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Developmental Trajectories of Individuals’ Code of the Street Beliefs through Emerging Adulthood

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Objectives This study seeks to contribute to research on the patterning and stability of code of the street beliefs. We describe trajectories of street code beliefs from late childhood to emerging adulthood and investigate social factors that influence membership in and distinguish between trajectories. Methods Using six waves of panel data from the Family and Community Health Study, group-based trajectory models were estimated to describe developmental patterns of street code beliefs from age 10 to 26. Correlates of street code beliefs, including racial discrimination, parenting practices, and neighborhood crime, were used to predict trajectory membership. Results Analyses identified five distinct trajectories of street code beliefs. Four trajectories were largely stable across the study period; however, one group, comprised of 12 percent of the sample, dramatically declined in beliefs. Being male and experiencing racial discrimination significantly distinguish between all of the trajectories. Parental monitoring and perceptions of neighborhood crime differentiate between the declining trajectory and the stable trajectories. Conclusions Findings provide insights into the developmental patterns and correlates, of street code beliefs. Results suggest beliefs are malleable but remain largely stable and underscore the need for more nuanced, longitudinal approaches to the code of the street.
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Original Article
Developmental
Trajectories of
Individuals’ Code
of the Street Beliefs
through Emerging
Adulthood
Richard K. Moule Jr.
1
, Callie H. Burt
1
,
Eric A. Stewart
2
, and Ronald L. Simons
3
Abstract
Objectives: This study seeks to contribute to research on the patterning and
stability of code of the street beliefs. We describe trajectories of street
code beliefs from late childhood to emerging adulthood and investigate
social factors that influence membership in and distinguish between trajec-
tories. Methods: Using six waves of panel data from the Family and Commu-
nity Health Study, group-based trajectory models were estimated to
describe developmental patterns of street code beliefs from age 10 to 26.
Correlates of street code beliefs, including racial discrimination, parenting
practices, and neighborhood crime, were used to predict trajectory mem-
bership. Results: Analyses identified five distinct trajectories of street code
1
Arizona State University, Phoenix, AZ, USA
2
Florida State University, Tallahassee, FL, USA
3
University of Georgia, Athens, GA, USA
Corresponding Author:
Richard K. Moule Jr., School of Criminology and Criminal Justice, Arizona State University,
Phoenix, AZ, USA.
Email: rmoulejr@asu.edu
Journal of Research in Crime and
Delinquency
1-31
ªThe Author(s) 2015
Reprints and permission:
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DOI: 10.1177/0022427814565904
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beliefs. Four trajectories were largely stable across the study period; how-
ever, one group, comprised of 12 percent of the sample, dramatically
declined in beliefs. Being male and experiencing racial discrimination signif-
icantly distinguish between all of the trajectories. Parental monitoring and
perceptions of neighborhood crime differentiate between the declining tra-
jectory and the stable trajectories. Conclusions: Findings provide insights into
the developmental patterns and correlates, of street code beliefs. Results
suggest beliefs are malleable but remain largely stable and underscore the
need for more nuanced, longitudinal approaches to the code of the street.
Keywords
code of the street, group-based trajectory modeling, human development,
life-course criminology, racial discrimination
The past two decades have seen a renewed interest in culture as a causal
mechanism for criminal behavior, particularly among residents of urban
communities (e.g., Sampson and Bean 2006; Small and Newman 2001;
Wilson 1987, 2009). In contrast to earlier ‘‘cultural deficit’’ explana-
tions, these recent cultural approaches explicate, even emphasize, the
structural underpinnings of cultural landscapes and models. Anderson
(1999) described a particularly influential conception of culture known
as the code of the street. Consistent with other prominent subcultural
theories (Cloward and Ohlin 1960; Cohen 1955), the code is embedded
in structural disadvantage, especially the absence of opportunities to
achieve status through conventionally prescribed means. This absence
is coupled with issues in individuals’ immediate social milieu, such
as a distrust of law enforcement (Brunson 2007; Carr, Napolitano, and
Keating 2007; Stewart, Schreck, and Brunson 2008). The code has
emerged to regulate interpersonal behavior in public spaces, particularly
violence, in these neighborhoods. Given the dearth of conventional
opportunities for status attainment and the perceived lack of protection
from formal control agents, violence has emerged as an acceptable
means of managing social status and discouraging future predation on
the street.
Although some research has tested Anderson’s arguments on the ori-
gins of the code and its relationship to crime (Brezina et al. 2004;
Pyrooz, Moule, and Decker 2014; Stewart and Simons 2006, 2010),
little is known about the developmental patterns of street code beliefs.
1
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According to Anderson (1999), distinct patterns of these beliefs emerge
at a young age through varying degrees of exposure to adverse parent-
ing, neighborhood conditions, and peers. Neighborhood residents provide a
rough account of these patterns, labeling individuals ‘‘decent’’ or ‘‘st r e e t .’’
This dichotomy is likely more complex, however, existing along a conti-
nuum of beliefs (Anderson 1999:36, 2002; Benoit et al. 2003).
This complexity is magnified by conflicting evidence on the stability
of these beliefs. Anderson (1999:69) suggests that beliefs are formed in
childhood and reinforced in adolescence before becoming more stable in
adulthood. Such a view parallels emerging research on social schemas,
whereby individuals internalize the lessons of salient or persisting life
experiences (Simons and Burt 2011). Although malleable, schemas
often remain relatively stable, given cumulative continuity in experi-
ences. As many individuals remain embedded in areas where knowledge
of the street code is necessary, there is good reason to expect consider-
able relative stability in their belief in the street code. Alternatively,
qualitative research has found many individuals claim to disavow the
code of the street or follow it only in passing, even if they continue
to reside in disadvantaged communities (e.g., Hunter and Davis 1992,
1994; Oliver 2006). We thus interpret Anderson to suggest relative sta-
bility into adulthood, while also recognizing individuals’ capacities to
adapt to changes in social circumstances.
Drawing from prior research on the street code, and using panel data
of several hundred African Americans, we use group-based trajectory
modeling(GBTM)toexaminestreetcode beliefs through emerging
adulthood (Nagin 2010). Consistent with Brame, Paternoster, and
Piquero (2012), we harness GBTM to investigate etiologically signifi-
cant trajectories and inform theory on the code. We are interested in
discerning the patterning of street code beliefs, the factors distinguish-
ing these patterns, and the stability of these patterns; GBTM is well
suited for these goals. We attempt to answer the following three
research questions: (1) Are most individuals characterized by approxi-
mate, or relative, stability in their street code beliefs? (2) Are there dis-
tinct longitudinal patterns of these beliefs, and, if so, what do they look
like? and (3) Do established correlates of the street code distinguish
between these patterns? The overall goal of this article is to describe
long-term developmental patterns and stability of street code beliefs.
Addressing this topic can provide theoretical clarity on the code and
assist in the development of interventions that target correlates of these
beliefs.
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Development and Internalization of the Code of the
Street
The code of the street refers to public norms of interpersonal behavior. Indi-
vidual adherence to the code, which can be understood as a cognitive land-
scape (Sampson and Bean 2006), is linked to the differences in the social
milieus—families, peer groups, and neighborhoods—in which individuals
are situated. These milieus convey, confirm, and reinforce various cultural
frames, such as the code of the street (Anderson 1999).
Street codes emerge in disadvantaged areas primarily through resident
socialization processes, where families view one another as either decent
or street (Anderson 1999). Most families are decent, accepting and instil-
ling mainstream values into their childrenthroughacombinationofstrict
monitoring, love, and affection (Furstenberg et al. 1999; Simons et al.
2005; Stewart and Simons 2006). Recognizing the dangers of the street
code, decent families educate their children on it and work to prevent
associating with individuals who model and reinforce it. Furthermore,
decent families encourage their children to focus more strongly on pro-
social activities and behaviors, instead of those associated with the code.
Street families, in contrast, are characterized by chaotic home lives.
According to Anderson (1999), parents in these families rely on harsh dis-
cipline, are often inattentive, emotionally distant, and encourage aggres-
siveness in their kids. Children of street families thus learn at an early
age that problem solving is best accomplished with violence (Anderson
1999; Patterson 1982).
Street code socialization extends beyond the home. Local residents may
reinforce beliefs of street-oriented families or challenge those of decent
families. ‘‘Old heads’’ and ‘‘decent dads’’—older, employed men who once
educated youngsters on being decent—have been superseded by drug
dealers and others actively involved in illicit, underground economies
(Anderson 1999:111). Despite the efforts of parents, children are likely to
come into contact with street-oriented peers in public areas such as school
(Anderson 1999, 2008). These encounters are coupled with adverse day-to-
day events, such as experiences with racial discrimination and exposure to
crime. Discrimination promotes legal cynicism (Anderson 1999; Unnever
and Gabbidon 2011), can reduce adherence to conventional conduct norms,
or foster the adoption of unconventional beliefs (Burt, Simons, and Gibbons
2012; Cloward and Ohlin 1960). Such beliefs may focus on the need to
engage in violent self-defense in areas where crime or legal cynicism is high
(Black 1983). Further, discrimination can promote a wariness of others and
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aggressive social posturing (Bernard 1990). These experiences promote
stronger adherence to the code (Anderson 1999).
These factors provide a foundation for stronger code-related beliefs,
though, ‘‘[by] the time they are teenagers, most young people in the disad-
vantaged, isolated communities have internalized the code of the street, or
have at least learned to comport themselves in accordance with its rules’’
(Anderson 1999:72). That is, most youths are familiar with the code; how-
ever, focusing on behavioral comportment neglects differences in the
degree that individuals ‘‘buy into’’ it. Indeed, Anderson (1999) suggests that
street code beliefs are varied and can change over time (i.e., individuals can
at least become acculturated to the code by adolescence). Given this,
experiences with hostile or negative parenting, associations with deviant
peers, and exposure to more discrimination should increase adherence to the
code in childhood and distinguish between developmental patterns of these
beliefs (e.g., Anderson 1999; Simons and Burt 2011; Stewart and Simons
2006). Importantly, although these characteristics provide a foundation for
understanding the code, it is unclear how stable beliefs are over time.
Stability of Street Code Beliefs
Although Anderson (1999) discussed the developmental features of street
and decent socialization, little is known about the developmental patterns
of street code beliefs or their stability over time. To be sure, Anderson’s
(1999:102) description of the ‘‘coming of age process’’ associated with the
code draws attention to individual adherence to it over time, and evidence
suggests that ‘‘street socialization’’ extends beyond adolescence (Oliver
2006). Anderson (1999:68-69) noted, ‘‘As children mature and obtain an
increasingly more sophisticated understanding of the code, it becomes part
of their working conception of the world, so that by the time they reach
adulthood, it has emerged as an important element of public social order.
The rules of physical engagement and their personal implications have crys-
tallized.’’ Based on his observations and interactions with others over a
number of years, Anderson (1999) appears to suggest that individuals’ street
code beliefs are relatively stable and become increasingly stable as an indi-
vidual enters emerging adulthood.
Anderson provides some evidence suggesting that street code beliefs are
durable and persisting. Anderson’s (1999:289) depiction of John Turner
shows the intractability of the code despite some changes in social condi-
tions (i.e., entry into the legitimate workforce as a janitor). The stability
of the code is also implicit in Anderson’s (1999:49, 115) accounts of street
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families. Individuals born into such families are socialized into the code,
buy into it at an early age, and continue adhering to it as they age. Residing
in the same neighborhoods and repeatedly experiencing hostile interactions
naturally reinforces belief in the code. In short, Anderson’s accounts imply
that street code stability is tied to continuity of neighborhood and interac-
tional experiences, and as these experiences accumulate over time, beliefs
become more entrenched, and change becomes less likely. Tentative
empirical evidence supports continuity in these beliefs but has examined
only late adolescence and has not specifically focused on stability (e.g.,
Brezina et al. 2004).
Consistent with this interpretation of stability of beliefs as a consequence
of stability of circumstances, we would expect changes in adherence to the
street code as a consequence of changes in the conditions of these individ-
uals’ lives. Consonant with this idea, Simons and Burt (2011) found that
street code beliefs changed in response to changes in parenting, discrimina-
tion, and community conditions (viz. collective efficacy and community
crime). Similarly, individuals from decent families may become more
strongly attached to the code as a consequence of their peer interactions dur-
ing adolescence, only to see such beliefs attenuate over time as their social
networks change (Anderson 1999). Likewise, Matsuda et al. (2013) showed
that the onset of gang membership corresponds with increased adherence to
the street code. In sum, we interpret Anderson’s theses (1999) in concert
with theory and research on the stability of schemas and worldviews
(e.g., Simons and Burt 2011), as implying that there will be considerable
relative stability in street code beliefs, while recognizing the possibility for
change. Providing empirical evidence of the extent of stability in the street
code is a central goal of this study.
Current Study
Absent from studies of the street code has been a satisfactory empirical
examination of the developmental patterns and stability of individuals’
street code beliefs. This study focuses on three questions. First, is there
short- and long-term stability in street code beliefs? Second, what are the
distinct longitudinal patterns of these beliefs? Third, what social factors
influence assignment into and distinguish between these trajectories? Draw-
ing on Anderson’s (1999) work, we anticipate multiple developmental
belief patterns, with specific socialization factors (e.g., negative parenting
practices, association with antisocial peers, and experiences with racial dis-
crimination) setting the stage for distinct developmental pathways. Further,
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we expect that adherence to the code remains relatively stable through ado-
lescence, becoming more intractable in adulthood. We formulate the fol-
lowing three hypotheses that reflect these considerations:
Hypothesis 1: There is short- and long-term relative stability in street
code beliefs over time.
Hypothesis 2: The complex underlying reality of the code of the street
reflects the presence of multiple, distinct developmental trajectories of
street code beliefs.
2
Hypothesis 3: Hostile parenting, associating with antisocial peers, and
racial discrimination will influence the levels of street code beliefs and
distinguish between specific developmental trajectories of these beliefs.
Method
Data
The data used in this study are from the Family and Community Health Study
(FACHS), a longitudinal, multisite investigation of factors that promote Afri-
can American family functioning and youth development in various contexts
(Gibbons et al. 2004; Simons et al. 2002). Families were recruited from
neighborhoods varying in demographic characteristics, specifically racial
composition (percentage of African American) and economic level (percent-
age of families with children living below the poverty line). Using 1990 cen-
sus data, block groups (BGs) were identified in both Iowa and Georgia in
which the proportion of African American families was high enough to make
recruitment economically practical (10 percent or higher), and in which the
proportion of families with children living below the poverty line varied (ran-
ged from 10 percent to 100 percent). Using these criteria, 259 BGs were iden-
tified (115 in Georgia and 144 in Iowa). Families living in the chosen BGs
were randomly selected and recruited by telephone fromrosters of all African
American families who had a fifth grader (the target child) in the public
school system (see Simons et al. 2006).
A total of 897 African American families (475 from Iowa and 422 from
Georgia) participated in the first wave of the FACHS. Each family included
a fifth grade target youth between the ages of 10 and 12 at wave 1. Fifty-
four percent were female. The first wave of data collection began in 1997
to 1998, and follow-up interviews with the target children and their family
members were conducted every 2 to 3 years thereafter. This study uses tar-
get child data from the first six waves of data, collected between 1997 and
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2011. These data capture information from late childhood through emerging
adulthood. By wave 6, participants are between the ages of 21 and 26. The
FACHS retention rate is high. Specifically, 699 target youth (78.6 percent
of the original sample) participated more than a decade later at wave 6, and
there is little evidence of selective attrition over the course of the study.
Although a higher percentage of the wave 6 respondents were female and
were slightly less delinquent, there were no significant differences between
participants and nonparticipants with regard to community measures, family
structure, or parenting practices at earlier waves (Burt, Sweeten, and Simons
2014).
This study uses GBTM, which requires a minimum of three observations
on the dependent variable (Jones, Nagin, and Roeder 2001; Nagin 2005).
Seventy-nine respondents (8.8 percent of the entire sample) were excluded
given this requirement. Thus, our core sample consists of 818 respondents
who had available measures of street code beliefs in at least three study
waves. A complete description of study variables is in Appendix A.
Variables
Our outcome measure, street code beliefs, is a seven-item composite scale,
encompassing the respondent’s view that violence is justified or acceptable
to use. Although the code encompasses much more than just these beliefs,
these items tap into a salient component of the code (e.g., Stewart and Simons
2006). Respondents indicated agreement with each statement on a scale rang-
ing from 1 (strongly disagree)to4(strongly agree). Responses were summed
at each wave to indicate the extent of an individual’s street code beliefs, rang-
ing from 7 to 28, with higher levels indicating stronger beliefs.
Independent Variables
The key independent variable, age, is the respondent’s self-reported age at
the time of the survey’s administration.
Risk Variables
We include a number of individual-level variables that may influence street
code beliefs. These variables are drawn from the wave 1 survey, when
respondents were in the fifth grade (between the ages of 10 and 12), an
important time period in socialization on the street code and the formation
of street code beliefs (Anderson 1999).
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Delinquent peers. Children self-reported their affiliation with deviant peers
using an instrument adapted from the National Youth Survey (Elliott,
Huizinga, and Menard 1989). They were asked how many of their close
friends (1 ¼none,2¼some, and 3 ¼all) had engaged in seven delinquent
acts in the previous year. Responses were summed to obtain a total score,
ranging from 7 to 21, on the extent respondents’ friends engaged in
deviance (e.g., Burt, Simons, and Simons 2006).
Racial discrimination. Youth completed 13 items from a revised version of the
Schedule of Racist Events (SRE; Ladrine and Klonoff 1996). The SRE was
originally designed for African American adults, thus the FACHS research-
ers revised the instrument to make it more applicable to youths. The scale
asks about events that occurred as a consequence of being African
American and has been used in prior studies of African Americans (e.g.,
Burt et al. 2012; Simons et al. 2006). The items assess the frequency
(1 ¼never to 4 ¼several times) that discriminatory events were experi-
enced over the past year, and higher values indicate more experiences with
discrimination.
Caregiver hostility. Respondents’ perceptions of caregiver hostility were mea-
sured using a 13-item cumulative scale. Responses ranged from (1) never to
(4) always. Questions involved caregiver behavior directed at the respon-
dent in the year prior to the interview, with higher scores indicating greater
hostility.
Caregiver monitoring. Respondents answered four items about monitoring
practices by their caregiver. Responses ranged from (1) never to (4) always,
with higher scores indicating more monitoring (Brody et al. 2003).
Caregiver warmth. Respondents assessed nine items reporting the extent to
which their parent was warm and loving. Each item ranged from (1) never
to (4) always. Questions involved caregiver behavior directed at the respon-
dent in the year prior to the interview, with higher scores indicating greater
caregiver warmth.
Parental reinforcement of conformity. Respondents were asked nine items
about how their parents would react to them engaging in various prosocial
behaviors. Responses to each item were (1) tell you to stop,(2)do nothing,
or (3) encourage you to do it again. Higher scores indicate greater reinfor-
cement of conforming behavior by parents.
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Caregiver harsh discipline. Respondents answered four questions regarding
harsh discipline by their caregiver. Responses ranged from (1) never to
(4) always, with higher scores indicating more frequent, harsh discipline.
Self-control. Children reported on 16 items tapping into elements of self-control
(Gottfredson and Hirschi 1990). They were asked how true statements were
regarding their impulsivity, ability to delay gratification, and proclivity for
risky behavio r (1 ¼not at alltrue,2¼somewhat true,and3¼verytrue). Items
were summed, with higher scores indicating lower levels of self-control (see
Burt et al. 2006). We include self-control to account for population heteroge-
neity, and because self-control and the code of the street likely interweave in
complex ways (e.g., Brezina, Tekin, and Topalli 2009; Simons and Burt 2011).
Monitoring in neighborhood. Respondents assessed the monitoring practices of
residents in their neighborhoods using three questions. Response sets ran-
ged from (1) very unlikely to (4) very likely for each item, such that higher
overall scores indicate more neighborhood monitoring.
Neighborhood crime. Respondents reported on their perceived frequency of
serious, interpersonal crimes in their neighborhood on a five-item compo-
site scale. Responses ranged from (1) never to (3) often. Higher numbers
reflect higher levels of perceived crime. Male is a binary variable where
male and female are coded 1 and 0, respectively.
All analyses were conducted using the Proc Traj command in SAS 9.3
(SAS Institute Inc., Cary, NC). Given the scaled nature of the dependent
variable, a censored normal model is used (Nagin 1999). Collinearity diag-
nostics revealed no problematic correlations, thus allowing for the inclusion
of covariates following an assessment of the basic model.
3
Results
Summary Statistics and Correlations
Table 1 presents summary statistics of the study sample. Mean levels of
street code beliefs remain largely consistent across waves, peaking at wave
3 and declining thereafter. To assess the stability of these beliefs, we first
examine their correlations across study waves.
Table 2 shows the correlation of these beliefs across the six waves of the
study, revealing two key patterns. First, street code beliefs are mildly stable
over the long term but, as expected by Anderson (1999), become more
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strongly correlated over time. Street code beliefs between waves 1 and 2
are modestly correlated (r¼.24) and are more than twice that size between
waves5and6(r¼.57).
4
This finding lends tentative support to Anderson’s
(1999) suggestion that beliefs become more intractable in adulthood. This
trend may mask various patterns, or the continuum, of belief in the street code
Table 1. Summary Statistics of Study Variables.
Valid nMean SD Min Max
Street code beliefs wave 1 779 18.68 3.80 7 28
Street code beliefs wave 2 758 18.73 3.82 7 28
Street code beliefs wave 3 755 19.08 3.81 8 28
Street code beliefs wave 4 710 18.23 3.64 7 28
Street code beliefs wave 5 679 17.80 4.64 7 28
Street code beliefs wave 6 658 15.89 4.17 7 27
Age wave 1 417 10.41 0.53 10 12
Age wave 2 761 12.29 0.85 11 15
Age wave 3 760 15.56 0.88 13 18
Age wave 4 713 18.83 0.91 16 21
Age wave 5 686 21.55 0.86 19 25
Age wave 6 689 23.58 0.87 21 26
Peer delinquency 791 8.85 2.02 7 18
Racial discrimination 709 21.19 6.85 13 47
Self-control 804 26.36 4.76 16 41
Caregiver hostility 801 19.23 4.37 13 40
Caregiver warmth 797 30.91 4.76 9 36
Caregiver monitoring 811 13.51 2.44 4 16
Caregiver reinforcement of conformity 780 24.74 2.16 10 27
Caregiver harsh discipline 804 7.52 2.19 4 16
Monitoring in neighborhood 806 9.26 2.29 3 12
Neighborhood crime 784 6.65 2.16 5 15
Male 818 .45 — 0 1
Table 2. Street Code Correlation Coefficients.
Wave 2 Wave 3 Wave 4 Wave 5 Wave 6
Wave 1 .24 (722) .21 (721) .11 (677) .17 (648) .18 (625)
Wave 2 .39 (706) .28 (656) .24 (625) .26 (607)
Wave 3 .37 (668) .36 (627) .29 (608)
Wave 4 .46 (623) .42 (603)
Wave 5 .57 (599)
Note: Sample size is given in parentheses.
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(e.g., Piquero 2008). To address this, we turn to our second hypothesis and a
modeling strategy that can better elaborate on the complexity of the code.
GBTM of Street Code Beliefs
Trajectories of street code beliefs are presented in Figure 1. Bayesian infor-
mation criterion (BIC) estimates indicate that the addition of groups beyond
five reduces the accuracy of the overall model, and each trajectory was best
defined by a quadratic term. Figure 1 shows the five trajectories of street
code beliefs across the six waves of the study as well as the percentage
of the sample participants classified into each group. Four clusters of indi-
viduals, encompassing 88 percent of the sample, exhibit substantial stability
in their adherence to the street codes. These include those who would pre-
sumably be considered street (6.3 percent), decent (7.1 percent), and those
occupying the complex middle ground (34.2 and 40.8 percent, respectively)
noted by Anderson (2002). Notably, these trajectories peak at different
ages. Group 2 appears to peak around age 13, group 1 at 15, group 3 at
16, and group 5 between 17 and 18. The general shape and slope of the tra-
jectories suggests past research on adolescents’ adherence to the street code
(e.g., Brezina et al. 2004; Taylor et al. 2010) has perhaps tapped only into
the escalation of street code beliefs during adolescence.
5
10
15
20
25
30
11 12 13 14 15 16 17 18 19 20 21 22 23 24
Street Code Beliefs
Age
Group 1 (7.1%) Group 2 (34.2%) Group 3 (40.8%)
Group 4 (11.6%) Group 5 (6.3%)
Figure 1. Trajectories of street code beliefs through emerging adulthood (N¼818).
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In general, these findings offer further answers to Hypotheses 1 and 2.
Evidence is largely supportive of the relative stability of street code beliefs
over roughly 15 years.
5
The presence of group 4 raises questions about street
code beliefs, as it is not anticipated by the literature. In contrast to the other
groups, which exhibit relative stability, for group 4, street code beliefs begin
to decline soon after age 10 and continue this decline throughout the study
period.
6
What situations and experiences characterize group 4? We first use
profiles of group membership, shown in Table 3, to answer this question.
The descriptive profiles of group membership shown in Table 3 are derived
from the ‘‘classify and analyze’’ method (Nagin 2005). This method uses max-
imum posterior probabilities of group membership when creating profiles and
highlights a number of potential features distinguishing between trajectories.
Group 4, for instance, exhibits some of the highest means with respect to racial
discrimination but also caregiver monitoring, warmth, and reinforcement of
conformity. Those classified into group 4 are, on average, middle of the road
regarding delinquent peer affiliations, self-control, caregiver hostility, and
harsh discipline. This juxtaposition, between negative experiences outside the
home but supportive caregiver practices at home, might explain the decline in
street code beliefs. These descriptive group profiles, although informative, do
not speak to whether any of these characteristics significantly influence or dis-
tinguish between the trajectories. We thus turn to our third hypothesis and
assess risk factors for trajectory assignment in a multivariate context.
7
Risk Factors for Group Membership
Hypothesis 3 focuses on the characteristics that are hypothesized to distin-
guish trajectory assignments—negative parenting practices, experiences
with discrimination, and delinquent peers. The application of risk factors
in this context is essentially a multinomial logistic regression and can be
thought of as reporting separate logistic regressions contrasting each trajec-
tory with the reference group, group 1 (see Chap. 6 in Nagin 2005).
8
Table 4
contains these models. Two variables consistently influence group assign-
ment, namely, experiences with racial discrimination and being male. For
instance, being male increases the odds that an individual will be in group
5, relative to group 1, substantially. The only variable distinguishing group
4 from the group 1 is racial discrimination. A one-unit increase in experi-
ences with racial discrimination corresponds with a 23 percent, increase
in the odds of being in group 4 relative to group 1. Notable, differences
in levels of self-control are only salient when distinguishing group 5 from
the reference category and only nominally so.
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Table 3. Profiles of Group Membership Using the ‘‘Classify and Analyze’’ Method.
Group 1 Group 2 Group 3
nMean SD Min Max nMean SD Min Max nMean SD Min Max
Delinquent peers 50 8.24 1.65 7 17 284 8.5 1.90 7 18 340 9.16 2.15 7 18
Racial discrimination 40 18.18 4.96 13 34 249 19.78 6.31 13 46 314 21.88 6.81 13 45
Self-control 50 24.88 4.83 17 37 291 25.85 4.77 16 40 347 26.87 4.68 17 40
Caregiver hostility 49 18.20 4.89 13 36 289 19.00 4.40 13 35 347 19.47 4.15 13 40
Caregiver warmth 49 31.53 4.33 19 36 288 31.25 4.71 13 36 344 30.33 4.98 9 36
Caregiver monitoring 49 14.24 2.35 7 16 294 13.74 2.32 6 16 350 13.10 2.58 4 16
Caregiver reinforcement of conformity 46 24.28 2.13 17 26 283 24.94 1.82 17 27 335 24.63 2.37 10 27
Caregiver harsh discipline 49 6.92 1.75 4 11 293 7.36 2.00 4 15 344 7.66 2.27 4 16
Monitoring in neighborhood 48 9.42 2.22 3 12 293 9.25 2.28 3 12 349 9.24 2.27 3 12
Neighborhood crime 47 5.98 1.45 5 10 282 6.43 2.12 5 15 342 6.82 2.21 5 15
Male 50 0.20 — 0 1 296 0.46 — 0 1 354 0.48 — 0 1
Group 4 Group 5
nMean SD Min Max nMean SD Min Max
Delinquent peers 76 8.92 1.85 7 14 41 9.24 1.91 7 14
Racial discrimination 69 22.78 7.68 13 47 37 25.08 7.62 13 45
Self-control 75 25.92 4.47 18 39 41 28.32 4.97 21 41
Caregiver hostility 76 19.16 4.54 13 39 40 20.28 4.90 13 37
Caregiver warmth 75 31.92 4.20 18 36 41 30.85 4.37 23 36
Caregiver monitoring 77 14.00 2.21 7 16 41 13.49 2.16 7 16
Caregiver reinforcement of conformity 76 24.79 2.16 13 27 40 24.58 2.48 16 27
Caregiver harsh discipline 77 7.44 2.23 4 13 41 8.32 2.85 4 16
Monitoring in neighborhood 75 9.23 2.37 3 12 41 9.24 2.44 3 12
Neighborhood crime 73 6.68 2.17 5 15 40 7.53 2.42 5 13
Male 77 0.38 0 1 41 0.63 — 0 1
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Table 4. Risk Factors for Trajectory Membership.
a
Group 2 Group 3 Group 4 Group 5
Coefficient SE Coefficient SE Coefficient SE Coefficient SE
Delinquent peers 0.02 (0.18) 0.06 (0.17) 0.03 (0.19) 0.01 (0.20)
Racial discrimination 0.04 (0.07) 0.15 (0.05)** 0.21 (0.06)*** 0.22 (0.06)***
Self-control 0.04 (0.07) 0.07 (0.07) 0.08 (0.08) 0.15 (0.09)
#
Caregiver hostility 0.04 (0.10) 0.02 (0.09) 0.02 (0.10) 0.10 (0.13)
Caregiver warmth 0.08 (0.07) 0.07 (0.07) 0.05 (0.08) 0.01 (0.09)
Caregiver monitoring 0.08 (0.15) 0.17 (0.13) 0.00 (0.16) 0.04 (0.18)
Caregiver reinforcement of conformity 0.02 (0.16) 0.04 (0.15) 0.10 (0.19) 0.07 (0.17)
Caregiver harsh discipline 0.05 (0.15) 0.14 (0.14) 0.14 (0.15) 0.07 (0.18)
Monitoring in neighborhood 0.07 (0.12) 0.02 (0.10) 0.02 (0.12) 0.01 (0.14)
Neighborhood crime 0.09 (0.15) 0.01 (0.14) 0.08 (0.16) 0.10 (0.16)
Male 1.29 (0.68)
#
1.67 (0.65)** 1.07 (0.76) 2.46 (0.78)**
Constant 0.46 (5.73) 0.27 (5.28) 6.31 (6.23) 6.31 (6.33)
Note: n ¼651.
a
Group 1 is the reference group.
***p< .001; **p< .01; *p< .05;
#
p< .10.
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Because group 4 is of paramount theoretical interest, weran alternative tests
in which this group was used as the reference category.
9
Table 5 contains these
models. We focus on the comparisons between groups 3, 4, and 5. As groups 4
and 5 start at similar levels of belief in the code of the street, discerning the fac-
tors that distinguish these trajectories is worthwhile. Two risk factors emerge.
First, higher levels of neighborhood crime promote stronger adherence to the
code. A one-unit increase in neighborhood crime corresponds with a roughly
20 percent increase in the odds of being in group 5 versus group 4. Second, and
consistent with earlier models, being male exerts considerable influence, dis-
tinguishing these trajectories. With respect to groups 3 and 4, two risk factors
also emerge that influence trajectory assignment, racial discrimination, and
caregiver monitoring. A one-unit increase in caregiver monitoring, for exam-
ple, corresponds to a roughly 16 percent, reduction in the odds of being in
group 3, compared to group 4. These findings provide evidence that group 4
is at a nexus between negative external experiences (e.g., racialdiscrimination)
and more attentive parenting.
Finally, consistent with Jones and Nagin (2007), we evaluate whether the
risk factors distinguish between all trajectories using a Wald test of equality
of coefficients. As Table 6 shows, two features distinguish between all of the
groups: being male and experiences with racial discrimination; results are con-
sistent for models in Tables 4 and 5, regardless of reference group. Overall, this
finding provides only partialsupport for Hypothesis 3,regarding theinfluence
of hostile parenting, associating with antisocial peers, and racial discrimination
in influencing beliefs and distinguishing between developmental trajectories.
We reserve discussion of these findings for the following section.
Discussion
Motivated by the knowledge gap on street code stability over time and
drawing upon Anderson’s (1999) description of the code, this study
assessed developmental patterns of code-related beliefs and the impact of
risk factors on these patterns. Using panel data of a sample of African
Americans followed from childhood to emerging adulthood, GBTM
revealed three key findings. First, five different groups emerged from the
data, four of which exhibited relative stability. Second, being male and hav-
ing more experiences with racial discrimination were significant risk factors
for stronger street code beliefs. Third, the factors distinguishing the declin-
ing trajectory from the more stable groups include racial discrimination,
parental monitoring, neighborhood crime, and being male. These findings
warrant two broader points of discussion.
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Table 5. Risk Factors for Trajectory Membership.
a
Group 1 Group 2 Group 3 Group 5
Coefficient SE Coefficient SE Coefficient SE Coefficient SE
Delinquent peers 0.03 (0.19) 0.01 (0.14) 0.08 (0.11) 0.04 (0.14)
Racial discrimination 0.21 (0.06)*** 0.17 (0.06)** 0.06 (0.03)* 0.01 (0.04)
Self-control 0.08 (0.08) 0.03 (0.06) 0.01 (0.05) 0.08 (0.06)
Caregiver hostility 0.02 (0.10) 0.07 (0.07) 0.04 (0.06) 0.07 (0.10)
Caregiver warmth 0.05 (0.08) 0.03 (0.06) 0.02 (0.05) 0.04 (0.07)
Caregiver monitoring 0.00 (0.16) 0.07 (0.12) 0.17 (0.10)
#
0.04 (0.14)
Caregiver reinforcement of conformity 0.10 (0.19) 0.08 (0.15) 0.14 (0.13) 0.17 (0.15)
Caregiver harsh discipline 0.14 (0.15) 0.09 (0.12) 0.00 (0.09) 0.08 (0.14)
Monitoring in neighborhood 0.02 (0.12) 0.05 (0.11) 0.01 (0.08) 0.00 (0.11)
Neighborhood crime 0.08 (0.16) 0.17 (0.14) 0.09 (0.10) 0.18 (0.12)
y
Male 1.07 (0.76) 0.22 (0.57) 0.59 (0.43) 1.39 (0.59)*
Constant 6.31 (6.23) 6.76 (4.67) 6.58 (4.01)
#
0.01 (5.09)
Note: n ¼651.
a
Group 4 is the reference group.
***p< .001; **p< .01; *p< .05;
#
p< .10.
y
p< .13.
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First, it appears that street code beliefs are relatively stable for most of the
sample from childhood into their mid-20s. This stability is consistent with
Anderson’s (1999) suggestions that street code beliefs become more stable
in early adulthood, as further evidenced by stronger correlations among
beliefs in later study waves. Yet, these results show that street code beliefs
are not fixed after early childhood. One trajectory, comprising roughly 12
percent of the individuals in the sample, exhibited substantial declines in
street code beliefs after late childhood (age 10). This finding of a changing
(declining) group is consonant with work, suggesting that cognitions about
the way the world works remain malleable at least through adolescence
(e.g., Giordano, Cernkovich, and Rudolph 2002; Simons and Burt 2011).
This finding of malleability raises new questions regarding the timing
and catalysts for change in street code beliefs. For example, future research
might examine if there is a period of sensitivity or vulnerability for street
code beliefs, at which point individuals are more responsive to changes
in social conditions. Such research might offer important information for
the timing of interventions among at-risk populations. Similarly, we hope
future work examines factors that engender change in street code beliefs and
how these may interact with individual characteristics. For example, shifts in
familial and social relations or involvement in other age-graded life events,
such as marriage or employment in a satisfying job, may serve as turning
points away from a commitment to the street lifestyle (Giordano et al.,
2002; Laub and Sampson 2003; Simons and Barr 2014). Conversely, as
Anderson (1999:136) noted, negative experiences, including justice system
Table 6. Wald Test of Equality of Coefficients.
a
Variable w
2
Delinquent peers 1.27
Racial discrimination 11.26*
Self-control 3.31
Caregiver hostility 2.47
Caregiver warmth 1.35
Caregiver monitoring 4.66
Caregiver reinforcement of conformity 2.06
Caregiver harsh discipline 1.41
Neighborhood monitoring 0.41
Neighborhood crime 2.61
Male 8.25*
a
Group 1 is omitted; all tests use three degrees of freedom.
*p< .05.
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involvement, victimization, blocked opportunities, or mistreatment related to
racism and other forms of discrimination, may strengthen adherence to the
code. Future research should work to explore the influence of such life
experiences on changes in street code beliefs, net of possible selection effects.
Second, the role of racial discrimination in shaping street code beliefs is
noteworthy. Anderson (1999:312-13) argues that experiences with racism
can foster adherence to the code. Our results are consistent with this thesis
and highlight the genesis of the code in racialized conditions. A number of
recent studies identify the criminogenic consequences of racial discrimina-
tion in part through hostile views of the world, such as those espoused in the
street code (Burt and Simons 2013; Simons et al. 2003; Unnever and
Gabbidon 2011). Accompanying research linking discrimination and crime
is work highlighting the strengths of African American cultures and fami-
lies in the face of racial hostility. Such work identifies familial racial socia-
lization as an important resilience factor that reduces the criminogenic
effects of racial discrimination, in part by reducing the link between dis-
crimination and street code beliefs (e.g., Burt et al., 2012; Burt and
Simons 2013). Some forms of parentalracialsocialization prepare ado-
lescents for experiences with discrimination and assist in the develop-
ment of prosocial coping strategies (see Hughes et al. 2006). Racial
socialization practices, as well as early intervention strategies which
incorporate these practices, may be one avenue to buffer the effects
of discrimination on investment in the code and reduce code-related
violence (Burt and Simons 2013). Future research might pay specific
attention to the role of masculinity in the code, how it shapes street
code beliefs and behavioral manifestations of adherence to the code.
This study is not without limitations. First, consistent with Anderson’s
(1999) account of the code, we have relied on a racially homogenous sam-
ple of African American men and women from Iowa and Georgia. We can-
not think of any reason why our results would be specific to African
Americans or why this geographic restriction at the onset of the study would
bias our results (Stewart and Simons 2006). Nonetheless, we hope future
research explores these issues in more diverse samples. Second, we have
concentrated only on individual correlates of adherence to the code of the
street. Anderson (1999) suggests that street codes are a contextually-
based cultural adaptation. Future research should examine how changes
in social context influence changes in street code beliefs. As prior research
had not yet sufficiently assessed the patterning or stability of street code
beliefs, these trade-offs are a necessary step for considering the code of the
street with the broader context of the life course (Cullen 2011:310).
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Concerns about the use of GBTM must also be addressed. These con-
cerns often hinge on the reification of groups (Sampson and Laub 2005;
Skardhamar 2010), which we have strived to avoid. Consistent with Brame
et al. (2012:485), GBTM was used to elaborate on the ‘‘etiologically signif-
icant’’ developmental trajectories of the street code beliefs that may, in turn,
provide for new ‘‘theoretical propositions and testable hypotheses.’’ The pres-
ence of intersecting trajectories, coupled with Anderson’s (2002) acknowl-
edgment of a complex continuum of beliefs, suggests this strategy is
appropriate. We must stress, although, that the groups here are not ‘‘real’’ but
capture the ‘‘average behavioral trend of a collection of individuals’’ (Nagin
and Tremblay 2005:892). The shapes or sizes of groups are not immutable,
nor are individuals beholden to group patterns. Nevertheless, this study rep-
resents an early attempt to assess street code beliefs over an extensive
period of time using a suitable methodology. Alternative methods and
approaches would be a necessary and vital addition to this body of work.
To be sure, the code of the street encompasses much more than just
beliefs. Perceptions of respect, interpersonal interactions, and techniques of
impression management are all tied to the code. One concept we are unable
to examine is the notion of code switching. Code switching is a situational
adaptation by individuals who are weak believers in the code to make others
think that they, in fact, are strong believers (Anderson 1999; Benoit et al.
2003). The disjunction between situations and the longitudinal data used here
means assessments of code switching are beyond the purview of our study. It
would, however, be reasonable to anticipate that those individuals associated
with all but the strongest beliefs in the street code would engage in code
switching, with varying frequency and effectiveness. With respect to stability
of street code beliefs and code switching, perhaps code switching could be
reinforced or rewarded by peers, thus prompting individuals to increasingly
adhere to the code over time. Although we are unable to explore the concept
further, we encourage greater attention be paid to code switching, the circum-
stances which facilitate it, and the consequences thereof.
In the end, despite the attention it has received over the past decade, the
rich theoretical puzzles of the code of the street await much greater scrutiny.
By elaborating on developmental patterns and the stability of adherence to
the code, this study sought to provide clarity on theoretical issues related to
adherence to the code over an important transitional period of the life
course. In doing so, this research has also demonstrated the necessity and
utility of nuanced and diverse approaches to street code research and pro-
vided a number of fruitful avenues for future inquiry. This remains the tip
of theoretical iceberg, however, and exploring in greater depth how patterns
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of street code beliefs influence patterns of offending, victimization, and
other areas of development is necessary for the vitality of the theory. We
hope researchers continue to elaborate on the complexities, catalysts, and
consequences of the code of the street.
Appendix A
Variable Items and Psychometric Properties
Street code beliefs. (1) Sometimes you have to use physical force or violence
to defend your rights, (2) people will take advantage of you if you don’t let
them know how tough you are, (3) people do not respect a person who is
afraid to fight physically for his or her rights, (4) behaving aggressively is
often an effective way of dealing with someone who is taking advantage of
you, (5) if you don’t let people know you will defend yourself, they will think
you are weak and take advantage of you, (6) it is important to show other peo-
ple that you cannot be intimidated, and (7) people tend to respect a person
who is tough and aggressive. The scale has acceptable reliability across
waves (afrom .705 to .866, mean interitem rranging from .255 to .481).
Risk Factors
Delinquent peers. (1) Engaged in petty theft (<US$25); (2) serious theft
(>US$25); (3) hit someone with the idea of hurting them; (4) attacked some-
one with a weapon; (5) used a weapon, force, or strong-arm methods to get
money or other things from people; (6) gotten high using drugs of some kind;
and (7) drunk a lot of alcohol (three or more drinks at one time). The scale
exhibits acceptable reliability (a¼.749, mean interitem r¼.318).
Racial discrimination. (1) Someone said something insulting to you just because
you are African American; (2) a store owner, sales clerk, or person working at a
place of business treated you in a disrespectful way because you are African
American; (3) the police hassled you just because you are African American;
(4) someone ignored you or excluded you from some activity just because you
are African American; (5) someone suspected you of doing something wrong
just because you are African American; (6) someone yelled a racial slur or
racial insult at you just because you are African American; (7) someone threat-
ened to harm you physically just because you are African American; (8) you
encountered Whites who are surprised that you as anAfrican American person
did something really well; (9) you been treated unfairly because you are
African American instead of White; (10) you encountered Whites who didn’t
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expect you to do well just because you are African American; (11) someone
discouraged you from trying to achieve an important goal just because you are
African American; (12) close friends of yours been treated unfairly just
because they are African American; and (13) members of your family been
treated unfairly just because they are African American. This instrument has
strong psychometric properties (a¼.857, mean interitem r¼.321).
Self-control. (1) You could do something most people would consider danger-
ous like driving a car fast; (2) you enjoy taking risks; (3) you would do almost
anything for a dare; (4) life with no danger would be dull for you; (5*) when
you promise to do something, people can count on you to do it; (6) when you
ask a question, you often jump to something else before getting an answer; (7*)
you stick with what you’re doing until you’ve finished with it; (8) you have to
have everything right away; (9*) when you have to wait in line, you do it
patiently; (10) you have to be reminded several times to do things; (11) you
have a lot of accidents; (12) you would rather have a small gift today than a
large gift tomorrow; (13) you could be described as careless; (14) you like
to switch from one thing to another; (15) if you find that something is really
difficult, you get frustrated and quit; and (16*) you usually think before you
act. The scale exhibits an adequate level of reliability (a¼.672, mean interi-
tem r¼.115). Note: * indicates the item was reverse coded.
Caregiver hostility. (1) Get angry at you; (2) get so mad at you that (he or she)
broke or threw things; (3) shout or yell at you because (he or she) was mad
at you; (4) threaten to hurt you physically; (5) criticize you or your ideas;
(6) push, grab, hit, or shove you; (7) argue with you whenever you disagreed
about something; (8) slap or hit you with (his or her) hands; (9) strike you with
an object; (10) boss you around a lot; (11) throw things at you; (12) insult or
swear at you; and (13) tell you (he or she) is right and you are wrong about
things. The scale has acceptable reliability (a¼.738, mean interitem r¼.190).
Caregiver monitoring. (1) How often does your (parent) know what you do
after school; (2) how often does your (parent) know where you are and what
you are doing; (3) how often does your (parent) know how well you are
doing in school; and (4) how often does your (parent) know if you do some-
thing wrong. The scale has acceptable psychometric properties (a¼.639,
mean interitem r¼.309).
Caregiver warmth. (1) Help you do something that was important to you; (2)
let you know that (he or she) really cares about you; (3) listen carefully to
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your point of view; (4) act supportive and understanding toward you; (5) act
loving and affectionate toward you; (6) have a good laugh with you about
something that was funny; (7) let you know that (he or she) appreciates you,
your ideas, or the things you do; (8) tell you (he or she) loves you; and (9)
understand the way you feel about things. The scale has strong psycho-
metric properties (a¼.817, mean interitem r¼.337).
Caregiver reinforcement of conformity. (1) If you took part in school activities
like band, choir, clubs or school dances; (2) If you took part in community
activities like Young Men’s Christian Association, Young Women’s Christian
Association; (3) If you worked hard to get good grades in school; (4) If you
saved money to go to college; (5) If you took part in sports at school; (6) If you
took part in church activities; (7) If you helped at home by doing things like
cleaning, doing dishes, or taking care of your brother or sister; (8) If you had
a (boy/girl)friend; and (9) If you helped at home by spending money you had
earned on food, clothing, or rent for the family. The scale exhibits reasonable
psychometric properties (a¼.669, mean interitem r¼.226).
Caregiver harsh discipline. (1) When you do something wrong, how often does
your (parent) ground you; (2) when you do something wrong, how often
does your (parent) lose (his or her) temper and yell at you; (3) when you
do something wrong, how often does your (parent) spank you; and (4) when
your (parent) disciplines you, how often does (he or she) hit you with a belt,
a paddle, or something else. The scale has nominally acceptable psycho-
metric properties (a¼.525, mean interitem r¼.239).
Monitoring in neighborhood. (1) If a group of neighborhood children were
skipping school and hanging out on a street corner, how likely is it that your
neighbors would do something like call the school or parents; (2) if some
children were spray-painting graffiti on a local building, how likely is it that
your neighbors would do something about it; and (3) if a child was showing
disrespect to an adult, how likely is it that people in your neighborhood
would scold that child or tell the child’s parents. The scale has reasonable
psychometric properties (a¼.611, mean interitem r¼.345).
Neighborhood crime. (1) Fight in your neighborhood in which a weapon like a
gun or knife was used; (2) a gang fight; (3) a sexual assault or rape; (4) a
robbery or mugging; and (5) a murder. The scale exhibits acceptable relia-
bility (a¼.735, mean interitem r¼.363).
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Appendix B
Table B1. Profiles of Group Membership Using the ‘‘Expected Value’’ Method.
Group 1 Group 2 Group 3
nMean SD Min Max nMean SD Min Max nMean SD Min Max
Delinquent peers 791 8.22 0.41 7 18 791 8.61 1.15 7 18 791 9.1 1.36 7 18
Racial discrimination 709 18.27 1.39 13 47 709 20.12 3.71 13 47 709 21.81 4.40 13 47
Self-control 804 24.96 1.27 16 41 804 26.02 2.81 16 41 804 26.77 3.01 16 41
Caregiver hostility 801 18.22 1.23 13 40 801 19.06 2.57 13 40 801 19.43 2.65 13 40
Caregiver warmth 797 31.92 1.12 9 36 797 31.07 2.81 9 36 797 30.41 3.13 9 36
Caregiver monitoring 811 14.28 0.58 4 16 811 13.63 1.42 4 16 811 13.18 1.61 4 16
Caregiver reinforcement of conformity 780 24.54 0.53 10 27 780 24.90 1.11 10 27 780 24.64 1.51 10 27
Caregiver harsh discipline 804 7.04 0.51 4 16 804 7.38 1.20 4 16 804 7.63 1.44 4 16
Monitoring in neighborhood 806 9.39 0.59 3 12 806 9.28 1.33 3 12 806 9.21 1.45 3 12
Neighborhood crime 784 6.11 0.43 5 15 784 6.46 1.24 5 15 784 6.81 1.43 5 15
Male 818 0.27 — 0 1 818 0.45 — 0 1 818 0.49 — 0 1
Group 4 Group 5
nMean SD Min Max nMean SD Min Max
Delinquent peers 791 8.80 0.63 7 18 791 9.29 0.52 7 18
Racial discrimination 709 22.02 2.49 13 47 709 24.21 1.96 13 47
Self-control 804 26.13 1.52 16 41 804 27.63 1.21 16 41
Caregiver hostility 801 19.19 1.5 13 40 801 20.08 1.26 13 40
Caregiver warmth 797 31.57 1.51 9 36 797 30.96 1.09 9 36
Caregiver monitoring 811 13.81 0.8 4 16 811 13.51 0.54 4 16
Caregiver reinforcement of conformity 780 24.83 0.73 10 27 780 24.56 0.59 10 27
Caregiver harsh discipline 804 7.54 0.73 4 16 804 8.04 0.66 4 16
Monitoring in neighborhood 806 9.29 0.8 3 12 806 9.19 0.59 3 12
Neighborhood crime 784 6.56 0.7 5 15 784 7.37 0.58 5 15
Male 818 0.4 — 0 1 818 0.58 — 0 1
24
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Acknowledgement
The authors want to thank the editor, Mike Maxfield, as well as the anonymous
reviewers for their helpful comments and suggestions. Gary Sweeten, Andrea Bor-
rego, Kina Harding, Laura Beckman, and Kara Hannula provided advice, guidance,
and feedback for which we are grateful.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, author-
ship, and/or publication of this article: This research was supported by the National Insti-
tute of Mental Health (MH48165 and MH62669) and the Center for Disease Control
(029136 -02). Additional funding for this project was provided by the National Institute
on Drug Abuse (DA021898 and 1P30DA027827) and the National Institute on Alcohol
Abuse and Alcoholism (2R01AA012768 and 3R01AA012768 -09S1).
Notes
1. We use the phrases ‘‘street code beliefs’’ and ‘‘adherence to the code,’’ or varia-
tions thereof interchangeably, and focus only on these beliefs. Behavioral adher-
ence to the code is not assessed. Focusing on behavioral comportment with the
street code may neglect or otherwise overlook key differences in these beliefs.
2. We do not specifically assess street and decent, although these notions are tied to
the code (Anderson 1999; 2002). This dichotomy clearly demarcates two patterns
of street code beliefs, one strong and one weak, though Anderson (1999; 2002)
explains that these beliefs exist on a continuum.
3. For model selection, the Bayesian information criterion (BIC) is used to maxi-
mize model fit (D’Unger et al. 1998). The BIC values are estimated using the fol-
lowing equation:
BIC ¼2log LðÞþlog nðÞk;
where Lis the maximum likelihood, nis the sample size, and kis the number of
parameters (Nagin, 2005). The best fitting model has the BIC value closest to zero.
4. By comparison, research on the stability of self-control finds correlations between
.4 and .7 over time (Burt, Simons, and Simons 2006; Hay and Forrest 2006).
5. Postestimation procedures were used to assess the accuracy of the group-based
modeling strategy beyond the BIC. First, the average posterior probability of group
assignment (AvePP) is reported. Nagin (2005:88) suggests a minimum threshold of
.7 for all groups. Present values ranged between .682 (group 4) and .855 (group 1).
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Second, the odds of correct classification (OCC) was examined, using the formula:
OCCj¼
AvePPj=ð1AvePPjÞ

^
pj=ð1^
pjÞ

:
The OCC is the ratio of the odds of correctly classifying individuals into
group jbased on the AvePP value, to the odds of correctly classifying individ-
uals into group jbased solely on the estimated proportion of the sample that
belongs in group j. Nagin (2005:88) suggests a rule of thumb of five when asses-
sing assignment accuracy. OCC’s in this model vary from just below Nagin’s
suggested threshold, 4.97 (group 2) to a high of 77.5 (group 1). The groups with
the lowest OCCs, groups 2 and 3, are the middle, largest groups, which may
explain why they have lower OCCs. A third diagnostic, entropy, is also used
(Ramaswamy et al. 1993). Entropy assesses the overall homogenous grouping
of individuals based on the posterior probabilities (Nagin 1999). Ranging from
0 to 1, a higher entropy number indicates better class separation (Petras and
Masyn 2010), using the following formula:
Entropy ¼1X
N
i¼1X
J
j¼1
ppijðlnðppij ÞÞ
NðlnðJÞÞ :
This model has an entropy value of .638. These postestimation procedures
suggest the overall model is adequate in its assessment of street code beliefs
over time.
6. This study’s group-based trajectory modeling approach is supported by the exis-
tence of developmental trajectory group 4. This distinct pattern would be
obscured in other methods (linear growth curve modeling and hierarchical linear
modeling) that assume a single developmental pattern.
7. An alternative classification strategy, the ‘‘expected value’’ method was also
explored. The distinguishing feature between the two methods reflects the expected
value method’s use of posterior probabilities as weights for group assignment. This
overcomes the weakness of the ‘‘classify and analyze’’ method, which cannot
account for the uncertainties of membership (i.e., ‘‘C and A’’ uses only maximum
posterior probabilities). Results from the expected value method are similar to those
from classify and analyze method, and are shown in the Appendix B.
8. The percentage of the sample assigned to trajectories following the inclusion of
risk variables remains fairly consistent with the base model. Of the 651 individ-
uals with complete risk factor information, 5.8 percent fall into group 1, 29 per-
cent fall into group 2, 43 percent are in group 3, 16.4 percent are in group 4, and
5.8 percent are in group 5.
9. We thank the anonymous reviewers for this suggestion.
26 Journal of Research in Crime and Delinquency
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Author Biographies
Richard K. Moule Jr., is a doctoral candidate in the School of Criminology and
Criminal Justice at Arizona State University. His research focuses on gangs and
deviant networks, criminological theory, the intersection of technology and crime,
and microsocial processes related to violence.
Callie H. Burt is an assistant professor in the School of Criminology and Criminal
Justice and a faculty affiliate of the School of Social Transformation at Arizona
State University. Her research takes a biopsychosocial approach to elucidate the
pathways through which social factors influence criminal offending and develop-
ment over the life course.
Eric A. Stewart is a professor of criminology at Florida State University. His
research focuses on contextual and individual dimensions of offending, victimiza-
tion, and criminal justice outcomes.
Ronald L. Simons is a distinguished research professor in the Department of
Sociology and the Center for Contextual Genetics at the University of Georgia. His
current research investigates the manner in which social factors become biologically
embedded and influence development and health across the life course.
Moule Jr. et al. 31
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... As such, research on individual level predictors of street code attitudes has explored demographics consistent with the individuals highlighted in Anderson's work in order to understand how these characteristics infl uence one's likelihood of embracing the street code. Many studies, however, have limited samples that focus on African Americans, younger individuals, and/or males ( Brezina, Agnew, Cullen, & Wright, 2004 ;Intravia, Wol , Stewart, & Simons, 2014 ;Moule, Burt, Stewart, & Simons, 2015 ). Although these studies may examine samples that are consistent with the specifi c demographics outlined by Anderson, it is more di cult to assess which demographic groups, if any, are most likely to adopt the street code belief system. ...
... Research shows that police satisfaction is not related to acquiring street code attitudes ( Intravia et al., 2017( Intravia et al., , 2018; however, those who have less respect for -or have negative attitudes toward -the police are more likely to hold street code attitudes ( Piquero et al., 2012 ;Keith & Gri ths, 2014 ). Regarding discrimination, studies support Anderson's notion that measures of racial discrimination is a key cause of adopting street code beliefs Moule et al., 2015 ). Further, a multilevel assessment focusing on racial discrimination from police personnel found that African Americans who perceived greater discrimination from the police were more likely to adopt street code beliefs, and this relationship was more pronounced in neighborhoods characterized by higher levels of violence ( Intravia et al., 2014 ). ...
... In their study, the authors found that being in a street family structure was positively related to adopting street code beliefs, whereas being in a decent family structure yielded no signifi cant e ect. Other studies that controlled for characteristics such as family structure (e.g., one versus two parent household), family socioeconomic status, parental supervision, and parental discipline have found little to no support that family and parenting factors are related to adopting the street code ( Brezina et al., 2004 ;Keith & Griffi ths, 2014 ;Moule et al., 2015 ). Anderson (1994Anderson ( , 1999 argues that the code of the street is a cultural orientation that is found in disadvantaged, urban locales that consist of primarily African American residents. ...
Chapter
Criminal or delinquent subcultures symbolize certain groups in society that have norms, values, or attitudes that are conducive to deviance, crime, and/or violence. Dating back to the works of the Chicago School in the early- and mid-twentieth century, the study of criminal and delinquent subcultures has long been of interest to sociologists and criminologists ( Thrasher, 1927 /1936; Cohen, 1955 ; Miller, 1958 ;). More recently, Elijah Anderson’s (1994 , 1999 ) code of the street thesis on criminal values, and violent attitudes in particular, has led to a renewed interest in understanding subcultures of violence. The purpose of this chapter is to provide an overview of the empirical work that focuses on the causes and consequences of streetcode attitudes. The chapter is divided into five main sections: (1) a brief history of criminal and delinquent subcultures, (2) an overview of the street code, how different family structures embrace this value system, and the characteristics of the code, (3) research on the causes of street code attitudes, (4) research on the consequences of those who embrace the code, and (5) a conclusion summarizing the street code research and providing suggestions for future avenues of inquiry.
... However, this developmental pattern has been questioned in recent quantitative analyses. Moule et al. (2015) suggested that individual patterns of street code development and stability included those that started high on street code agreement before precipitously declining at just the time Anderson suggests adherence should remain stable, if not increase. Similarly, Erickson et al. (2020) found decreasing street code adherence into early adulthood was the norm, not the exception, when analyzed as latent classes of agreement with street code attitudes. ...
... Both the code of the street and low self-control were posited to be informed by external factors of socialization and solidify and stabilize over time (Anderson 1999;Gottfredson & Hirschi, 1990). However, while street code attitudes and low self-control have been found to be related in multiple studies, and measures tend to correlate when repeated, neither have evinced the very high levels of stability originally theorized (Arnekelev et al., 1998;Erickson et al., 2020;Moule et al., 2015). We add to expanding literatures on the (in)stability and development of the code of the street and low self-control with a focus on how each informs the other across time. ...
... However, by late adolescence both Anderson (1999) and Gottfredson & Hirschi (1990) have suggested that street code adherence and low self-control should be fairly stable. Despite these theorists suggestions, previous research on street code adherence has provided evidence that decreases in street code adherence is more common in late adolescence than Anderson suggested Moule et al., 2015), and prior investigations have provided mixed support for the stability of low self-control (Burt, Simons, & Simons, 2006;Hay & Forrest, 2006;Na & Paternoster, 2012;Turner & Piquero, 2002). No prior research has examined the relative stability of street code adherence and low self-control and their reciprocal effects on each other over time. ...
Article
Full-text available
The code of the street and low self-control are prominent theories of crime. However, there is no research that examines if these criminogenic dispositions inform each other over time. We utilize the G.R.E.A.T. data to analyze the development of street code adherence and low selfcontrol longitudinally. We find a portion of the stability associated with street code adherence and low self-control to be a product of measurement, as evidenced by correlating error terms across waves. Additionally, we find low self-control to be related to increases in street code adherence especially in later waves and, to a lesser extent, we show effects of street code adherence on subsequent levels of low selfcontrol. We also discuss results from analyses split by race, gender, and neighborhood type. We discuss the theoretical implications of our findings and argue for the development and utility of a broad measure of criminal propensity.
... For example, residing in neighborhoods with higher levels of disorder, disadvantage, and violence corresponds with stronger beliefs in the street code (Intravia et al., 2014;Stewart & Simons, 2006). Similarly, negative experiences with authority figures are also associated with increased street code beliefs; exposure to hostile and abrasive parenting, as well as discrimination at the hands of law enforcement or other institutional authorities, promote these beliefs (Intravia et al., 2014;Moule et al, 2015;Stewart & Simons, 2006). Evidence similarly suggests that negative perceptions of police and feelings of hopelessness are associated with stronger beliefs in the street code (Drummond et al., 2011;Fine, Simmons, et al., 2020). ...
... Code of the Street Individual belief in the code of the street was assessed at the 12-month interview (i.e., wave 3) using an 8-item measure (Fine, Simmons, et al., 2020). The items overlap with measures commonly used in the study of the code of the street (e.g., Burgason et al., 2020;Moule et al., 2015;Stewart & Simons, 2006;Wolff et al., 2020). The scale used 4 items from the Weinberger Adjustment Inventory (Weinberger & Schwartz, 1990) and 4 items from the Peer Conflict Scale (Marsee et al., 2011) 1 that assess the core components of the street code, including "getting even" or escalation in response to disrespect or threats (e.g., "I threaten others when they do something wrong to me." "If someone tries to hurt me, I make sure I get even with them." ...
Article
A popular model of legal socialization contends that interactions with authority figures impact the internalization of pro-social values and beliefs, including authority legitimacy. Simultaneously, subcultural theories, including the code of the street, emphasize that negative contextual and experiential factors promote subcultural beliefs. The current study examines whether legal socialization processes are associated with the development of subcultural beliefs. Using longitudinal data from approximately 1,200 adolescent male offenders, we examined whether social experiences and contextual characteristics influence the development of individual beliefs in the code of the street through police legitimacy and legal cynicism. Consistent with theoretical expectations, the effects of deleterious neighborhood characteristics and negative interactions with authority figures were associated with beliefs in the code of the street through diminished police legitimacy and higher levels of cynicism toward the law. These findings provide evidence of the relevance of legal socialization processes for the development of subcultural norms.
... In the two decades since its elaboration, a sizable literature has examined the correlates and consequences of belief in the street code (e.g., Baron,2017;Hirschinger et al., 2002;McNeeley et al., 2018;Moule et al., 2015Moule et al., , 2019. The growing body of research on the street code has corresponded with a broader view and assessment of the code, the individuals who may adhere to it, and its relative influence on offending. ...
... All identified publications were scanned to ensure that they met the inclusion criteria and were not mistakenly identified. For instance, articles which conceptually or qualitatively described the code of the street (but did not quantitatively measure it; e.g., Anderson, 2008;Bennett & Frasier, 2000;Benoit et al., 2003;Brunson & Miller, 2009;Brunson & Stewart, 2006;Kubrin, 2005;Mitchell et al., 2017;Stewart et al., 2008;Urbanik & Haggerty, 2018) and studies which did not evaluate or provide sufficient statistical information on the relationship between street code beliefs and offending (e.g., Erickson et al., 2019;Martin et al., 2011;Mears et al., 2017;Moule et al., 2015;Simons et al., 2011;Stewart et al., 2006) were excluded, so only individual-level studies quantifying the relationship between the code of the street to offending were included. There are more effect sizes than total studies in the sample, as certain studies contained multiple results (e.g., certain studies included multiple analyses, such as using the street code to predict general offending and violent crime). ...
Article
Full-text available
Anderson’s Code of the Street thesis suggests that stronger belief in, and adherence to, subcultural “street code” norms increases the risk of criminal and aggressive behaviors, particularly among adolescents and young adults in urban communities. This study uses a meta-analysis to assess the overall relationship between individual belief in the street code and risk of offending. Effect sizes ( n = 38) from 20 unique studies produced a weighted correlation ( r) of .11, indicating a belief in the street code had a positive association with offending across all studies. The effect is strongest for violent offending (.13) and among samples comprised of adolescents (.14), as predicted by Anderson’s theory. Even after accounting for competing theoretical and established correlates of offending, modest effects of street code beliefs on offending remained. These findings indicate that overall, the street code is a more general theory than Anderson originally predicted. Directions for future research on the code are discussed.
... The patterns of development of street culture are mediated with exposure of structural disadvantages in neighborhood and peer. To test this thesis, Moule et al. (2015) employed FACHS data of 879 people by applying group-based trajectory modeling for analyzing developmental patterns and stability of individuals' street code beliefs through emerging adulthood. The age of the target youth, which included 45% female in both the first wave of data collection (1997) and last wave (2011) was between 10 and 12 years and 21 and 26 years old, respectively. ...
... This affects the generalizability of the approach and the understanding of street violence. (Anderson, 1999: 33 Moule et al. 2015). Zudem wurden mit wenigen Ausnahmen nur großstädtische Quartiere untersucht, obwohl nicht klar ist, ob der code of the street Urbanität erfordert oder nicht (Keith/Griffiths 2014). ...
... Other factors related to street code values include prior victimization (Brezina et al., 2004), perceived police discrimination (Intravia et al., 2014) as well as a general lack of respect for police (Piquero et al., 2012). Finally, and perhaps most relevant to the current study, street code values have been shown to be associated with levels of self-control as described by Gottfredson and Hirschi (1990), Intravia et al. (2018), McNeeley et al. (2018, Moule et al. (2015), and Piquero et al. (2012). For instance, a study of young adults demonstrated a significant association between low self-control and adherence to the Code of the Street after accounting for demographic characteristics, past involvement in violent behavior, and past victimization experiences (McNeeley et al., 2018), highlighting the role of individual-level personality characteristics in the adoption of the street code. ...
Article
Although Elijah Anderson’s code of the street thesis has received a great deal of scholarly attention, fewer studies have examined the characteristics associated with its adoption. Existing evidence is supportive of Anderson’s initial observations, however, less is known about the association between personality and emotional characteristics and adopting street code norms. The current study assesses the role of DeLisi and Vaughn’s difficult temperament index in the adoption of the street code among a sample of juvenile justice-involved youth. Results indicated youth with more difficult temperaments, characterized by lower levels of effortful control and higher levels of negative emotionality, were more likely to report greater street code adherence. Implications for juvenile justice policy and future research are discussed.
... To our knowledge, only urban ethnographers have found that Black males express their masculinity through the Cool Pose (Oliver 2003). However, scholars have examined the degree to which Blacks support the "code of the street" and whether their level of support predicts greater criminal behavior (Brezina et al. 2004;Intravia et al. 2014;Moule et al. 2015;Stewart, Schreck, and Simons 2006;Stewart, Simons, and Conger 2002). In addition, scholars have examined whether there is a gendering of violence and a gendering of violent attitudes among Blacks (Mullins, Wright, and Jacobs 2004). 2 However, this body of research tests only the intra-group variation in the degree to which Blacks support the use of retaliatory violence. ...
Article
Full-text available
Scholars argue that racial oppression uniquely causes Black males to construct a definition of their masculinity—the “Cool Pose”—that is different from White male masculinity. In this paper, using a nationally representative survey conducted in 2018, we examined whether young Black males were more likely than White male youths to feel greater pressure to conform to the Cool Pose. We analyzed six measures of the Cool Pose. We found no evidence that young Black males were more likely than White male youths to feel greater pressure to use violence if provoked. However, we found that young Black males were more likely than White male youths to feel greater pressure to be physically and emotionally strong, play sports, and to dominate or control others. We conclude that research needs to move beyond idiosyncratic accounts of Black males’ cultural adaptations in order to explicate the developmental processes that affect how Black males living in a systemically racist society express their masculinity.
... Finally, while scholars have demonstrated that beliefs of street culture are rather stable over time (Moule et al., 2015), our data are cross-sectional and limit the ability to draw causal conclusions. ...
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The convict code guides behaviors, beliefs, and interactions of incarcerated people by encouraging them to mind their own business, never back down, keep to themselves, and not get too close with correctional officers. Within communities, a similar subculture exists, termed the code of the street, which values respect, toughness, autonomy, and anti-police sentiments. Despite the overlap in their themes, these cultures have been theorized and analyzed independently. Yet, with 600,000 people entering and leaving prisons annually, it is possible that these seemingly distinct cultures blend together through the transition of people into and out of prison, raising theoretical and empirical questions about their independence. We examine the overlap between the convict code and code of the street in a representative sample of prisoners. Our results indicate that the code of the street and convict code are moderately correlated (r = 0.368 to r = 0.591), although the code of the street indicator overlaps mainly with the convict code dimension for masculinity. A sizeable group (47%) of individuals held converging beliefs regarding these two constructs. Convergence was explained primarily by years in prison, prison misconduct, gang membership, and neighborhood quality. Implications for an integrated model of culture are discussed.
... The CoS was assessed at the 6-month interview. Grounded in how extant research has operationalized the CoS (Matsuda et al., 2013;McNeeley & Hoeben, 2017;Moule, Burt, Stewart, & Simons, 2015;Wolff, Intravia, Baglivio, & Piquero, 2019), we selected four items from the Weinberger Adjustment Inventory (Weinberger & Schwartz, 1990) and four items from the Peer Conflict Scale (Marsee et al., 2011) that map onto similar items in other CoS indexes (e.g., "I threaten others when they do something wrong to me.", "If someone tries to hurt me, I make sure I get even with them.", and "When someone threatens me, I end up getting into a fight."). Regarding content validity, although this longitudinal study did not include the Stewart and Simons's (2010) CoS measure, our items mapped onto theirs. ...
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