LEARNING TO BE BAD: ADVERSE SOCIAL
CONDITIONS, SOCIAL SCHEMAS, AND
RONALD L. SIMONS
Department of Sociology
University of Georgia
CALLIE HARBIN BURT
School of Criminology and Criminal Justice
Arizona State University
KEYWORDS: crime, criminological theory, social schemas, discrimina-
tion, integrated theory
In this article, we develop and test a new approach to explain the
link between social factors and individual offending. We argue that
seemingly disparate family, peer, and community conditions lead to
crime because the lessons communicated by these events are similar
and promote social schemas involving a hostile view of people and
relationships, a preference for immediate rewards, and a cynical view
of conventional norms. Furthermore, we posit that these three schemas
are interconnected and combine to form a criminogenic knowledge
structure that results in situational interpretations legitimating criminal
behavior. Structural equation modeling with a sample of roughly 700
African American teens provided strong support for the model. The
ﬁndings indicated that persistent exposure to adverse conditions such
as community crime, discrimination, harsh parenting, deviant peers,
and low neighborhood collective efﬁcacy increased commitment to the
three social schemas. The three schemas were highly intercorrelated and
combined to form a latent construct that strongly predicted increases in
∗This research was supported by the National Institute of Mental Health
(MH48165, MH62669) and the Center for Disease Control (029136-02). Addi-
tional funding for this project was provided by the National Institute on Drug
Abuse and the National Institute on Alcohol Abuse and Alcoholism. We thank
Tanja Link, Brea Perry, Travis Pratt, Eric Stewart, several anonymous reviewers,
and Denise Gottfredson for valuable comments on earlier drafts of this article.
Direct correspondence to Dr. Ronald L. Simons, Department of Sociology, Uni-
versity of Georgia, Athens, GA 30602 (e-mail: firstname.lastname@example.org).
C2011 American Society of Criminology doi: 10.1111/j.1745-9125.2011.00231.x
CRIMINOLOGY Volume 49 Number 2 2011 553
554 SIMONS & BURT
crime. Furthermore, in large measure, the effect of the various adverse
conditions on increases in crime was indirect through their impact on
this latent construct. We discuss the extent to which the social-schematic
model presented in this article might be used to integrate concepts and
ﬁndings from several major theories of criminal behavior.
The history of science clearly indicates that as the understanding of
causal processes develops, what initially appears extremely complex
ultimately proves to reduce to a relatively small number of mediating
mechanisms. Clearly, this reduction is needed in the ﬁeld of antisocial
behavior ...(Rutter, 2003: 3–24)
Studies indicate that perpetrators tend to view their criminal actions as
legitimate and acceptable given the prevailing circumstances (Baumeister,
1997; Giordano, Cernkovich, and Rudolph, 2002; Katz, 1988). Offenders
usually do not see their behavior as evil or immoral. Instead, they consider
their deeds to have been sensible, necessary, inevitable, or compelled by
the exigencies of the situation (Katz, 1988; Shermer, 2004; Steffensmeier
and Ulmer, 2005; Sykes and Matza, 1957). In many instances, offenders
perceive their actions as a moralistic pursuit of justice calculated to address
some injustice or grievance (Black, 1998; Katz, 1988). After arrest, perpe-
trators almost always ﬁnd public portrayal of their crimes to be dramatically
different than the meaning they attributed to their behavior at the time
of the offense (Baumeister, 1997; Black, 1998). This ﬁnding suggests that
the challenge in explaining crime is identifying the factors that cause some
individuals to perceive that illegal actions are warranted, necessary, and
justiﬁed. We need a theory that speciﬁes the social circumstances and life
lessons that foster this deviant view of reality.
Questions about learning naturally suggest a social-learning framework,
which in criminology is dominated by Akers’s social learning theory (Akers,
1985, 1998; Akers and Sellers, 2009). According to Akers’s model, social
learning takes place through imitation and reinforcement. Individuals attain
deﬁnitions either favorable or unfavorable to the commission of crime as a
consequence of imitation and reinforcement in their everyday environment.
Consonant with this perspective, this article is concerned with identifying
the processes whereby adverse social circumstances inﬂuence situational
deﬁnitions favorable to the commission of crime. We depart from Akers’s
social learning theory, however, by shifting the emphasis from operant
learning to the messages or principles communicated by persistent and
recurring circumstances that comprise an individual’s everyday existence.
Rather than focusing on schedules of reinforcement, we accent the lessons
or tenets implicit in the repetitive patterns of interaction occurring within
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 555
a person’s social space. The heuristic value of this altered focus is that
it suggests a common set of avenues whereby seemingly disparate social
environments foster crime.
Past research has provided strong evidence that exposure to commu-
nity disorganization (e.g., Sampson, Morenoff, and Gannon-Rowley, 2002),
harsh parenting (e.g., Reid, Patterson, and Snyder, 2002), deviant peers
(e.g., Warr, 2002), racial discrimination (e.g., Simons et al., 2003), and a
wide variety of other adverse circumstances (Agnew, 2006) increases the
chances that a person will engage in criminal behavior. In the following
pages, we argue that this is the case because the lessons communicated by
these events promote social schemas that combine to form a criminogenic
knowledge structure that shapes situational interpretations legitimating or
compelling criminal and antisocial behavior. We test this social-schematic
perspective on crime using longitudinal data from roughly 700 African
American adolescents. Finally, we discuss the implications of this new
social-learning approach to explaining crime.1
LESSONS AND SCHEMAS
Numerous theories in social and developmental psychology (Baldwin,
1992; Cassidy and Shaver, 2008; Dodge and Pettit, 2003) as well as in
cultural sociology (Bourdieu, 1990, 1998; Meisenhelder, 2006) suggest that
social schemas serve as the link between past experiences and future
behavior. Social schemas are internalized representations of the patterns
inherent in past social interactions that guide the processing of future
social cues (Crick and Dodge, 1994). They are abstract principles and
dispositions that are tacitly relied on when perceiving situations and form-
ing lines of action (Bourdieu, 1990; Meisenhelder, 2006). All situations
involve a vast array of stimuli, and social schemas simplify the task of
processing that information as they specify the regularities, patterns, or
rules of everyday life (Dodge and Pettit, 2003). These simplifying principles
make deﬁning and responding to situations more efﬁcient as they suggest
which cues are most important, the meaning of these stimuli, and the
likely consequence of various courses of action (Baldwin, 1992; Crick and
1. We should note that the emphasis in the current article is on explaining street
crimes. Although we believe that this schematic perspective can be extended to
white-collar and corporate crimes as well, we believe that nontrivial distinctions
are present in the social factors that inﬂuence these divergent offenses. Thus, the
current focus is on street crimes, but extending the model to “suite” crimes is an
important next step.
556 SIMONS & BURT
Social schemas are durable as they are the internalization of patterns
intrinsic to the repeated and persistent interactions to which the individ-
ual has been exposed, and they are transposable in that they are carried
into new settings and situations (Bourdieu, 1990, 1998; Sallaz and Zavisca,
2007). Humans who inhabit the same position in the social world develop
comparable constellations of schemas (Bourdieu, 1984, 1990; Crick and
Dodge, 1994). Similar conditions of existence result in a common set of
schemas, with the consequence being similar expectations, choices, and
lines of action.
Offenders are more likely than their conventional counterparts to have
experienced difﬁculties and challenges relating to community disadvan-
tage, inept parenting, discrimination, afﬁliation with deviant peers, and
so on. These various hardships and disadvantages are so disparate that
one might assume that each of them inﬂuences involvement in crime
through a separate and unique avenue. Indeed, this is the assumption
of many theories of crime. In contrast, we posit that these family, peer,
and community conditions increase crime through a common mechanism;
they teach a mutual set of lessons that are internalized as social schemas
that justify crime. This collection of schemas includes a hostile view of
relationships, a concern with immediate gratiﬁcation, and a cynical view
of conduct norms. These schemas, each of which is discussed in later
sections, closely correspond to cognitive constructs that extant work has
linked to offending. Speciﬁcally, they relate to theory and research con-
cerned with hostile attributions (Dodge, 2006; Dodge, Bates, and Pettit,
1990), low self-control (Gottfredson and Hirschi, 1990), and commitment
to conventional norms (Akers, 1998; Bandura et al., 1996; Hirschi, 1969),
We expect that these social schemas are correlated and coexist. Our
rationale for this prediction is twofold. First, these schemas represent
mental structures that are a function of the same set of social conditions
such as poor parenting and bad neighborhoods. Second, as will be argued
in the subsequent discussion, we have good reason to believe that these
deviant schemas impact one another. A hostile view of relationships, in
particular, is likely to foster belief in the other two schemas. We now turn to
consideration of each of the three schemas that constitute the criminogenic
HOSTILE VIEW OF RELATIONSHIPS
Numerous studies (Baldwin, 1992; Bowlby, 1982; Dodge and Pettit, 2003;
Mikulincer and Shaver, 2001) have documented how relationship schemas
inﬂuence a person’s interaction with others. These studies indicate that
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 557
individuals who possess an optimistic, trusting model of relationships en-
gage in warm, cooperative interactions with other people, whereas those
who hold a hostile, distrusting model approach others with suspicion and
aggression. Given their cynical view of relationships, persons who hold a
hostile view of relationships assume that most people are unfair and cannot
be trusted to reciprocate. They expect to be cheated and exploited and
believe that they must use coercive measures both to obtain what they
deserve and to punish wrongdoers (Dodge, 1980, 1986; Dodge, Bates, and
Pettit, 1990; Slaby and Guerra, 1988).2They are hypersensitive to disrespect
and consider a strong response to such events to be imperative. To let
transgressions go unchallenged, even small ones, demonstrates weakness
and exposes one to future predation and exploitation. Such an orientation
to relationships is a major component of what Anderson (1999) labeled
the “code of the street.” Furthermore, persons with a hostile view of re-
lationships regard most people as different from themselves, which blunts
empathy as humans tend to show empathy and sympathy toward individ-
uals perceived as trustworthy and similar to themselves (Berreby, 2005;
de Waal, 2008).
A hostile view of relationships would be expected to promote situational
deﬁnitions leading to aggression, intimidation, and exploitation of others.
Consistent with this idea, research has shown that this view of relationships
is strongly held by aggressive children and adolescents (Burks et al., 1999;
Dodge, Bates, and Pettit, 1990; Dodge et al., 2002; Dodge and Newman,
1981; Zelli et al., 1999). Indeed, a meta-analysis of more than 100 studies
reported a robust association between a hostile view of others and youth
aggression (Orobio de Castro et al., 2002); moreover, antisocial adults
also demonstrate this cognitive bias (Bailey and Ostrov, 2007; Epps and
Kendall, 1995; Vitale et al., 2005). Furthermore, strong evidence suggests
that aggression and violence are often responses to situations in which an
individual feels disrespected (Anderson, 1990, 1999; Gilligan, 2001; Jacobs
and Wright, 2006; Kubrin and Weitzer, 2003), and possessing a hostile view
of relationships increases the likelihood that an individual will interpret an
interaction as involving such an affront.
2. Originally, we identiﬁed four schemas instead of three. What currently is iden-
tiﬁed as a hostile view of relationships was separated into two schemas, with
one involving a cynical, distrusting view of other people and their motives and
another consisting of the need to be tough and aggressive to avoid exploitation.
Statistically, however, these two components were not clearly distinguishable, and
theoretically, these two dimensions capture analogous ideas and come together
in Dodge’s (1980) conceptualization. After considerable reﬂection and a helpful
nudge from a reviewer, we concluded that these two schemas should be combined
to represent one indicator of the criminogenic knowledge structure labeled a
hostile view of relationships.
558 SIMONS & BURT
Several studies have shown that persistent exposure to harsh, emotionally
distant parenting fosters a hostile view of relationships (Dodge, Bates,
and Pettit, 1990; Mikulincer and Shaver, 2001). We argue that models of
relationships are learned and reinforced in a wide variety of settings besides
the family. Research shows, for example, that racial discrimination foments
a hostile view of relationships (Simons et al., 2003, 2006). This result would
be expected as victims of discrimination learn ﬁrsthand that people often
show prejudice and favoritism in their treatment of others. In addition to
harsh parenting and discrimination, we expect that other adverse conditions
that have been linked to crime also contribute to a hostile view of others.
This includes persistent exposure to a deviant peer group as interacting in
such settings often focuses on the need to stand up to the members of other
groups who cannot be trusted (Granic and Dishion, 2003). Furthermore,
living in a neighborhood where crime and victimization are high is apt
to promote a hostile, distrustful view by providing persistent examples of
individuals who are deceitful and treacherous (e.g., Anderson, 1999). In
contrast, exposure to supportive parenting and residing in an area high in
collective efﬁcacy are likely to encourage a more positive view of people
and relationships. Supportive parents show kindness and altruism, and the
residents of efﬁcacious communities assist one another and make sacriﬁces
for the common good.
IMMEDIATE GRATIFICATION (DISCOUNTING THE
Self-control has been the centerpiece of several theories of crime
(Gottfredson and Hirschi, 1990; Wilson and Herrnstein, 1985), and an
enormous body of research demonstrates that self-control is an important
predictor of crime (e.g., Pratt and Cullen, 2000). Importantly, research
also shows that individuals’ self-control is inﬂuenced by social experiences
and events, such as parenting (e.g., Hay, 2001), peers (Burt, Simons, and
Simons, 2006), and community characteristics (Pratt, Turner, and Piquero,
2004). Self-control involves inhibiting impulses and delaying gratiﬁcation to
obtain a later reward (e.g., Gottfredson and Hirschi, 1990). Although most
individuals develop at least a modest ability to delay gratiﬁcation, virtually
everyone tends to discount distant compared with more immediate rewards.
People differ in their discounting curves, however, with some individuals
showing a weak and others a strong tendency to discount future rewards
and consequences (Ainslie, 2000; Gottfredson and Hirschi, 1990; Mischel
and Shoda, 1995; Wilson and Herrnstein, 1985).
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 559
When individuals perceive that a low probability exists that their be-
havior will result in long-term beneﬁts, they engage in steep discount-
ing. At least seven experiments have reported that socially excluded in-
dividuals show a reduction in self-control when they are led to believe
that their actions will have no impact on future acceptance (de Waal,
2008). Furthermore, a recent experiment found that exposure to infor-
mation suggesting the world is unjust enhanced participants’ preferences
for immediate versus larger, delayed rewards (Callan, Snead, and Olson,
2009), and several studies have reported that fatalism regarding the future
increases the acceptability of risky behavior, including crime (Brezina,
Tikan, and Topalli, 2010; Caldwell, Wiebe, and Cleveland, 2006; DuRant
et al., 1994; Hill, Ross, and Low, 1997; Ross and Hill, 2002; Wilson and
These studies indicate that patience and delayed gratiﬁcation are often
not practical (Hauser, 2006; Wilson, 2007). In some environments, reci-
procity and fair play are uncommon and delayed rewards rarely materialize.
In such contexts, steep discounting of future events and pursuing immedi-
ate rewards is a rational response to information indicating an uncertain
probability of reaping delayed beneﬁts (Callan, Snead, and Olson, 2009;
Wilson, 2007; Wilson and Daly, 1997, 2006). It is adaptive for individuals
living in such unpredictable, hostile environments to be opportunistic in
their pursuit of rewards. In this way, we argue that delayed gratiﬁcation
(i.e., the exercise of self-control) will be reduced by persistent exposure
to community crime, racial discrimination, and deviant peers. Inherent
within these experiences is the lesson that life is unfair and unpredictable
and that one should take advantage of rewards whenever they become
available. However, supportive parenting and collective efﬁcacy are likely
to increase the delay of gratiﬁcation and pursuit of long-term rewards as
such experiences indicate that people are trustworthy and can be depended
on to keep their word.
In addition, we propose that concern with immediate gratiﬁcation is likely
reinforced by a hostile view of relationships. Such a view of relationships
suggests that people cannot be trusted to reciprocate or to keep their
promises. Therefore, one should obtain rewards from others whenever they
become available. Also, a hostile view of relationships reduces empathy and
undermines concern about the impact of one’s actions on others, thereby
making it easier to pursue immediate rewards without regard for the delete-
rious consequences for others. Other individuals are more likely to become
potential marks if they are untrustworthy, if one does not empathize with
them, and if one is unconcerned with treating them fairly (Berreby, 2005;
Sykes and Matza, 1957). Thus, a hostile view of relationships consequently
would result in reinforcing concern with immediate gratiﬁcation and an
opportunistic scrutiny of situations.
560 SIMONS & BURT
CYNICAL VIEW OF CONVENTIONAL NORMS
The last element in the criminological knowledge structure involves a
person’s beliefs regarding society’s norms of conventional conduct. Some
individuals consider social norms prohibiting sexual promiscuity, ﬁghting,
substance use, cheating on tests, and so on to be legitimate, morally com-
pelling standards of behavior, whereas others possess a cynical, contemp-
tuous view of these social rules. Several studies have reported that a dis-
paraging view of conventional norms increases the probability of engaging
in criminal behavior (e.g., Akers, 1998; Hirschi, 1969).
Both social control (Hirschi, 1969; Sampson and Laub, 1993) and social
learning theories (Akers, 1998) argue that supportive parenting increases
the chances that a youth will develop a commitment to conventional norms.
In addition, social learning theory (Akers, 1998) emphasizes the role of
peer afﬁliations. Consistent with these arguments, numerous studies have
reported that involved, supportive parenting increases commitment to con-
ventional norms, whereas afﬁliation with deviant peers discourages such
commitment (see Akers and Sellers, 2009).
We argue that a cynical view of conventional norms is also rooted in
other social circumstances. Community collective efﬁcacy, for example,
would be expected to enhance a youth’s commitment to social norms as
it communicates that residents believe that conduct norms are legitimate
and worthy of enforcement. When residents fail to respond to deviance,
however, adolescents are apt to conclude that conduct norms are inconse-
quential. Similarly, events such as neighborhood crime and discrimination
convey the message that conduct norms are unimportant. These incidents
indicate that, instead of playing by society’s rules, people simply tend to
pursue their selﬁsh interests.
We expect that a cynical view of conduct norms is reinforced by the other
two criminogenic schemas. Many persons respect authority and believe that
most conventional norms enhance social order, harmony, and organization.
Individuals who trust and care about others and who delay immediate
gratiﬁcation to obtain long-term rewards usually perceive the value of
honoring these conventions. We have noted, however, that in response
to the lessons inherent in their everyday circumstances, some individuals
perceive life as unpredictable or believe that society consists of selﬁsh,
untrustworthy people and therefore judge that the wisest approach is to
enjoy rewards whenever they become available. For these opportunistic
persons, honoring social prohibitions regarding sex, drugs, ﬁghting, and so
on makes little sense. If other people are not following society’s rules, then
why should they? Only a sucker would do so. Furthermore, their hostile
view of relationships contributes to a lack of trust and respect for the
authority ﬁgures and social institutions that champion these social rules.
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 561
Thus, we expect that persons possessing a hostile view of relationships and
seeking immediate gratiﬁcation will tend to hold a cynical view of society’s
THE CRIMINOGENIC KNOWLEDGE STRUCTURE
We have argued that the social schemas comprising an individual’s
knowledge structure tend to be interrelated and connected as they are
rooted in the same set of social conditions and are mutually reinforcing.
In addition, we expect that they operate as a dynamic unit. It is not any one
schema that predicts an individual’s actions in a situation; rather, it is the
dynamic interplay of the constellation of relevant schemas that is important
(Bourdieu, 1984; Swartz, 2002). A person’s collection of schemas operates
in a manner analogous to the rules of grammar or to the rules of a game. A
person tacitly integrates the rules of grammar when formulating linguistic
utterances or follows the rules of the game when designing a strategic move.
Likewise, individuals implicitly combine the rules of social life represented
by their constellation of schemas when construing situational circumstances
and constructing a line of action (Bourdieu, 1984, 1990). Based on this idea,
we expect that it is the combination of the three schemas, and not simply
belief in any one element, that is most important in explaining individual
variation in offending. Past research has investigated the extent to which
speciﬁc attitudes and beliefs predict criminal behavior, whereas our social-
schematic approach suggests that it is the constellation of schemas—the
dynamic whole rather than the sum of the parts—that predicts crime and
Notably, the model proposes that learned knowledge structures, rather
than situational factors, are the primary mechanisms that account for
the causal effects of social factors on crime. The model views objective
situational opportunities for crime as ubiquitous, whereas perceived op-
portunities for crime are largely dependent on individuals’ knowledge
structures, as individuals with criminogenic knowledge structures often
construe the routine situations encountered in everyday life as an oc-
casion for some antisocial act.3Although situations occur that virtually
compel criminal behavior (e.g., a rival gang invades another’s turf or a
3. Notably, this assumption does not imply that opportunities for speciﬁc offenses are
ubiquitous. We do not assume that all individuals and groups have opportunities
for the same offenses but that the opportunity for an act of law violation is ubiq-
uitous. For example, the opportunity for assault is generally available whenever
another person is present; likewise, the opportunity for theft is present whenever
another’s private property is available. We acknowledge, however, the fact that
opportunities for speciﬁc offenses do vary across individuals, groups, space, and
time. For example, some individuals have ready access to illicit drugs, whereas
562 SIMONS & BURT
companion pulls a knife on a shopkeeper), we argue that for the most
part individuals with a criminogenic knowledge structure select themselves
into such situations. However, it is certainly the case that individuals some-
times encounter, not by design or through any fault of their own, situations
that are so provoking that they incite a violent or antisocial response
regardless of a person’s knowledge structure, such as walking in on your
spouse having sex with a family friend. Importantly, we argue that, even in
such situations, it is still the case that those more strongly committed to the
criminogenic knowledge structure are most likely to respond in a violent or
Throughout human history and in every culture, men have displayed
higher rates of aggression and antisocial behavior than women (Archer,
2004; Gottfredson and Hirschi, 1990; Steffensmeier et al., 2005). Therefore,
any compelling theory of crime must account for this major and persistent
sex difference (Wilson and Herrnstein, 1985). Although a comprehensive
discussion of the role and effects of sex or gender in the proposed theoret-
ical model is beyond the scope of the present study, given the salience of
sex differences, we brieﬂy outline the basics in our approach.4We expect
that a portion of the association between sex and crime is explained by
males being somewhat more likely than females to experience the adverse
social conditions that have been linked to crime. Some evidence indicates,
for example, that boys are more likely than girls to experience harsh
parenting (Sobsey, Randall, and Parrila, 1997), criminal victimization
(Stewart, Schreck, and Simons, 2006), and afﬁliation with deviant peers
(Warr, 2002). The observed sex differences, however, are usually small, and
others might be unable to procure drugs despite much effort. Some individuals live
or work in areas where frequent exposure to unmonitored valuable goods occurs,
or where others rarely encounter such easy opportunities for theft.
4. We use the term “sex” rather than the term “gender” because we are discussing
differences between males and females, the biological groups, although we do
not imply that these differences are simply caused by biological characteristics.
Drawing on evolutionary theory, we discuss the origins of differences in risk taking
and aggressiveness among males and females. It is certainly the case, however, that
as societies have developed these differences based on the survival of progeny,
they have taken on a life of their own in the social expectations, rules, regulations,
and constraints that are implicated in the social construct of gender, such that now,
for example, being a girl means not being aggressive, whereas rough and tumble
play among boys is just “boys being boys.” An elaborate discussion of sex and
gender differences is out of the scope of this article, but we wish to make clear that
this model does not suggest that biology explains male and female differences in
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 563
we expect that they account for only a modest proportion of the association
between sex and crime. Instead, we posit that the greater portion of the
association between sex and crime is explained by evolved sex differences
that inﬂuence the probability that men and women will develop schemas
that comprise the criminogenic knowledge structure.
From an evolutionary perspective, sex differences are expected wherever
men and women are exposed to differing selection pressures. Throughout
human history, the mother’s presence was more critical to the survival
of her offspring than was that of the father (Campbell, 1999; Campbell,
Muncer, and Bibel, 2001). Studies in preindustrial societies conﬁrm that
the death of the mother is the single most important threat to infant
survival (Hill and Hurtado, 1996; Voland, 1988). This ﬁnding suggests that
women who were cautious and avoided risky situations would have been
more likely to reproduce successfully (Campbell, Muncer, and Bibel, 2001).
In contrast, scholars have argued that risk taking among males increased
survival and reproductive success by vanquishing rivals, killing prey, and
attracting mates (Daly and Wilson, 2001; Wilson and Daly, 1985). As a
consequence of these differing environmental pressures, the available ev-
idence suggests that women have evolved a lower threshold for fear than
men (Campbell, Muncer, and Bibel, 2001). Scores of studies have found
that girls express fear earlier than boys and that women experience fear
and phobias more frequently and intensely (given the same stimulus) than
men (see Campbell, 2006). Furthermore, research shows that on average
females are more cautious, are more sensitive to potential dangers, and
engage in less risk taking than males (Byrnes, Miller, and Schafer, 1999;
Hersch, 1997). These ﬁndings portend sex differences regarding elements
of the criminogenic knowledge structure.
First, women’s concern with safety and security reduces the probability
that they will adopt a hostile view of relationships. Although women are
no less likely than men to develop the perception that people cannot
be trusted, their greater fear and caution is likely to deter them from
embracing a tough, coercive response to perceived mistreatment. After
all, aggressive encounters could result in injury. Furthermore, physically
aggressive acts by females attract more social control than that for males
given that aggressive acts are inconsistent with social constructions of
femininity (e.g., Messerschmidt, 1993). Rather than criminalized physical
aggression, research shows that females are more likely to engage in in-
direct or relational aggression, which is not regulated by criminal statutes
Osterman, and Lagerspetz, 1994). In addition, we expect that
women are generally more likely than men to endorse conventional norms
prohibiting ﬁghting, drug use, cheating, driving fast, and so on. Given the
danger associated with these behaviors, women are more apt than men
to see the wisdom of rules proscribing such activities. Finally, we expect
564 SIMONS & BURT
Figure 1. A Social-Schematic Model of Crime
Hostile View of
to ﬁnd sex differences in self-control. Although we have no reason to
believe that men and women differ in the general tendency to pursue
immediate rewards in response to environments that fail to reward delayed
gratiﬁcation, women seem to be more cautious than men regarding the
instantaneous reinforcement associated with risky or dangerous activities
(Burton et al., 1998; Keane, Maxim, and Teevan, 1993; LaGrange and
Silverman, 1999; Nakhaie, Silverman, and LaGrange, 2000; Tittle, Ward,
and Grasmick, 2003).
Figure 1 presents a general model summarizing our theoretical argu-
ments. The model suggests that the various social-environmental condi-
tions emphasized in many dominant criminological theories inﬂuence risk
for crime because they inﬂuence the development of the following social
schemas: a hostile view of relationships, focus on immediate rewards, and
low commitment to conduct norms. These cognitive schemas, in turn, in-
crease the probability that an individual will deﬁne situations in a manner
that legitimates, justiﬁes, or requires criminal behavior. These deﬁnitions
might involve, for example, a perceived threat, slight, or injustice that
requires a forceful reaction. Or they might entail discerned opportunities
for a quick reward or an immediate beneﬁt by engaging in behavior that
ﬂouts convention or exploits others.
Turning to speciﬁc predictions derived from this model, we have argued
that the three criminogenic schemas are rooted in similar social conditions
and that they are mutually reinforcing. Thus, our ﬁrst hypothesis is that
the three schemas will be intercorrelated and will load as indicators of
a latent construct that we call a criminogenic knowledge structure. The
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 565
model suggests that this criminogenic knowledge structure increases the
likelihood of crime because it promotes situational deﬁnitions favorable
to such lines of action. Unfortunately, our data set does not include as-
sessments of situational deﬁnitions. Therefore, we only can assess the
extent to which this knowledge structure predicts an increase in crimi-
nal behavior with the assumption that situational deﬁnitions account for
The left side of our theoretical model includes the following social causes
of crime: parenting practices, collective efﬁcacy, neighborhood crime, racial
discrimination, and deviant peers. Perhaps the strongest association in
criminology is that between afﬁliation with deviant peers and involve-
ment in criminal behavior (Warr, 2002). Hence, this variable is a com-
ponent of most criminological theories. Social learning theories, for ex-
ample, assert that parenting (Akers, 1998; Patterson, Reid, and Dishion,
1992) and social disorganization theories argue that collective efﬁcacy
(Sampson, Morenoff, and Gannon-Rowley, 2002) deters association with
deviant peers in addition to discouraging direct involvement in crime.
Similarly, strain theories argue that exposure to high-crime neighborhoods
and racial discrimination (Agnew, 2006; Cloward and Ohlin, 1960) increase
afﬁliation with delinquent peers as well as involvement in crime. In line
with these theories and depicted in ﬁgure 1, we contend that supportive
parenting, collective efﬁcacy, community crime, and racial discrimination
affect criminal propensity in part by inﬂuencing afﬁliation with deviant
peers. We depart from these theories, however, regarding the nature of
the effect of these variables on crime. We contend that the crimino-
genic knowledge structure is the individual-level mechanism that explains
the effects of social factors on individual offending. Thus, we hypothe-
size that the criminogenic knowledge structure mediates the effect of all
of these variables, including afﬁliation with deviant peers, on criminal
Finally, we have no reason to believe that sex differences will occur in
the structural associations posited among the various constructs, although
males might exhibit greater exposure than females to some adverse social
environments. We do expect, however, that sex will be related to the
criminogenic knowledge structure that, in turn, will mediate much, if not
all, of the association between sex and crime.
Our research uses the ﬁrst four waves of the Family and Community
Health Study (FACHS), a multisite (Georgia and Iowa) investigation of
566 SIMONS & BURT
neighborhood and family processes that contribute to the development
of African American children in families living in a wide variety of com-
munity settings (see Gibbons et al., 2004; Simons et al., 2002). Sample
members were recruited from neighborhoods, deﬁned as census tracts,
that varied on demographic characteristics, speciﬁcally racial composition
(i.e., percent Black) and economic level (i.e., percent of families with
children living below the poverty line). In Georgia, families were selected
from 36 census tracts from metropolitan areas such as South Atlanta,
East Atlanta, Southeast Atlanta, and Athens, which varied in terms of
economic status and ethnic composition. In Iowa, the 35 census tracts that
met the study criteria were located in two metropolitan communities—
Waterloo and Des Moines. In both research sites, families were drawn
randomly from rosters and contacted to determine their interest in
The ﬁrst wave of the FACHS data were collected in 1997 from 897
African American ﬁfth-grade children (417 boys and 480 girls; 475 from
Iowa and 422 from Georgia), their primary caregiver, and a secondary
caregiver when one was present in the home. The mean age of the pri-
mary caregiver was 37 years (range, 23–80 years), 93 percent were female,
84 percent were the target’s biological mothers, and 44 percent identiﬁed
themselves as single parents. Their educational backgrounds were diverse,
ranging from less than a high-school diploma (19 percent) to a bachelor’s
or advanced degree (9 percent).
The second, third, and fourth waves of data, which we use for our re-
search, were conducted in 1999–2000, 2001–2002, and 2004–2005 to capture
information when the target children were ages 12–13 years, 14–15 years,
and 17–18 years, respectively. We focus on the latter three waves of data
given that this is a period for escalating rates of delinquency and police
contact (Gottfredson and Hirschi, 1990; Mofﬁtt, 1997; Sampson and Laub,
1993). Of the 897 families, 779 remained in the panel at wave II; 767 were
interviewed at wave III; and 714 were retained at wave IV (80 percent of
the original sample).
Analyses comparing those families that did not participate in waves II or
III did not differ signiﬁcantly from those that participated regarding youths’
age, sex, or participation in delinquency as well as regarding primary
caregivers’ education, household income, or neighborhood characteristics.
Respondents who dropped out after the third wave, however, differed in
a few ways from those in the ﬁrst three waves. A larger percentage of
those interviewed at wave IV were female and, not surprisingly, engaged
in slightly less delinquency (diff =−.51, t=−1.97) on average than those
not reinterviewed at wave IV. A greater proportion of the families that did
not participate at wave IV had lower household incomes on average than
those in the sample. No differences were observed between those remaining
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 567
in the panel and those dropping out with regard to community measures,
family structure, or parenting practices.
Of the original sample of children and their caregivers, 713 people were
interviewed at wave IV. Given the sampling design, these subjects represent
a sample of Black youth from the two research sites that come from ex-
tremely poor-to-middle-class families and who reside in neighborhoods that
exhibit signiﬁcant variability in economic status, racial composition, and
other factors, which are sampling features that are well suited for studying
neighborhood effects (Jencks and Mayer, 1990).
Our analyses primarily use measures from waves III and IV, although
controls for prior delinquency and social schemas are drawn from waves
I and II. We use multiple informants for instances in which youths might
have limited or biased information, such as parenting practices and neigh-
borhood social ties (Furman et al., 1989; Simons, Johnson, and Conger,
1994). In these instances, we combine caregiver and youth reports. This
multimethod approach was assumed to provide a more comprehensive and
valid depiction of parental behavior than measures based only on a single
We have argued that persistent exposure to various environments in-
ﬂuences individuals’ offending through the lessons inherent in social ex-
periences that are internalized or saved as cognitive schemas. Obviously,
this argument implies that exposure to various environments is causally
prior to the development of the schemas, which in turn, inﬂuences later
crime. For several reasons, we model these processes at waves III and IV
rather than measuring one step at each wave. First, we are examining youth
across developmental stages (late childhood through early adulthood) in
which arguably the greatest changes in life circumstances occur. Both the
respondents’ experiences in social situations as well as the individuals’
themselves are different when they are 10–12 years old compared with when
they are 17–20 years old. Most importantly, our analyses are organized by
our proposition that it is persistent exposure to social contexts, rather than
exposure at one time point, that inﬂuences the content of the schema as
well as our contention that more recent exposure to antagonistic or sup-
portive environments should have a stronger inﬂuence on current schemas
than those that occurred many years prior. For these reasons, we use the
average wave III and IV measures of the social contexts to predict the social
schemas and crime measured at wave IV.5Importantly, we examine the
5. When creating the average measures, we standardize the measures prior to av-
eraging. Notably, 39 youths and caregivers, comprising 5 percent of the cases in
568 SIMONS & BURT
veracity of our causal order arguments by testing the effects of changes in
the environments from waves II through IV on changes in the schemas.6
Dependent Variable: Crime
This construct was measured using youth self-reports on the conduct
disorder section of the Diagnostic Interview Schedule for Children, Ver-
sion 4 (DISC-IV). The DISC-IV corresponds to symptoms listed in the
Diagnostic and Statistical Manual-IV (DSM-IV; American Psychiatric As-
sociation, 1994). The DISC-IV was developed during a 15-year period of
research on thousands of youths and parents and has demonstrated reliabil-
ity and validity (Schaffer et al., 1993). The conduct disorder section contains
a series of questions regarding how often during the preceding year the re-
spondent engaged in 26 antisocial acts such as shoplifting, physical assault,
setting ﬁres, vandalism, burglary, and robbery. The maximum possible score
of 26 corresponds to a subject responding that he or she engaged in all of
the different acts. Not surprisingly, no respondent reported engaging in all
26 acts in any wave. The maximum score was 21 at wave IV. The alpha
coefﬁcient for the instrument was greater than .90. The control for previous
delinquency was measured with the instrument averaged across waves I and
II. The maximum scores were 15 and 19 in the ﬁrst two waves, respectively.
The alpha coefﬁcient was greater than .89 in both waves.
Hostile View of Relationships. A hostile view of relationships consists of
the following dimensions: a cynical view of others’ intentions and a belief
in the need for an aggressive attitude to avoid exploitation. The measure
was generated combining two scales that capture each dimension and load
on separate factors. The ﬁrst comprised 16 items that assess respondents’
hostile view of the intentions of others and includes, for example, the
following items: “When people are friendly, they usually want something
from you”; “some people oppose you for no good reason”; and “you have
often been lied to.” The response format ranged from 1 (strongly disagree)
to 4 (strongly agree). The coefﬁcient alpha for the scales were .81 and .88 at
the current study, were not interviewed in the third wave. Rather than deleting
these cases and biasing the sample in creating average wave III and IV measures,
we used the average scores from waves II and IV for these 39 cases. Finally,
preliminary analyses indicated that controls for household income and community
economic disadvantage were not correlated with the outcomes or the mediators
and hence were not included in the present study. For details on the construction
of these measures, see Simons et al. (2005).
6. We also estimate cross-lagged models to test our argument that the plurality of the
effect is from the schemas to crime rather than from the reverse (see appendix A).
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 569
waves II and IV, respectively. A 5-item scale was used to assess the extent
to which respondents believe that a tough, aggressive response to others is
necessary and functional, which is analogous to Anderson’s depiction of the
street code. Respondents indicated how much they agreed or disagreed with
the following statements: “People do not respect a person who is afraid to
ﬁght for his/her rights”; “people tend to respect a person who is tough and
aggressive”; “being viewed as tough and aggressive is important for gaining
respect”; “it is important not to back down from a ﬁght or challenge because
people will not respect you”; and “it is important to show courage and
heart and not be a coward in a ﬁght in order to gain or maintain respect.”
Response categories ranged from 1 (strongly disagree) to 4 (strongly agree).
The coefﬁcient alpha for the mean scale was .78. Only the ﬁrst 2 of the
5 items were available in the wave II instrument. Thus, the wave II measure
of reputation for toughness was the mean of those 2 items (α=.57). The
two dimensions were standardized and averaged to create the measure of
hostile view used in the analyses. The alpha coefﬁcient was .83 at wave IV
and .73 at wave II.
Immediate Gratiﬁcation (Discounting the Future). This construct was
assessed with 13 items and captures respondent’s propensity to discount
the future in choosing courses of action. These items were gleaned from
Kendall and Wilcox’s (1979) good self-control (1 item: “When you have
to wait in line you do it patiently”) and poor self-control scales (6 items,
e.g.: “You would rather have a small gift today than a large gift tomorrow”
and “you have to have everything right away”) as well as Eysenck and
Eysenck’s (1977) risk-taking scale (6 items, e.g.: “You enjoy taking risks”
and “you would do almost anything for a dare”). The resulting mean scale
captures the extent to which the youth focuses on immediate rather than on
delayed gratiﬁcation. The alpha coefﬁcient was .75 and .76 for waves II and
Low Commitment to Social Conventions. This measure includes youth
responses to questions about how wrong they believe it is for someone
their age to engage in various deviant actions. The instrument included
acts such as using marijuana, having casual sex, and cheating on a test. The
response format for each item was as follows: 1) not at all wrong, 2) a little
bit wrong, 3) fairly wrong, and 4) very wrong. The items were reverse coded
prior to creating the mean scale such that the maximum score corresponds
to a response of “not at all wrong” for all 6 items. Only two respondents
scored the maximum. Although 195 individuals (27 percent) indicated that
all deviant acts were “very wrong,” considerable variation in scores was
observed across the sample (α=.78).
570 SIMONS & BURT
This instrument was not incorporated in the wave II interview schedule,
but an analogous norms scale was available. In the second wave, the youths
completed a 4-item scale that asked how they felt about kids their age
having sex, smoking, drinking, or using drugs. The response format for these
items was as follows: 1) You think it is very bad, 2) you think it is bad; 3)
you think it is neither bad nor good, 4) you think it is good, and 5) you think
it is very good. Items were standardized and then averaged to create a mean
scale of deviant norms at wave II (α=.77).
Social Environmental Conditions
Supportive Parenting. The instruments used in creating the quality of
parenting measure were adapted from instruments developed for the Iowa
Youth and Families Project (Conger and Elder, 1994). These measures
have demonstrated high reliability and validity. Prior to data collection,
focus groups conﬁrmed that the items resonate with African American
parents and capture what they consider to be the important dimensions
of effective parenting. Both caregivers and youths completed instruments
assessing problem solving and inductive reasoning, and youth answered
three additional scales concerning parental warmth, hostility, and positive
reinforcement. Respondents were asked about parenting “during the past
12 months”; response categories for the items were as follows: 1) never,
2) sometimes, 3) often, and 4) always. Responses were coded such that
higher scores correspond to superior parenting. In both waves, a composite
supportive parenting measure was created by standardizing and averaging
the scales. These two scales (r=.43) then were averaged to create the
measure of supportive parenting used in the study analyses.
At each wave target, youths answered 9 items concerning parenting
warmth.7The alpha coefﬁcient for the 9-item scale was .89 and .91 at waves
III and IV, respectively. Parental hostility was measured with 14 items that
assess the frequency with which caregivers engage in harsh discipline or oth-
erwise hostile behaviors toward the target youth. These items were recoded
such that a high score indicates an absence of caregiver hostility (α=.83 and
.85). Targets reported on their caregiver’s positive reinforcement; the alpha
coefﬁcient for this 2-item scale was approximately .57. Caregiver problem
solving was assessed with 3 items. The alpha coefﬁcients were roughly .58
for respondents in both waves. Finally, caregiver’s inductive reasoning—
the extent to which caregivers provide explanations for the decisions they
make regarding their children—was measured with respondents’ answers
to 5 items. The alpha coefﬁcient was .86 for youths and .84 for the primary
7. For brevity’s sake, we refer the reader to appendix B in Burt, Simons, and Simons
(2006) for a list of the items included in the parenting measures.
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 571
caregivers. The reliability coefﬁcient for the six scales at wave III was .73,
and for the three scales at wave IV, it was .66. The correlation between the
waves III and IV scales was .43, and the reliability coefﬁcient was .60.
Discrimination. At waves III and IV, the target youth completed 13
items from the Schedule of Racist Events (Landrine and Klonoff, 1996).
This instrument has strong psychometric properties and has been used
extensively in studies of African Americans (e.g., Simons et al., 2006).
The items assess the frequency (1 =never, 4 =several times) with which
various discriminatory events were experienced during the past year. The
scale asks about events that occurred as a consequence of being African
American and includes items such as racial slurs, being hassled by the
police, disrespectful treatment by sales clerks, false accusations by authority
ﬁgures, and exclusion from social activities. The alpha coefﬁcient for this
scale was .90 and .91 at waves III and IV, respectively. The two scales
(r=.50) were summed and averaged to create a composite measure of
Community Crime and Victimization. This composite measure was based
equally on the following scales: community crime and victimization in the
community. The measure of crime was assessed with a revised version
of the community deviance scale developed for the Project on Human
Development in Chicago Neighborhoods (PHDCN; Sampson, Rauden-
bush, and Earls, 1997). The 9-item measure is concerned with how of-
ten various criminal acts occur within the community. It includes behav-
iors such as ﬁghting with weapons, robbery, gang violence, and sexual
assault. In wave III, primary caregivers and target children completed
these items in reference to their residential neighborhood. At wave IV,
because almost half of the youth lived apart from their caregivers at least
part of the year, only target reports were used. The alpha coefﬁcient for
the target and primary caregiver (PC) reports was greater than .80 at
wave III; the correlation between the target and caregiver reports was
approximately .35. The alpha coefﬁcient for the target reports at wave IV
The measure of criminal victimization was based on target youth re-
sponses to 2 items. These items assessed the number of times that someone
in “the neighborhood surrounding where you lived for most of the past
12 months used violence, such as in a mugging, ﬁght, or sexual assault
against you?” and “against one of your friends.” Responses ranged from 0
(94 percent and 91 percent, respectively) to 8 (3 percent) and 12 (2 percent).
The alpha coefﬁcient for the 2-item composite scale was approximately .78
in both waves. Finally, the measures from waves III and IV were combined
572 SIMONS & BURT
and averaged to create the measures used in the model. The correlation
between the measures at waves III and IV was .23.
Community Collective Efﬁcacy. Following Sampson, Raudenbush, and
Earls (1997), the measure of collective efﬁcacy was formed by combining
a social-ties scale with a social-control scale. Community social ties were
assessed with a 9-item revised version of the Social Cohesion and Trust
Scale developed for the PHDCN (Sampson, Raudenbush, and Earls, 1997).
The items focus on the extent to which individuals in the area interact, trust,
and respect each other and share values. In wave III, youths and caregiver
reports were standardized and summed to create the social-ties scale. The
alpha coefﬁcient for the scale at wave III was greater than .80 for both
respondents, and the correlation between youth and caregiver reports was
roughly .35. The youth reports were used for the wave IV measure; alpha
reliability was .86.
The social-control scale consists of 6 items (also adapted from the
PHDCN; Sampson, Raudenbush, and Earls, 1997) that assess the extent to
which individuals in the neighborhood would take action if various types of
deviant behavior were evident. For example, items included the following:
“If teenagers got loud or disorderly, the adults in the area would tell them to
behave” and “the adults in the area would not hesitate to call the authorities
if a group of teens were ﬁghting with each other.” Reliability coefﬁcients for
the three measures (youths at waves III and IV, caregivers at wave III) were
all greater than .85. The waves III and IV scales were averaged to create a
measure of persistent exposure. The correlations between the two measures
Deviant Peers. At waves III and IV, the target youth reported their
afﬁliation with deviant peers using an instrument adapted from the National
Youth Survey (Elliot, Huizinga, and Menard, 1989). They were asked how
many of their close friends (1 =none, 2 =half, and 3 =all) had engaged in
each of the 15 deviant acts at wave IV (19 acts in wave III). The acts ranged
from relatively minor offenses, such as using tobacco, to more serious viola-
tions, such as stealing something worth more than $50, attacking someone
with a weapon with the idea of hurting them, and using crack or cocaine.
The alpha coefﬁcient was .83 and .87 for the scales at waves III and IV,
respectively. These two scales (r=.42) were standardized, summed, and
averaged to create the measure used in the present study.
Control Variables. In all the models we present, the sex of the respon-
dents is controlled. The variable sex is coded 1 for males and 0 for females.
In several models in which preliminary analyses support incorporating the
variable, the standardized age of the respondents is entered as a control.
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 573
Age is measured in months at the time of the wave IV interview. Additional
controls were considered, including household income; primary caregiver
race, age, and sex; and the presence of a second caregiver in the home. None
of these variables signiﬁcantly inﬂuenced the processes under consideration
and, thus, were not included in the models.
Structural equation modeling (SEM) was used to test our hypotheses
and offers several advantages to traditional econometric analyses. This
approach permits correction for bias in the estimation of substantive pa-
rameters as a result of measurement error. Moreover, it allows for the
estimation of substantive parameters simultaneously in the context of a
full-information model—a model corresponding to the causal ordering of
both the theoretical arguments and the longitudinal FACHS data. Perhaps
most important for the present study, SEM provides tests of signiﬁcance for
indirect (or mediation) effects, including speciﬁc paths (e.g., Bollen, 1989).
Analyses were conducted using the statistical program MPlus Version
en and Muth´
en, 2007) using maximum likelihood parameter es-
timates with standard errors and a mean-adjusted, chi-square statistic that
are robust to non-normality. Noting that we adjusted for item nonresponse
for respondents who were interviewed in at least waves I, II, and IV and
employed wave IV measures in lieu of waves III and IV averaged scales for
those not interviewed at wave III, we use the default of listwise deletion
in estimating the models. With one exception, the study variables were
generally symmetric and normally distributed. The lone exception is the
dependent variable—crime—which is an overdispersed count variable and
is estimated with a negative binomial equation model accommodating the
features of count outcome (Long, 1997).8
To assess goodness of ﬁt, Steiger’s root mean square error of approxima-
tion (RMSEA; Browne and Cudeck, 1993), the comparative ﬁt index (CFI;
Bentler, 1990), and the chi square divided by its degrees of freedom (ﬁt
ratio) are used. The CFI is truncated to the range of 0–1, and values close
to 1 indicate a good ﬁt (Bentler, 1990). A RMSEA smaller than .05 indicates
a close ﬁt, whereas a RMSEA between .05 and .08 suggests a reasonable ﬁt
(Browne and Cudeck, 1992).
8. The calculation of indirect effects and model ﬁt indices are based on a con-
tinuous model. The negative binomial estimator requires numerical integration,
and indirect effects cannot be calculated with model computations that require
numerical integration (Muth´
en and Muth´
en, 2007). The continuous model on
which the indirect effects and model ﬁt indices, including the R-squared for the
crime outcome, were based is presented in appendix B.
574 SIMONS & BURT
Table 1 presents the means, standard deviations, and correlation matrix
for the study variables. The mean number of criminal acts committed by the
study youths is 2.84 and ranges from 0 to 21 acts. Approximately 33 percent
(237) of the respondents did not commit any of the acts in wave IV; roughly
43 percent (305 respondents) committed one to four acts; 24 percent
(171 youths) committed ﬁve or more. Among the respondents who commit-
ted at least one act in the crime measure, almost half committed at least four
different acts, and more than 20 percent admitted to engaging in at least
seven different acts. Clearly, sufﬁcient involvement and individual variation
in criminal offending exists in the data.
Turning to the zero-order correlations, the pattern of associations is
largely as expected. Each of the social schemas has approximately a .30
correlation with crime (p<.001) as well as associations with each other
ranging from .30 to .36. As expected, the social-environmental variables are
signiﬁcantly related to the social schemas in the expected direction, with
one exception. Collective efﬁcacy is not related to hostile views.
Sex is not signiﬁcantly associated with most study variables; however,
as expected, being male is signiﬁcantly related to crime, tough reputation,
and low commitment to social conventions. Contrary to our expectations,
however, no signiﬁcant association was found between being male and
immediate gratiﬁcation. Additional analysis showed that being male is sig-
niﬁcantly related (raverages .11) to the risk-taking items in the immediate
gratiﬁcation scale but not to those concerned with patience and delayed
gratiﬁcation.9These results are consonant with those of prior studies show-
ing that the relationship between sex and self-control is explained by the
greater attraction to risk taking by males than by females (see Campbell,
We argued that persistent childhood and adolescent exposure to adverse
social-environmental conditions fosters criminogenic schemas. Thus, we
began our analyses by examining the extent to which changes in social
schemas from wave II to wave IV (mid-to-late adolescence) were explained
by changes in social environments. We expected that increased exposure
to coercive environments (i.e., crime and discrimination) augment each
9. These results are available upon request.
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 575
Table 1. Correlation Matrix for Study Variables (N=713)
1. CrimeW4 — 2.84 3.52
2. Deviant peersW3+W4 .38∗∗ —.01 .88
3. Immediate gratiﬁcationW4 .28∗∗ .34∗∗ —.00 .59
4. Hostile viewW4 .30∗∗ .34∗∗ .30∗—1.58 .59
5. Social conventionsW4 .33∗∗ .43∗∗ .30∗∗ .36∗∗ —−.07 .59
6. Community crimeW3+W4 .22∗∗ .35∗∗ .13∗∗ .24∗∗ .17∗∗ —−.07 .75
7. Collective efﬁcacyW3+W4 −.15∗∗ −.15∗∗ −.13∗∗ −.06 −.16∗∗ −.17∗∗ —2.21 .49
8. Supportive parentingW3+W4 −.20∗∗ −.39∗∗ −.36∗∗ −.24∗−.34∗∗ −.19∗∗ .18∗∗ —−.01 .87
9. DiscriminationW3+W4 .26∗∗ .34∗∗ .21∗∗ .23∗∗ .20∗∗ .20∗∗ −.05 −.12∗∗ —.51 .29
10. DelinquencyW1+W2 .27∗∗ .40∗∗ .20∗.19∗∗ .28∗∗ .18∗∗ −.06 −.26∗∗ .25∗∗ —2.17 2.40
11. Sex (1 =male) .13∗∗ .04 .01 .10∗.19∗∗ .01 .05 .02 .01 .17∗∗ —.44 .50
12. Age (standardized) .04 .08∗.01 −.03 .05 −.03 −.05 −.08∗.16∗∗ .14∗∗ −.01 — .00 1.00
ABBREVIATION: SD =standard deviation.
∗p≤.05; ∗∗p≤.001 (two-tailed).
576 SIMONS & BURT
Table 2. Results from SEMs Predicting the Change in
Immediate Hostile Social
GratiﬁcationW4 ViewsW4 ConventionsW4
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Exogenous Predictors γγγγγ γ
Outcome variableW2 .40∗∗ .42∗∗ .30∗∗ .30∗∗ .20∗∗ .18∗∗
Community crimeW4−W2 .01 .01 .18∗∗ .17∗∗ .17∗∗ .15∗∗
Collective efﬁcacyW4−W2 −.06†−.05 −.02 −.01 −.08∗−.08∗
Supportive parentingW4−W2 −.16∗∗ −.12∗∗ −.10∗∗ −.09∗∗ −.12∗∗ −.09∗∗
DiscriminationW4−W2 .19∗∗ .15∗∗ .18∗∗ .17∗∗ .08∗∗ .05
Sex (1 =male) .06†.06†.19 .19†
Age −.06†−.06 .06 .07†
Deviant peersW4−W2 .15∗∗ .04 .15∗∗
R2.22 .24 .17 .17 .16 .20
χ2(d.f.) 9.04(12) 9.11(14) 4.95(9) 6.25(11) 5.23(8) 11.35(13)
RMSEA/CFI .00/1.00 .00/1.00 .00/1.00 .00/1.00 .00/1.00 .00/1.00
NOTE: Reduced models presented; standard coefﬁcients shown.
ABBREVIATIONS:CFI=comparative ﬁt index; d.f. =degrees of freedom; RMSEA =root
mean square error of approximation.
†p<.08; ∗p<.05; ∗∗p<.01.
of the criminogenic schemas, whereas supportive environments (i.e., par-
enting and collective efﬁcacy) diminish belief in the schemas. Six SEMs
were estimated—two for each social schema. In the ﬁrst SEM, change in
the schemas from wave II to wave IV was predicted by the change in
the social-environmental variables. Change in the schemas was assessed
by incorporating the wave II schema as an exogenous predictor. In the
second model for each schema, increased afﬁliation with deviant peers
was added as an exogenous predictor to take into account the fact that
some of a social environment’s effect might be indirect through its impact
on peer associations. Table 2 presents the results.10 In general, the ﬁnd-
ings show that changes in social environments produce changes in each
of the social schemas. The model ﬁt statistics across the table indicate
that the models ﬁt the data well. Across the six models, the chi-square
statistic is insigniﬁcant, indicating that the model ﬁts the data well. The
RMSEA statistic for all models is ≤.01. The CFI statistic is 1.00 in all cases
Turning to the parameter estimates in table 2, immediate gratiﬁcation
shows the most stability across the models (γ=.40) followed by hostile
10. Reduced models are presented in table 2. Chi-square differences between the
fully recursive models and the models presented were not signiﬁcant. Correlations
between the exogenous variables are not listed for brevity.
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 577
view (γ=.30) and social conventions (γ=.20). Increased exposure to
community crime and victimization is associated with signiﬁcant increases
in hostile view and in lower commitment to social conventions, with and
without changes in deviant peers in the model. Community collective efﬁ-
cacy is associated with a signiﬁcant decrease in low commitment to social
conventions (γ=−.08) and a marginally signiﬁcant decrease in immediate
gratiﬁcation (γ=−.06). The inﬂuence of collective efﬁcacy on these two
schemas is only slightly altered by the inclusion of deviant peers, suggesting
that its inﬂuence is not indirect through deviant peer afﬁliation. Supportive
parenting signiﬁcantly decreases each of the schemas, with the strongest
effects on immediate gratiﬁcation; path coefﬁcients ranged from −.12 to
−.16 (p<.001). Experiences with discrimination produce statistically and
substantively signiﬁcant changes in all schemas, with the strongest effects
on immediate gratiﬁcation and hostile views. As is shown comparing the
ﬁrst and second models for each schema, some effects of changes in the
contexts are indirect through changes in deviant peer afﬁliations, which
are signiﬁcantly related to changes in immediate gratiﬁcation and social
conventions. Sex is not associated with changes in immediate gratiﬁcation,
but being male is signiﬁcantly associated with increased hostile view of
relationships and with increased rejection of social conventions. Finally,
being older is associated with lower hostile views and increased rejection
of social conventions, but these coefﬁcients are only marginally signiﬁcant.
Overall, the changes in the social schemas produced by changes in
social-environmental conditions are largely consistent with our arguments.
Approximately 20 percent of the variance in immediate gratiﬁcation, hostile
views, and commitment to social conventions is explained in the models.
Even with the relative stability of both the schemas and the contexts,
changes in exposure to deleterious and supportive conditions alter social
We have argued that the three schemas are interrelated, mutually rein-
forcing cognitive frameworks that combine to form a knowledge structure
that inﬂuences crime through deﬁnitions of the situation. This argument
implies that the schemas should come together as a higher order latent
construct. We estimated a conﬁrmatory factor analysis to test this idea.
Following convention, we set the metric for the latent construct by ﬁxing
the factor loading of immediate gratiﬁcation to 1. Multiple group analy-
ses indicated that the factor loadings were invariant by sex.11 Although
11. We tested for measurement invariance (invariance of intercepts and factor load-
ings) by sex using multiple group analyses and the chi-square difference test
in MPlus. The chi-square difference value was marginally signiﬁcant (p=.051)
because of different thresholds for hostile view by sex.
578 SIMONS & BURT
Figure 2. Reduced Structural Equation Model (N=713):
Negative Binomial Model Estimator Predicting
NOTE: Standardized values displayed; age controlled but only related to exogenous con-
structs and thus not shown for clarity. R2in parentheses below endogenous constructs.
Event rate ratio from NB model in brackets.
it is not a deﬁnitive test, the results of the conﬁrmatory factor analysis
(CFA) provide support for our argument. The factor loadings are .61
for immediate gratiﬁcation, .68 for hostile views, and .66 for social con-
ventions, suggesting that these constructs combine to comprise a latent
Next, we estimated a structural model to test the central feature of our
proposed theoretical model that this latent knowledge structure construct
is associated with crime (i.e., it is criminogenic) and that it mediates much
of the effects of social environments on crime. First, we estimated a model
that included all possible pathways between the constructs. After the initial
estimation of the model, nonsigniﬁcant paths (t<1.5), which were not part
of the hypothesized model, and residual correlations were eliminated to
improve model ﬁt. All direct paths between the ecological contexts and
crime as well as the direct path from earlier delinquency to the outcome
were removed in this step, as all had tvalues less than 1.5, except for
discrimination, which continued to have a direct effect. Figure 2 displays
the results of the reduced model for the total sample. Although model ﬁt
indices are not available for the count model, the model ﬁt indices for the
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 579
continuous model presented in appendix B indicate a good ﬁt of the model
to the data.12
The results in ﬁgure 2 show that the social-environmental factors inﬂu-
ence the latent knowledge structure variable as predicted.13 Community
crime and discrimination have positive effects on the criminogenic schema
of .07 and .12, respectively. Supportive parenting and collective efﬁcacy,
however, are negatively associated with this knowledge structure (γ=
−.18 and γ=−.09, respectively). Moreover, these social-environmental
variables, with the exception of collective efﬁcacy, which does not seem
to inﬂuence deviant peer afﬁliations, are signiﬁcantly related to deviant
peers in the same manner. That is, community crime and discrimination
are associated with an increase, whereas quality of parenting is associated
with a decrease in afﬁliation with deviant peers. The deviant peers variable,
in turn, shows a strong association with knowledge structure (γ=.49). This
pattern of ﬁndings is consistent with our argument that afﬁliation with de-
viant peers fosters a criminogenic knowledge structure and that, in addition
to their direct effects, the other social-environmental variables inﬂuence
this knowledge structure indirectly through their impact on afﬁliation with
deviant peers. The ﬁrst half of table 3 displays the total effects of the social-
environmental variables on the knowledge structure as well as the speciﬁc
indirect paths through deviant peers. Delta-method standard errors for sig-
niﬁcance testing of the indirect effects were computed in Mplus.14,15 Finally,
as shown in ﬁgure 2, the effect of deviant peers on crime is completely
mediated by the knowledge structure.16
12. Chi-square and other ﬁt indices are not available in count models in which means,
variances, and covariances are not sufﬁcient statistics for model estimation. The
model ﬁt indices from the continuous model (see appendix B) suggest a good ﬁt
of the model to the data; the RMSEA statistic is .039, the TLI is .97, and the CFI
is greater than .97. The CFI is truncated to the range of 0–1, and values close to 1
indicate a good ﬁt (Bentler, 1990). An RMSEA smaller than .05 indicates a close
ﬁt, whereas an RMSEA between .05 and .08 suggests a reasonable ﬁt (Browne and
13. Notably, we included age as a predictor in the model, but given that age’s only
signiﬁcant inﬂuences were correlations with the other exogenous constructs, we
omitted it from the displayed ﬁgure for clarity.
14. MPlus has the following options for calculating the standard errors for indirect
effects: the delta and bootstrapping methods. We estimated standard errors using
both methods, and the results were analogous. The presented signiﬁcance levels
are based on the results from the default delta method.
15. Recall that these estimates are based on the reduced continuous model presented
in appendix B.
16. The chi-square difference between the models with and without (path constrained
to zero) deviant peers is .058 (p=.8213).
580 SIMONS & BURT
Table 3. Indirect Effects (N=713)
Knowledge Structure Crime
Peers to Total CKS to Peers to CKS
Predictors Total CKSaIndirect Crimebto Crimec
DelinquencyW1+W2 .248∗∗∗ .128∗∗∗ .135∗∗∗ .065∗∗ .070∗∗∗
Community crimeW3+W4 .193∗∗∗ .106∗∗∗ .105∗∗∗ .047∗.058∗∗∗
Collective efﬁcacyW3+W4 −.130∗∗∗ −.026 −.071∗∗ −.057∗∗ −.014
Supportive parentingW3+W4 −.288∗∗∗ −.080∗∗∗ −.157∗∗∗ −.114∗∗∗ −.043∗∗∗
DiscriminationW3+W4 .276∗∗∗ .099∗∗∗ .150∗∗∗ .097∗∗∗ .054∗∗∗
Deviant peersW3+W4 .252∗∗∗ .252∗∗∗
Sex (1 =male) .106∗∗∗ .106∗∗∗
NOTES: These indirect effects were calculated from a continuous SEM using delta method
ABBREVIATION:CKS=crime knowledge structure.
aThis column displays the effects of each predictor to peers to the CKS.
bThis column displays the effects of each predictor to CKS to crime.
cThis column displays the effects of each predictor from the path through deviant peers to
∗p<.05; ∗∗p<.01; ∗∗∗p<.001.
Among the controls for sex and prior delinquency, both being male
and prior delinquency are positively related to the criminogenic knowl-
edge structure directly (.15 and .07, p<.001, respectively) and to de-
viant peers. Importantly, both of these variables are fully mediated by
knowledge structure. In other words, sex/gender inﬂuences on crime are
explained by the criminogenic knowledge structure; likewise with previous
Finally, the path between knowledge structure and delinquency is signif-
icant and large (β=.95, p<.001). A 1 standard deviation increase in the
knowledge structure increases the expected count of crime by 159 percent
(calculated as follows: [100 ×(eβ– 1)]). Moreover, the latent knowledge
structure construct fully mediates all other predictors in the model with the
exception of racial discrimination. Discrimination has a signiﬁcant direct
effect on crime (γ=.13) in addition to its larger indirect effect through
knowledge structure. Forty-seven percent of the variance in knowledge
structure is explained by the ecological context, sex, previous delinquency,
and deviant peer afﬁliation, and the continuous model explains 31 percent
of the variance in crime.
17. The chi-square difference between the model including the path from sex to crime
and the model in which the path is constrained to be zero is .004 (p=.945). The
chi-square difference between the models with and without (path constrained to
zero) the direct path from delinquency to crime was .426 (p=.514).
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 581
The right side of table 3 displays the indirect effects of the social-
environmental factors on crime along with their signiﬁcance. All social-
environmental variables have signiﬁcant (p<.01) indirect effects on
crime. The standardized indirect effects range from an absolute value
high of .252 for deviant peers and −.157 for quality of parenting to
−.071 for collective efﬁcacy. Turning to speciﬁc paths, the two ways
that social-environmental factors can inﬂuence crime is through crim-
inogenic knowledge structure to crime or through deviant peers to
criminogenic knowledge structure to crime. All indirect effects through
these two pathways are signiﬁcant, except for collective efﬁcacy through
Although not part of our hypotheses, it is worth noting that prior
delinquency does not have a direct inﬂuence on later crime; its effect
is indirect through deviant peers and criminogenic knowledge structure.
As shown in table 3, both of these indirect effects are signiﬁcant. This
ﬁnding indicates that the stability of antisocial behavior over time is
explained by the fact that early involvement enhances commitment to
a criminogenic knowledge structure both directly and indirectly by in-
creasing afﬁliation with deviant peers. The effect of sex on crime is also
fully mediated by the knowledge structure. The indirect effects, shown
at the bottom of table 3, are signiﬁcant and positive, suggesting that sex
differences in crime are accounted for by the criminogenic knowledge
Criminal offenders, like conforming individuals, tend to view their
actions as legitimate and acceptable given prevailing circumstances
(Baumeister, 1997; Giordano, Cernkovich, and Rudolph, 2002; Katz, 1988).
The motives for criminal acts usually involve elements of revenge, teaching
someone a lesson, impressing peers or bystanders, or the opportunistic
pursuit of material rewards (Black, 1998; Katz, 1988). Usually little empathy
or concern is involved for the fair treatment of those negatively affected by
these acts. We posited that these perceptions and behaviors are fostered
by the combination of the following schemas: a hostile view of relation-
ships, a focus on immediate rewards, and low commitment to conventional
We argued that this cognitive framework, which shapes situational def-
initions and resulting actions, develops in response to adverse social-
environmental conditions that past research has linked to crime. Social
environments that have been shown to encourage crime (e.g., neighbor-
hood crime and discrimination) tend to be unpredictable and exploitive
582 SIMONS & BURT
as well as low on trust, reciprocity, and support, whereas those that have
been shown to discourage crime (e.g., authoritative parenting and collective
efﬁcacy) tend to be predictable and supportive, as well as high on trust and
reciprocity. The two types of milieus teach different lessons regarding the
nature of relationships, the value of delayed gratiﬁcation, and the authority
of social conventions. Consequently, persistent exposure to such antagonis-
tic social circumstances and lack of exposure to these positive conditions
increases the chances of developing social schemas involving a hostile view
of relationships, a focus on immediate rewards, and cynicism regarding
conventional conduct norms.
We posited that these three elements represent an interconnected set of
learned, mutually reinforcing principles that combine to form a knowledge
structure conducive to crime. We hypothesized that this cognitive structure
fosters situational deﬁnitions that lead to actions that are aggressive, op-
portunistic, and sometimes criminal. Finally, we argued that females, given
their greater fear and caution, would be less likely than males to develop
criminogenic knowledge structures, and that this difference largely accounts
for sex differences in criminal behavior.
Our ﬁndings provided preliminary support for this perspective. First,
social-environmental factors emphasized by other criminological theories
predicted changes in the three schemas. Speciﬁcally, community crime,
deviant peers, and discrimination increased, whereas collective efﬁcacy and
supportive parenting decreased belief in the schemas. Second, as predicted,
the schemas were intercorrelated and combined to form a latent construct.
Consistent with the contention that this construct represented a crimino-
genic knowledge structure, it was a strong predictor of change in crime.
Furthermore, our ﬁndings indicated that in large measure the effect of the
various social-environmental conditions on offending is indirect through
the criminogenic knowledge structure. With one exception—to be discussed
subsequently—the effect of these adverse conditions on change in crime
was mediated completely by the latent variable criminogenic knowledge
structure. Finally, we found that controlling for a criminogenic knowledge
structure eliminated the association between sex/gender and crime. Our
results indicated that this effect is largely a consequence of males being
more committed to a hostile view of relationships and less committed to
social conventions than females.
In contrast to the effects of the other social factors, whose effects on
crime were fully explained by the criminogenic knowledge structure, racial
discrimination had a direct effect in addition to its indirect effect. Although
this result was not expected, it is not inexplicable. First, unlike the other
examined social factors, racial discrimination is experienced exclusively by
racial minorities. Thus, it might be the case that racial discrimination affects
social behaviors such as crime through racially speciﬁc factors. Scholars
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 583
have argued that the unique position of African Americans shapes the
development of a distinctive worldview (e.g., Unnever and Gabbindon,
2011). Thus, it is possible that unique racial schemas or factors are needed
to explicate the link fully between race and racism and offending. It also
might be the case that ethnic–racial factors condition the inﬂuence of racial
discrimination on cognitions and behavior. For example, recent research
has highlighted the importance of ethnic–racial socialization—a class of
protective practices used to promote minority children’s pride and esteem
in their racial group and to provide children with competencies to deal
with racial stratiﬁcation—in explaining variations in responses to racial
discrimination (Neblett et al., 2008). Research indicates that ethnic–racial
socialization inﬂuences adolescents’ criminal responses to discrimination
(Burt, 2009). Thus, although most effects of racial discrimination are in-
direct through individuals’ knowledge structures, the remaining effect on
offending might be accounted for by various race- or ethnic-speciﬁc pro-
cesses or by mechanisms that affect situational deﬁnitions and thus in situ
Alternatively, it also might be the case that a general factor accounts
for the remaining direct effect of discrimination. As we noted, using the
example of someone walking in on his or her spouse in coitus with a
family friend, some situational factors might compel criminal behavior net
of individuals’ criminogenic knowledge structures. In some circumstances,
racial discrimination might be so frustrating, anger-provoking, or even mad-
dening that it could foster an antisocial reaction regardless of the victim’s
knowledge structure. A particularly severe experience with discrimination
could be the precipitating factor, or it could be a triggering event that is
no more injurious than those that have come before but served as the
last straw. Although additional research is needed to explicate the direct
effect of racial discrimination, the aforementioned explanations are not
inconsistent with the proposed model.
Although our ﬁndings largely conﬁrmed the study hypotheses and pro-
vided preliminary support for our theoretical arguments, our study is not
without limitations. Perhaps most importantly, because of the absence of
measures, we could not test the idea that situational deﬁnitions mediate the
relationship between criminogenic knowledge structure and perpetration
of criminal behavior. Additionally, the relative length of intervals between
waves, given the ages of the youth in the sample, precluded our ability to
provide a rigid test of the causal order of our proposed model. Additional
tests are needed that subject the theorized causal sequencing to more
Another limitation is the homogeneity of our sample; all respondents in
our sample were African American. Use of an all African American sample
had the beneﬁt of allowing us to incorporate racial discrimination into the
584 SIMONS & BURT
model—a factor that recent research indicates is an important predictor of
crime among African Americans (e.g., Simons et al., 2006; Unnever et al.,
2009). Although we cannot think of any reason why our results would be
speciﬁc to African Americans, our ﬁndings clearly need to be replicated
with more diverse samples.
Although important elements remain to be tested, the proffered frame-
work has the potential to integrate a wide array of extant criminological
ﬁndings and constructs into a coherent theoretical perspective. It spec-
iﬁes a temporal linkage between social-environmental factors identiﬁed
by various control, strain, and cultural deviance perspectives and the de-
velopment of a set of social schemas posited to foster situational deﬁni-
tions conducive to crime. These schemas build on Dodge’s (1986; Dodge,
Bates, and Pettit, 1990) concept of hostile attribution bias, Anderson’s
(1999) research on street code, and Gottfredson and Hirschi’s (1990) work
on self-control, as well as on Akers’s (1998) and Hirschi’s (1969) em-
phasis on moral beliefs and conduct norms. We argue that what unites
these seemingly disparate community, family, and peer variables is the
common set of lessons regarding the nature of relationships, the value
of delayed gratiﬁcation, and the authority of conduct norms inherent in
these social interactions. These cognitive constructs were reconceptual-
ized as interlinked schemas that operate in concert to foster situational
deﬁnitions favorable to crime. The result is a broader, more compre-
hensive model than that achieved in most prior attempts at theoretical
An advantage of this social-schematic theory is that it can be expanded
easily to accommodate additional social environments and experiences that
have been shown to increase the probability of criminal behavior. Watching
violent television (Bushman and Huesmann, 2000; Huesmann et al., 2003),
playing violent video games (Anderson and Bushman, 2001; Anderson
et al., 2010), incarceration (Laub and Sampson, 2003), and other negative
social relations (Agnew, 2006), for example, have been linked to increases
in offending. Our social-schematic perspective would predict that in large
measure these variables have their effect because they teach lessons about
relationships and about how the world works, thereby promoting a hostile
view of relationships, a focus on immediate rewards, and low commitment
to conventional conduct norms.
Research also has identiﬁed social factors that reduce involvement in
criminal and deviant behavior. Marriage, employment, and military service,
for example, have been linked to a reduction in antisocial behavior (Laub
and Sampson, 2003; Sampson and Laub, 1993). We expect that these factors
reduce offending because they foster a benign, predictable view of social
life, thereby diminishing belief in the criminogenic knowledge structure.
Support for this idea comes from studies showing that individuals with a
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 585
distrustful view of relationships tend to develop a more positive relation-
ship schema after marrying a caring and supportive individual (Hazan and
Hutt, 1990). Similarly, afﬁliation with conventional peers increases self-
control (Burt, Simons, and Simons, 2006), whereas improved parenting
has been linked both to increased self-control (Burt, Simons, and Simons,
2006; Hay and Forrest, 2006) and to decreased commitment to a hostile
view of relationships (Simons et al., 2006). Such ﬁndings highlight the
malleability of social schemas and point to various prosocial interventions
to reduce offending by changing cognitive structures. Indeed, already evi-
dence has been found that supports the efﬁcacy of this approach. Several
studies, for example, have shown that it is possible to enhance sensitivity
to others and delayed gratiﬁcation (e.g., Reid, Trout, and Schartz, 2005;
Strayhorn, 2002). In addition, at least ﬁve intervention experiments have
shown that a hostile view of relationships can be altered and that this change
decreases deviant, aggressive behavior (see Dodge, 2006).
Although our ﬁndings indicate that the three schemas included in the
present study are important elements of the criminogenic knowledge struc-
ture, subsequent studies might demonstrate that other factors need to
be incorporated. We do not claim that this model is fully exhaustive.
Human beings are extraordinarily complex creatures, and their percep-
tions and actions in any situation are inﬂuenced by a wide array of as-
sumptions and dispositions. That said, we do believe that these three
social schemas represent the basic components of the criminogenic knowl-
edge structure. And, in our view, the criteria for adding another element
consists of demonstrating that the new factor is interconnected with the
three schemas currently in the model, is rooted in the same existen-
tial conditions as these schemas, and signiﬁcantly enhances the predic-
tion of crime when the criminogenic knowledge structure is expanded to
In conclusion, we believe that the social-schematic framework we have
presented will provide a fresh way of thinking about theoretical inte-
gration. During the past 30 years, numerous exciting theoretical devel-
opments have been made in the ﬁeld of criminology (see Laub, 2004).
Unfortunately, although each of the dominant theories has abundant em-
pirical support, none explains more than a small amount of the variance
in criminal behavior. What is required, in our view, is an approach that
facilitates combining the important constructs from these various theories
into a more comprehensive perspective. Our ﬁndings suggest that such
integration might be accomplished by focusing on the lessons communi-
cated by recurrent social circumstances and the social schemas that result
from those lessons. This approach provides a framework for combining
concepts central to strain, cultural, control, and social-learning explanations
586 SIMONS & BURT
Agnew, Robert A. 2006. Pressured into Crime: An Overview of Strain
Theory. Los Angeles, CA: Roxbury.
Ainslie, George. 2000. Breakdown of Will. New York: Cambridge Univer-
Akers, Ronald L. 1985. Deviant Behavior: A Social Learning Approach.
Belmont, CA: Wadsworth.
Akers, Ronald L. 1998. Social Learning and Social Structure: A General
Theory of Crime and Deviance. Boston, MA: Northeastern University
Akers, Ronald L., and Christine S. Sellers. 2009. Criminological Theories:
Introduction, Evaluation, and Application, 5th ed. New York: Oxford
American Psychiatric Association. 1994. Diagnostic and Statistical Manual
of Mental Disorders. Washington, DC: American Psychiatric Associa-
Anderson, Craig A., and Brad J. Bushman. 2001. Effects of violent video
games on aggressive behavior, aggressive cognition, aggressive affect,
physiological arousal, and prosocial behavior: A meta-analytic review
of the scientiﬁc literature. Psychological Science 12:353–9.
Anderson, Craig A., Adiko Shibuya, Ihori Nobuko, Edward Swing, Brad J.
Bushman, Akira Sakamoto, Hanna R. Rothstein, and Maniba Saleem.
2010. Violent video game effects on aggression, empathy, prosocial
behavior in Eastern and Western countries: A meta-analytic review.
Psychological Bulletin 136:151–73.
Anderson, Elijah. 1990. Streetwise: Race, Class, and Change in an Urban
Neighborhood. Chicago, IL: University of Chicago Press.
Anderson, Elijah. 1999. Code of the Street: Decency, Violence, and the Moral
Life of the Inner City. New York: Norton.
Archer, John. 2004. Sex differences in aggression in real-world settings: A
meta-analytic review. Review of General Psychology 8:291–322.
Bailey, Christopher A., and Jamie M. Ostrov. 2007. Differentiating forms
and functions of aggression in emerging adults: Associations with hos-
tile attribution biases and normative beliefs. Journal of Youth and Ado-
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 587
Baldwin, Mark W. 1992. Relational schemas and the processing of social
information. Psychological Bulletin 112:461–84.
Bandura, Albert, Gian V. Capara, Claudio Barbaranelli, and Concetta
Pastorelli. 1996. Mechanisms of moral disengagement: Integrating so-
cial information processing and moral domain models. Child Develop-
Baumeister, Roy F. 1997. Evil: Inside Human Violence and Cruelty.New
Bentler, Peter M. 1990. Comparative ﬁt indexes in structural models. Psy-
chological Bulletin 107:238–46.
Berreby, David. 2005. Us and Them: Understanding Your Tribal Mind.
Boston, MA: Little, Brown.
orkqvist, Kaj, Karin ¨
Osterman, and Kirsti M. J. Lagerspetz. 1994. Sex
differences in covert aggression among adults. Aggressive Behavior 20:
Black, Donald. 1998. The Social Structure of Right and Wrong.NewYork:
Bollen, Kenneth A. 1989. Structural Equations with Latent Variables.New
Bourdieu, Pierre. 1984. Distinction: A Social Critique of the Judgment of
Taste. Cambridge, MA: Harvard University Press.
Bourdieu, Pierre. 1990. The Logic of Practice. Stanford, CA: Stanford
Bourdieu, Pierre. 1998. Practical Reason: On the Theory of Action.
Cambridge, U.K.: Polity Press.
Bowlby, John. 1982. Attachment and Loss: Vol. 1. Attachment, 2nd ed. New
York: Basic Books.
Brezina, Timothy, Erdal Tikan, and Volkan Topalli. 2009. Might not be a
tomorrow: A multi-methods approach to anticipated early death and
youth crime. Criminology 47:1091–130.
Browne, Michael W., and Robert Cudeck. 1993. Alternative ways of assess-
ing model ﬁt. In Testing Structural Equation Models, eds. Kenneth A.
Bollen and J. Scott Long. Newbury Park, CA: Sage.
588 SIMONS & BURT
Burks, Virginia Salzer, Robert D. Laird, Kenneth A. Dodge, Gregory S.
Pettit, and John E. Bates. 1999. Knowledge structures, social informa-
tion processing, and children’s aggressive behavior. Social Development
Burt, Callie Harbin. 2009. Discrimination and deviance: Racial socializa-
tion matters. PhD Dissertation, Department of Sociology, University of
Georgia, Athens, GA.
Burt, Callie Harbin, Ronald L. Simons, and Leslie G. Simons. 2006. A
longitudinal test of the effects of parenting and the stability of self-
control: Negative evidence for the general theory of crime. Criminology
Burton, Velmer S., Francis T. Cullen, David Evans, Leanne Fiftal Alarid,
and R. Gregory Dunaway. 1998. Gender, self-control, and crime. Jour-
nal of Research in Crime and Delinquency 35:123–47.
Bushman, Brad J., and L. Rowell Huesmann. 2000. Effects of televised
violence on aggression. In Handbook of Children and the Media, eds.
Dorothy Singer and Jerome Singer. Thousand Oaks, CA: Sage.
Byrnes, James P., David C. Miller, and William D. Schafer. 1999. Gen-
der differences in risk taking: A meta-analysis. Psychological Bulletin
Caldwell, Roslyn M., Richard P. Wiebe, and H. Harrington Cleveland.
2006. The inﬂuence of future certainty and contextual factors on delin-
quent behavior and school adjustment among African American ado-
lescents. Journal of Youth and Adolescence 35:591–602.
Callan, Mitchell J., N. Will Snead, and James M. Olson. 2009. Foregoing
the labor for the fruits: The effects of just world threat on the desire
for immediate monetary rewards. Journal of Experimental Psychology
Campbell, Anne. 1999. Staying alive: An evolutionary approach to women’s
intra-sexual aggression. Behavioral Brain Science 22:203–52.
Campbell, Anne. 2006. Sex differences in direct aggression: What are the
psychological mediators? Aggression and Violent Behavior 11:237–64.
Campbell, Anne, Steven Muncer, and Daniel Bibel. 2001. Women and
crime: An evolutionary approach. Aggression and Violent Behavior
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 589
Cassidy, Jude, and Phillip R. Shaver. 2008. Handbook of Attachment: The-
ory, Research, and Clinical Applications. New York: Guilford Press.
Cloward, Richard A., and Lloyd E. Ohlin. 1960. Delinquency and Opportu-
nity: A Theory of Delinquent Gangs. New York: Free Press.
Conger, Rand D., and Glen H. Elder. 1994. Families in Troubled Times:
Adaptation to Change in Rural America. New York: Aldine.
Crick, Nicki R., and Kenneth A. Dodge. 1994. A review and reformulation
of social information-processing mechanisms in children’s social adjust-
ment. Psychological Bulletin 115:74–101.
Daly, Martin, and Margo Wilson. 2001. Income inequality and homicide
rates in Canada and the United States. Canadian Journal of Criminol-
de Waal, Frans. 2008. Putting the altruism back into altruism: The evolution
of empathy. Annual Review of Psychology 59:279–300.
Dodge, Kenneth A. 1980. Social cognition and children’s aggressive behav-
ior. Child Development 51:162–70.
Dodge, Kenneth A. 1986. A social information processing model of social
competence in children. In Minnesota Symposium on Child Psychology,
ed. M. Perlmutter. Hillsdale, NJ: Lawrence Erlbaum.
Dodge, Kenneth A. 2006. Translational science in action: Hostile attribu-
tional style and the development of aggressive problems. Development
and Psychopathology 18:791–814.
Dodge, Kenneth A., John E. Bates, and Gregory S. Pettit. 1990. Mecha-
nisms in the cycle of violence. Science 250:1678–83.
Dodge, Kenneth A., Robert Laird, John E. Lochman, and Arnoldo Zelli.
2002. Multidimensional latent-construct analysis of children’s social in-
formation processing patterns: Correlations with aggressive behavior
problems. Psychological Assessment 14:60–73.
Dodge, Kenneth A., and Joseph P. Newman. 1981. Biased decision-making
processes in aggressive boys. Journal of Abnormal Psychology 90:
Dodge, Kenneth A., and Greg S. Pettit. 2003. A biopsychosocial model of
the development of chronic conduct problems in adolescence. Develop-
mental Psychology 39:349–71.
590 SIMONS & BURT
DuRant, Robert H., Chris Cadenhead, Robert A. Pendergrast, Greg
Slavens, and Charles W. Linder. 1994. Factors associated with the use
of violence among urban black adolescents. American Journal of Public
Elliot, Delbert S., David Huizinga, and Scott Menard. 1989. Multiple Prob-
lem Youth: Delinquency, Substance Abuse, and Mental Health Prob-
lems. New York: Springer.
Epps, James and Phillip C. Kendall. 1995. Hostile attributional bias in
adults. Cognitive Therapy and Research 19:159–78.
Eysenck, Sybil B. G., and Hans J. Eysenck. 1977. The place of impulsiveness
and venturesomeness in a dimensional system of personality descrip-
tion. British Journal of Social and Clinical Psychology 16:57–68.
Furman, Wyndol, L. Jones, Duane Buhrmester, and Terry Adler.
1989. Children’s, parent’s, and observers’ perspectives on sibling
relationships. In Sibling Interaction Across Cultures: Theoretical and
Methodological Issues, ed. Patricia G. Zukow. New York: Springer-
Gibbons, Frederich X., Meg Gerrard, Michael J. Cleveland, Thomas Ashby
Wills, and Gene Brody. 2004. Perceived discrimination and substance
use in African American parents and their children: A panel study.
Journal of Personality and Social Psychology 86:517–29.
Gilligan, James. 2001. Preventing Violence. New York: Thames & Hudson.
Giordano, Peggy C., Stephen A. Cernkovich, and Jennifer L. Rudolph.
2002. Gender, crime, and desistance: Toward a theory of cognitive
transformation. American Journal of Sociology 107:990–1064.
Gottfredson, Michael R., and Travis Hirschi. 1990. A General Theory of
Crime. Palo Alto, CA: Stanford University Press.
Granic, Isabela, and Thomas J. Dishion. 2003. Deviant talk in adolescent
friendships: A step toward measuring a pathogenic attractor process.
Social Development 12:314–34.
Hauser, Marc. 2006. Moral Minds: How Nature Designed Our Universal
Sense of Right and Wrong. New York: HarperCollins.
Hay, Carter. 2001. Parenting, self-control, and delinquency: A test of self-
control theory. Criminology 39:707–36.
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 591
Hay, Carter and Walter Forrest. 2006. The development of self-control:
Examining self-control theory’s stability thesis. Criminology 44:739–74.
Hazan, Cindy, and M. J. Hutt. 1990. Continuity and change in inner working
models of attachment. Paper presented at the 5th International Confer-
ence on Personal Relationships, Oxford, U.K.
Hersch, Joni. 1997. Smoking, seat belts and other risky consumer decisions:
Differences by gender and race. Managerial and Decision Economics
Hill, Kim, and Magdalena Hurtado. 1996. Ache Life History: The Ecology
and Demography of a Foraging People. New York: Aldine de Gruyter.
Hill, Elizabeth M., Lisa T. Ross, and Bobbi S. Low. 1997. The role of future
unpredictability in human risk-taking. Human Nature 8:287–325.
Hirschi, Travis. 1969. Causes of Delinquency. Berkeley: University of Cali-
Huesmann, L. Rowell, Jessica Moise-Titus, Cheryl-Lynn Podolski, and
Leonard D. Eron. 2003. Longitudinal relations between children’s expo-
sure to TV violence and their aggressive and violent behavior in young
adulthood: 1977–1992. Developmental Psychology 39:201–21.
Jacobs, Bruce, and Richard Wright. 2006. Street Justice: Retaliation in the
Criminal Underworld. New York: Cambridge University Press.
Jencks, Christopher, and Susan E. Mayer. 1990. The social consequences of
growing up in a poor neighborhood. In Adolescents at Risk: Medical and
Social Perspectives, eds. David E. Rogers and Eli Ginzberg. Boulder,
CO: Westview Press.
Katz, Jack. 1988. Seductions of Crime. New York: Basic Books.
Keane, Carl, Paul S. Maxim, and James J. Teevan. 1993. Drinking and
driving, self-control, and gender: Testing a general theory of crime.
Journal of Research in Crime and Delinquency 30:30–46.
Kendall, Phillip C., and Lance E. Wilcox. 1979. Self-control in children:
Development of a rating scale. Journal of Consulting and Clinical Psy-
Kubrin, Charis E., and Ronald Weitzer. 2003. Retaliatory homicide: Con-
centrated disadvantage and neighborhood culture. Social Problems
592 SIMONS & BURT
LaGrange, Teresa C., and Robert A. Silverman. 1999. Low self-control and
opportunity: Testing the general theory of crime as an explanation for
gender differences in delinquency. Criminology 37:41–72.
Landrine, Hope, and Elizabeth A. Klonoff. 1996. The schedule of racist
events: A measure of racial discrimination and a study of its negative
physical and mental consequences. Journal of Black Psychology 22:
Laub, John H. 2004. The life course of criminology in the United States: The
American Society of Criminology 2003 Presidential Address. Criminol-
Laub, John H., and Robert J. Sampson. 2003. Shared Beginnings, Divergent
Lives: Delinquent Boys to Age 70. Cambridge, MA: Harvard University
Long, J. Scott. 1997. Regression Models for Categorical and Limited Depen-
dent Variables. Thousand Oaks, CA: Sage.
Meisenhelder, Thomas. 2006. From character to habitus in sociology. Social
Science Journal 43:55–66.
Messerschmidt, James W. 1993. Masculinities and Crime. Lanham, MD:
Rowman & Littleﬁeld.
Mikulincer, Mario, and Phillip R. Shaver. 2001. Attachment theory and
intergroup bias: Evidence that priming the secure base schema attenu-
ates negative reactions to out-groups. Journal of Personality and Social
Mischel, Walter, and Yuici Shoda. 1995. A cognitive-affective system the-
ory of personality: Reconceptualizing situations, dispositions, dynam-
ics, and invariance in personality structure. Psychological Review 102:
Mofﬁtt, Terrie E. 1997. Neuropsychology, antisocial behavior, and neigh-
borhood context. In Violence and Childhood in the Inner City, ed. Joan
McCord. Cambridge, U.K.: Cambridge University Press.
en, Linda K., and Bengt O. Muth´
en. 2007. Mplus: Statistical Analysis
with Latent Variables. Los Angeles, CA: Muth´
en & Muth´
Nakhaie, M. Reza, Robert A. Silverman, and Teresa C. LaGrange. 2000.
Self-control and social control: An examination of gender, ethnicity,
class, and delinquency. Canadian Journal of Sociology 25:35–59.
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 593
Neblett, Enrique W., Jr., Rhonda L. White, Kahlil Ford, Cheri L. Philip,
Hoa X. Nguyen, and Robert M. Sellers. 2008. Patterns of racial so-
cialization and psychological adjustment: Can parental communications
about race reduce the impact of racial discrimination. Journal of Re-
search on Adolescence 18:477–515.
Orobio de Castro, Jan W. Bram, Veerman Willem Koops, Joop D. Bosch,
and Heidi J. Monshouwer. 2002. Hostile attribution of intent and ag-
gressive behavior: A meta analysis. Child Development 73:916–34.
Patterson, Gerald R., John B. Reid, and Thomas J. Dishion. 1992. Antisocial
Boys. Eugene, OR: Castelia.
Pratt, Travis C., and Francis T. Cullen. 2000. The empirical status of
Gottfredson and Hirschi’s general theory of crime: A meta-analysis.
Pratt, Travis C., Michael G. Turner, and Alex R. Piquero. 2004. Parental
socialization and community context: A longitudinal analysis of the
structural sources of low self-control. Journal of Research in Crime and
Reid, John B., Gerald R. Patterson, and James Snyder. 2002. Antisocial
Behavior in Children and Adolescents. Washington, DC: American Psy-
Reid, Robert, Alexandra L. Trout, and Michalla Schartz. 2005. Self-
regulation interventions for children with attention deﬁcit/hyperactivity
disorder. Exceptional Children 71:361–77.
Ross, Lisa T., and Elizabeth M. Hill. 2002. Childhood unpredictability,
schemas for unpredictability, and risk taking. Social Behavior and Per-
Rutter, Michael. 2003. Crucial paths from risk indicator to causal mech-
anism. In Causes of Conduct Disorder and Juvenile Delinquency, eds.
Benjamin B. Lahey, Terrie E. Mofﬁtt, and Avshalom Caspi. New York:
Sallaz, Jeffrey J., and Jane Zavisca. 2007. Bourdieu in American sociology,
1980–2004. Annual Review of Sociology 33:21–41.
Sampson, Robert J., and John H. Laub. 1993. Crime in the Making: Path-
ways and Turning Points Through Life. Cambridge, MA: Harvard Uni-
594 SIMONS & BURT
Sampson, Robert J., Jeffrey D. Morenoff, and Thomas Gannon-Rowley.
2002. Assessing neighborhood effects: Social processes and new direc-
tions in research. Annual Review of Sociology 28:443–78.
Sampson, Robert J., Stephen W. Raudenbush, and Felton Earls. 1997.
Neighborhoods and violent crime: A multilevel study of collective ef-
ﬁcacy. Science 277:918–24.
Schaffer, David, Prudence Fisher, John Piacentini, C. Keith Conners, May
Schwab-Stone, Patricia Cohen 1993. The Diagnostic Interview Sched-
ule for Children–Revised version (DISC-R). Preparation, ﬁeld test-
ing, inter-rater reliability, and acceptability. Journal of the American
Academy of Child and Adolescent Psychiatry 32:643–50.
Shermer, Michael. 2004. The Science of Good and Evil: Why People Cheat,
Gossip, Care, Share, and Follow the Golden Rule. New York: Times
Simons, Ronald L., Yi-Fu Chen, Eric A. Stewart, and Gene H. Brody. 2003.
Incidents of discrimination and risk for delinquency: A longitudinal test
of strain theory with an African American sample. Justice Quarterly
Simons, Ronald L., Christine Johnson, and Rand D. Conger. 1994. Harsh
corporal punishment versus quality of parental involvement as an expla-
nation of adolescent maladjustment. Journal of Marriage and the Family
Simons, Ronald L., Velma Murry, Vonnie McLoyd, Kuei-Hsiu Link, Car-
olyn Cutrona, and Rand D. Conger. 2002. Discrimination, crime, ethnic
identity and parenting as correlates of depressive symptoms among
African American children: A multilevel analysis. Development and
Simons, Ronald L., Leslie G. Simons, Callie Harbin Burt, Gene H. Brody,
and Carolyn Cutrona. 2005. Collective efﬁcacy, parenting practices, and
delinquency: A longitudinal test of a model integrating community- and
family-level processes. Criminology 43:989–1029.
Simons, Ronald L., Leslie G. Simons, Callie Harbin Burt, Holly Drum-
mund, Eric A. Stewart, and Gene H. Brody. 2006. Supportive parent-
ing moderates the effect of discrimination upon anger, hostile view of
relationships, and violence among African American boys. Journal of
Health and Social Behavior 47:373–89.
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 595
Slaby, Ronald G., and Nancy G. Guerra. 1988. Cognitive mediators of
aggression in adolescent offenders: I. Assessment. Developmental Psy-
Sobsey, Dick, Wade Randall, and Rauno K. Parrila. 1997. Gender differ-
ences in abused children with and without disabilities. Child Abuse and
Steffensmeier, Darrell, Jennifer Schwartz, Hua Zhong, and Jeff Ackerman.
2005. An assessment of recent trends in girls’ violence using di-
verse longitudinal sources: Is the gender gap closing? Criminology 43:
Steffensmeier, Darrell, and Jeffery T. Ulmer. 2005. Confessions of a Dy-
ing Thief: Understanding Criminal Careers and Illegal Enterprise.New
Brunswick, NJ: Aldine.
Stewart, Eric A., Christopher J. Schreck, and Ronald L. Simons. 2006. “I
ain’t gonna let no one disrespect me”: Does the code of the street
reduce occurrences of violent victimization among African American
adolescents? Journal of Research in Crime and Delinquency 23:1–33.
Strayhorn, Joseph M., Jr. 2002. Self-control: Theory and research. Journal
of the American Academy of Child & Adolescent Psychiatry 41:7–16.
Swartz, David L. 2002. The sociology of habit: The perspective of Pierre
Bourdieu. Occupational Therapy Journal of Research 22:61–9.
Sykes, Gresham M., and David Matza. 1957. Techniques of neutralization:
A theory of delinquency. American Sociological Review 22:664–70.
Tittle, Charles R., David A. Ward, and Harold G. Grasmick. 2003. Gender,
age, and crime/deviance: A challenge to self-control theory. Journal of
Research in Crime and Delinquency 40:426–53.
Unnever, James D., Francis T. Cullen, Scott A. Mathers, Timothy E. Mc-
Clure, and Marisa C. Allison. 2009. Racial discrimination and Hirschi’s
criminological classic: A chapter in the sociology of knowledge. Justice
Unnever, James D., and Shaun L. Gabbindon. 2011. Race, Racism, and
Crime: A Theory of African American Offending. New York: Rout-
Vitale, Jennifer E., Joseph Newman, John E. Bates, Jackson A. Goodnight,
Kenneth A. Dodge, and Gregory S. Pettit. 2005. Deﬁcient behavioral
596 SIMONS & BURT
inhibition and anomalous selective attention in a community sample of
adolescents with psychopathic and low-anxiety traits. Journal of Abnor-
mal Child Psychology 33:461–71.
Voland, James E. 1988. Differential infant and child mortality in evolu-
tionary perspective: Data from the late 17th to 19th century Osfriesland
(Germany). In Human Reproductive Behavior: A Darwinian Perspec-
tive, eds. Laura Betzig, Monique Borgerhof Mulder, and Paul Turke.
Cambridge, U.K.: Cambridge University Press.
Warr, Mark. 2002. Companions in Crime: The Social Aspects of Criminal
Conduct. Cambridge, U.K.: Cambridge University Press.
Wilson, David Sloan. 2007. Evolution for Everyone: How Darwin’s Theory
Can Change How We Think About Our Lives. New York: Delacorte
Wilson, Margo, and Martin Daly. 1997. Life expectancy, economic in-
equality, homicide, and reproductive timing in Chicago neighborhoods.
British Medical Journal 314:1271–8.
Wilson, Margo, and Martin Daly. 2006. Are juvenile offenders extreme
future discounters? Psychological Science 17:989–94.
Wilson, James Q., and Richard J. Herrnstein. 1985. Crime and Human
Nature. New York: Simon & Schuster.
Zelli, Arnoldo, Kenneth A. Dodge, John E. Lochman, and Robert D.
Laird. 1999. The distinction between beliefs legitimizing aggression and
deviant processing of social cues: Testing measurement validity and
the hypothesis that biased processing mediates the effects of beliefs on
aggression. Journal of Personality and Social Psychology 77:150–66.
Ronald L. Simons is Distinguished Research Professor in the Depart-
ment of Sociology and research fellow in the Institute for Behavioral Re-
search at the University of Georgia. Much of his research has focused on the
manner in which family processes, peer inﬂuences, and community factors
combine to inﬂuence deviant behavior across the life course. He also has
completed work on domestic violence and the effect of racial discrimination
on child development. His recent work has appeared in Criminology,the
Journal of Health and Social Behavior, and Developmental Psychology.
Callie Harbin Burt is an assistant professor in the School of Criminology
and Criminal Justice at Arizona State University. Her current research
SOCIAL CONDITIONS AND SOCIAL SCHEMAS 597
investigates the social-psychological mechanisms through which social fac-
tors, such as racial discrimination, community crime, and harsh parenting,
inﬂuence criminal offending. In other research, she examines the protective
effects of ethnic–racial socialization on the link between racial discrimina-
tion and offending. Her work has recently appeared in American Journal of
Sociology,Criminology, and the Journal of Health and Social Behavior.
598 SIMONS & BURT
Appendix A. Examining Causal Order Issues: Cross-Lagged
Models of Knowledge Structure Components
Wave 3 Wave 4
Cross-Lagged Associations Between Crime and Alternating Knowledge Structure Variables in Waves 3 and 4
Gratification Hostile View Rejected Norms
CrimeW3 ------>CrimeW4 .25** .31** .32**
Alternating KS VarW3 ------>Alternating KS VarW4
.36** .28** .27**
Crime ------>Alternating KS VarW4 .09 .14*.12*
Alternating VarW3------> CrimeW4 .17*.18*.20*
NOTES: Standardized coefﬁcients displayed. Zero degrees of freedom available for
calculation of model ﬁt indices.
aImmediate gratiﬁcation was not included in the wave 3 survey; thus, waves 2 and 4 were
used in this model.
∗p<.05; ∗∗p<.01 (two-tailed tests).
Appendix B. Reduced Continuous SEM (N=713)
NOTES. Standardized values displayed; age controlled but only related to exogenous constructs
and thus not shown for clarity. R2 in parentheses below endogenous constructs.
Model fit indices: χ
(36) p=.003; CFI = .97; TLI = .97; RMSEA =.03.
NOTES: Standardized values displayed; age controlled but only related to exogenous
constructs and thus not shown for clarity. R2in parentheses below endogenous con-
Model ﬁt indices: χ2(df) =63.36(36) p=.003; CFI =.97; TLI =.97; RMSEA =.03.