can facilitate or impede the implementation process. Local agencies can facilitate implementation by creating protocols, definitions, and enforcement guidelines—a process we refer to
as operationalization—in order to create and codify organizational meaning and manage enforcement. Surprisingly, however, the role of local context, both in terms of the contours of
the community and the enforcement organization itself, is understudied and thus poorly understood. Therefore, this article has focused on how local community and organizational contexts shape the adoption of hate crime policies in California police and sheriff’s agencies.
Our focus on community and organizational factors enables us to examine the most
proximate influences on the adoption of hate crime policy and to offer conclusions regarding
the ways local context, including a community-organization nexus, affects policy adoption.
Our analyses show that community factors thought to be associated with innovative crime
control policy—such as the crime rate and expressed community demands—are by themselves
The Law-In-Between
insufficient predictors of the adoption of hate crime policies by law enforcement agencies.
Instead, organizational perviousness is crucial to policy operationalization. By conceptualizing organizational perviousness as a condition that subsumes elements of both susceptibility
and alignment, we move beyond previous formulations of susceptibility (see Davis and Greve
1997) and philosophical resonance (see Maxson and Klein 1997) to recast the communityorganizational nexus that constitutes the context in which local policy is developed (or not).
By perviousness we mean to point to both the organization’s susceptibility to environmental
influence and the degree to which a particular innovation aligns with the local agency’s existing culture and practices.
Our findings demonstrate that the condition of perviousness is shaped by both environmental and organizational features. Specifically, agencies in high crime environments as well
as large agencies and those with low levels of organizational resources tend toward greater
perviousness. In other words, perviousness results from a conjunction of organizational properties and environmental conditions. The effects of the latter factors on agency policy are
indirect—mediated through perviousness.
Beyond merely exposing the aggregate patterns of policy operationalization and recognizing organizations’ crucial role in this process, our study underscores the value of analyzing
enforcement organizations and their immediate environments. By translating state statutes
into workable terms via the adoption of a formal policy, law enforcement agencies create the
opportunity for law enforcement officials to be aware of, understand, and respond to biasmotivated violence. Moreover, formal policies create the opportunity for citizens to have a
say in how this translation process unfolds. These factors are perhaps most pronounced insofar as the U.S. criminal justice system is, at best, only a “loosely coupled system” (Hagan
1989; Hagan, Hewitt, and Alwin 1979).
In theoretical terms, our findings support and extend both classic and more recent institutionalist arguments. First, in relation to classic arguments, our analysis demonstrates that
the larger institutional environment affects organizational behavior. However, it also demonstrates that organizations differentially receive and react to environmental influences, depending upon their perviousness. Second, our findings affirm the importance of the relationship
between functionality and organizational structure, including policy (Boyle 2002; Boyle and
Meyer 1998). Functionality matters, but in this case, the effects of functionality are mediated
by characteristics of organization-environment relations. Third, this study highlights a new
and unexamined dimension of the institutional context that conditions the “micropolitics of
trouble” (Emerson and Messinger 1977) in social control settings and specifies one further
resource that may be incorporated in the everyday “social problems work” (Holstein and
Miller 2004) through which crime, deviance, and social problems are constituted.
Although this article does not address the degree to which policymaking at the level of
the law-in-between shapes the behavior of law enforcement agents, it nonetheless moves us
one step closer to developing a more comprehensive understanding of why law-in-action
often does not align with law-on-the-books. By positioning police and sheriffs departments’
organizational policies as an intermediary mechanism through which abstract legal codes are
translated into instructions for concrete law enforcement practices, we move beyond a simplistic understanding of law-on-the-books and law-in-action that speaks only to these two
dimensions of a larger process of lawmaking and implementation. We call attention to lawin-between as a place wherein law enforcement agencies, both individually and as a recognizable organizational field, mediate law by encouraging or discouraging the enforcement of
criminal law and defining its parameters in the process. Embracing a temporally sensitive
view of lawmaking, we argue that the adoption of law by legislative bodies creates laws-onthe-books, which is best envisioned as an early stage of lawmaking. Thereafter, an intermediary stage of lawmaking involves policy operationalization as a source of lawmaking best
described as the law-in-between. Finally, of course, the law-in-action constitutes the third
stage of lawmaking.
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JENNESS/GRATTET
Future research should examine the next stage in the process identified in Figure 1.
Namely, it remains to be seen whether having crime control policies in place in law enforcement agencies affects what police officers actually do as they exercise discretion. We should
now ask whether having a hate crime policy in place actually increases the likelihood that
police officers will recognize incidents as hate crime and respond to them accordingly. Does
having a hate crime policy in place influence what law enforcement officers actually do when
they go about the business of enforcing hate crime law? If so, how do organizational- and
community-level variables, especially organizational perviousness, affect this relationship?
Sociolegal scholars, organizational theorists, and criminologists alike are committed to explaining the conditions under which law, and social policy more generally, is symbolic, instrumental, or—in some cases—both.15 Accordingly, the next step is to determine whether hate crime
policy is merely symbolic (as some have argued) or instrumental (as the law mandates)—or a
little bit of both, depending upon the organizational and community factors that mediate its
enforcement (see Jenness and Grattet 2005). At least two possibilities exist. First, department
policies may have no effect on what officers actually do. If this is the case, one could argue
that hate crime policies are merely symbolic (Edelman 1964; Gunnlaugsson and Galliher
1986; Gusfield 1967). In contrast, a policy—the law-in-between—might sensitize officers to
the problem of bias-motivated violence, provide them with a new conceptual tool to define
the parameters of the problem, and result in increased reporting of hate crime. If so, one
would be hard-pressed to argue that hate crime policies are merely symbolic when observable
consequences are evident.
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Appendix
Table A • Correlations, Means, and Standard Deviations of Variables
2
1. ln Violent crime
2. Ethnic heterogeneity
3. Socioeconomic conditions
4. Human relations commission
5. Perviousness
6. ln Size
7. ln Resources
* p , .05
** p , .01
3
4
5
.48*** 2.33*** .15
.30***
—
2.34*** .23**
.31***
—
—
.28*** 2.01
—
—
—
.22***
—
—
—
—
—
—
—
—
—
—
—
—
*** p , .001
6
7
.14
.14
.31*** 2.04
.02
.17*
.23***
.05
.53***
.01
—
.27***
—
—
Mean
SD
1.70
.50
0
.60
0
.57
5.30
1.01
.18
1.00
.49
1.00
1.31
.47
359