A Multilevel Examination of the Code of the Street’s Relationship With Fear of Crime

Abstract

Research suggests that youths adopt the code of the street to reduce potential victimization, but it may increase actual risk of victimization. Because of this contradiction, the relationship between the code of the street and fear of crime may be an important component; however, fear of crime is an understudied component in the code of the street literature. This study conducts multilevel models to examine whether the code of the street is associated with perceived risk of victimization and emotional fear of crime. Individual belief in the code of the street was positively related to emotional fear of violent crime. At the neighborhood level, the code of the street was associated with higher perceived risk.

Keywords

code of the street fear of crime perceived risk of victimization

Introduction

Elijah Anderson’s (1999) “code of the street” hypothesis, which describes cultural adaptations arising in disadvantaged urban areas, is a popular explanation for violence. Many studies have applied Anderson’s observations to examine violence, both in regard to delinquency and victimization. In particular, a great deal of research suggests that youths adopt the code of the street and engage in violent behavior because of a common belief that risk for victimization will be reduced by doing so (Anderson, 1999; Baron, Forde, & Kennedy, 2001; Brookman, Bennett, Hochstetler, & Copes, 2011; Garot, 2007; Jacobs & Wright, 2006). However, actual victimization experiences appear to be more likely among those who believe in the code (Berg, Stewart, Schreck, & Simons, 2012; McNeeley & Wilcox, 2015a; Schreck, Ousey, Fisher, & Wilcox, 2012; Stewart, Schreck, & Simons, 2006).

Because of this contradiction, fear of crime may be an important component of the code of the street; in fact, a great deal of research indicates that fear of crime does not always match up with one’s actual risk for victimization. However, fear of crime remains an understudied component in the literature on this theory; to our knowledge, no prior studies have examined the relationship between the code of the street and fear of crime. This study attempts to address this gap in the literature by providing an initial examination into whether individual adoption of street values is associated with perceived risk of victimization and emotional fear of crime. We also explore whether neighborhood street codes have contextual effects on fear of crime, net of individual belief in the code. In particular, a theoretical framework derived from lifestyle-routine activities theory is used to develop hypotheses regarding potential relationships between the code of the street and fear of crime.

By examining the relationship between fear of crime and individual- and neighborhood-level code of the street, this study makes the following important contributions to the literature. First, by approaching the relationship between the code of the street and fear of crime from an opportunity perspective, our study may provide additional insight into the way that the code influences criminal opportunity at both the individual and neighborhood levels. Second, specifying the way that the code of the street relates to fear of crime may help to clarify the relationship between the code and victimization, as some of the existing work discussing victimization has actually examined code followers’ perceptions of their risk for victimization. Third, by focusing on violent attitudes consistent with the code of the street, we extend previous research demonstrating that involvement in crime and gang membership increase fear of crime (Gialopsos, 2011; Lalli, Savitz, & Rosen, 1977; Melde & Esbensen, 2009; Melde, Taylor, & Esbensen, 2009). Finally, few existing studies have examined the relationship between neighborhood cultural context and individual fear of crime; by doing so, we provide a better understanding of how community characteristics may influence individual perceptions and behavior.

Fear of Crime

Fear of crime is a multifaceted construct, encompassing two dimensions: cognitive assessments of safety (i.e., perception of victimization risk) and emotional reactions to the prospect of being victimized (see Ferraro & LaGrange, 1987). Research on the different dimensions of fear of crime shows that, although similar, these concepts are empirically distinct (e.g., Wilcox Rountree & Land, 1996b). Therefore, scholars interested in fear of crime now include separate measures that capture both perceived risk of victimization and emotional fear of crime. In this study, “perceived risk” refers to a cognitive assessment of one’s personal safety within his or her neighborhood, and “fear of crime” refers to emotional reactions to potential violent victimization. The literature on fear of crime has generally followed lifestyle-routine activities theory (see Cohen & Felson, 1979; Hindelang, Gottfredson, & Garofalo, 1978), assuming that fear of crime is rationally held by individuals who are likely to experience crime. Therefore, indicators of criminal opportunity identified by the theory have previously been used to explain fear of crime (see, for example, Wilcox Rountree & Land, 1996a).

Individual-level characteristics related to one’s exposure or proximity to motivated offenders have been linked to fear of crime. For example, several studies have shown that youths involved in delinquency have greater levels of perceived risk and/or emotional fear of crime (Gialopsos, 2011; Lalli et al., 1977; Melde & Esbensen, 2009; Savitz, Lalli, & Rosen, 1977); this relationship may be indirect through increased risk for victimization (Melde & Esbensen, 2009). Research also indicates that individuals with delinquent peers experience higher fear of crime (Gialopsos, 2011; Lalli et al., 1977; Miller, Gibson, Ventura, & Schreck, 2005; Schreck & Miller, 2003). Notably, Melde et al.’s (2009) study of fear of crime among gang members showed that, although gang membership was related to increased risk of victimization and greater perceived risk, it was related to lower levels of emotional fear of crime. They argued that gang members are expected to appear tough and fearless to maintain their place in the gang; therefore, gang members are expected to be able to control their emotional fear.

Indicators of potential vulnerability to victimization are also related to fear of crime. Notably, several studies have suggested that previous victimization is associated with increased perceived risk and emotional fear of crime (e.g., Ferraro, 1995; Garofalo, 1979; Lalli et al., 1977; Miethe & Lee, 1984; Parker & Ray, 1990; Wilcox Rountree & Land, 1996a; Wilcox, Quisenberry, & Jones, 2003). In addition, several sociodemographic variables that are believed to represent perceived vulnerability have been linked to fear of crime in the literature. For example, females (e.g., Ferraro, 1995; Ferraro & LaGrange, 1992; Hindelang, 1974; LaGrange & Ferraro, 1989; LaGrange, Ferraro, & Supancic, 1992; Skogan & Maxfield, 1981; Warr, 1990; Wilcox Rountree & Land, 1996a) and the elderly (e.g., Hindelang, 1974; Hindelang et al., 1978; Parker & Ray, 1990) report higher levels of fear of crime, even though their risk of victimization is relatively low. However, other studies suggest that younger individuals, who are at greater risk of victimization, are more fearful (e.g., Ferraro, 1995; LaGrange & Ferraro, 1989; Wilcox Rountree & Land, 1996a; Wilcox et al., 2003). Consistent with objective risk for victimization, fear of crime is higher among African Americans and other non-Whites (e.g., Ferraro, 1995; Hindelang, 1974; Hindelang et al., 1978; LaGrange & Ferraro, 1989; Parker & Ray, 1990; Skogan & Maxfield, 1981) and those with low-socioeconomic status (e.g., Hindelang, 1974; Hindelang et al., 1978; Skogan & Maxfield, 1981; Wilcox Rountree & Land, 1996a; Wilcox et al., 2003) and education (e.g., Ferraro, 1995; Hindelang, 1974).

Because crime and victimization are clustered across neighborhoods (e.g., Sampson & Wooldredge, 1987; Shaw & McKay, 1942), neighborhood characteristics can also demonstrate criminal opportunity. Therefore, certain community-level variables are associated with fear of crime. For example, fear of crime is higher in neighborhoods with signs of physical and social disorder (Ferraro, 1995; LaGrange et al., 1992; Skogan & Maxfield, 1981; Taylor & Covington, 1993). In addition, fear of crime is lower in communities with certain social characteristics, such as social ties and collective efficacy, that are related to the use of guardianship to prevent criminal behavior (Brunton-Smith, Jackson, & Sutherland, 2014; Gibson, Zhao, Lovrich, & Gaffney, 2002).

However, few existing studies have examined the extent to which community cultural context is associated with individual fear of crime and perceived risk of victimization. One exception is Merry’s (1981) study on urban dwellers’ perceptions of crime, which suggests that residents of neighborhoods with high levels of cultural diversity are more likely to experience anxiety and fear because they tend to misjudge and misinterpret their neighbors’ behavior (see also Covington & Taylor, 1991).

The Code of the Street

In The Code of the Street (1999), Elijah Anderson describes an oppositional subculture that arises in urban areas as a response to neighborhood conditions such as disadvantage, residential segregation, and high rates of crime and victimization. The code of the street provides residents of these communities with alternative methods of obtaining and maintaining respect. Importantly, respect is believed to be vital for self-protection in these communities, as those who are not respected are believed to be easy targets for potential offenders. Poor community relations with the police also further necessitates cultural strategies of self-protection among residents of these areas (see, for example, Intravia, Wolff, Stewart, & Simons, 2014).

Many residents of neighborhoods like those described by Anderson believe that it is important to engage in violent behavior, especially in response to any sign of disrespect, however slight, to demonstrate to the community that they are capable of self-protection (see Anderson, 1999; Brookman et al., 2011; Garot, 2007; Jacobs & Wright, 2006). Consistent with these observations, quantitative studies indicate that individuals who believe in the values provided by the code of the street—especially the importance of retaliation to insults or challenges—are more likely to engage in violent behavior (Berg et al., 2012; Felson, Liska, South, & McNulty, 1994; Markowitz & Felson, 1998; Matsuda, Melde, Taylor, Freng, & Esbensen, 2013; Ousey & Wilcox, 2005; Stewart & Simons, 2006, 2010). In contrast to these beliefs regarding self-protection, a growing body of research suggests that beliefs related to the code of the street are actually associated with higher risk for violent victimization (Berg et al., 2012; McNeeley & Wilcox, 2015a; Schreck et al., 2012; Stewart et al., 2006; but for opposite results see Baron et al., 2001). In addition, at the neighborhood level, risk for victimization is higher in communities with pervasive street cultures (Berg et al., 2012; McNeeley & Wilcox, 2015a).

The Code of the Street’s Potential Effects on Fear of Crime

The literature on the code of the street provides evidence that many elements of criminal opportunity may be associated with the code (see, for example, McNeeley & Wilcox, 2015a; McNeeley & Wilcox, 2015b). At both the individual and neighborhood levels, the code of the street may affect the opportunity structure surrounding one’s risk for victimization. In particular, the code of the street has been linked with the concept of target congruence (see Finkelhor & Asdigian, 1996), or the extent to which the characteristics of the victim arouse anger (target antagonism), demonstrates an inability to resist victimization (target vulnerability), or demonstrates qualities that offenders want to obtain or use (target gratifiability). According to McNeeley and Wilcox (2015b), belief in the street code may influence different components of target congruence in different ways: The code of the street may decrease risk of victimization by decreasing target vulnerability; alternatively, it may increase target antagonism, provoking potential offenders and increasing victimization risk. Because belief in the code of the street can either reduce or increase opportunity for victimization, it could be hypothesized that at both the individual and neighborhood levels, the code of the street is either positively or negatively related to fear of crime.

Target (in)vulnerability: The code of the street and decreased fear of crime

First, individual-level adherence to the code of the street may be associated with lower fear of crime. Because code followers engage in specific behavior to project the image of one who is capable of extreme violence and therefore not a suitable target for victimization, code-related values could serve as a protective factor against victimization. Regardless of whether the code of the street actually succeeds in this protective function, research suggests that the code of the street is related to one’s perceived target vulnerability. Qualitative studies demonstrate that individuals believe that failure to follow the code will leave them vulnerable to attacks (Anderson, 1999; Brookman et al., 2011; Garot, 2007; Jacobs & Wright, 2006). Because code followers believe that the code of the street will create an image of invulnerability and thereby reduce their risk of victimization, they may experience lower levels of perceived risk, which may also reduce emotional fear. Furthermore, following research on gang members (Melde et al., 2009), the code of the street may reduce emotional fear of crime because of its emphasis on fearlessness despite the risk of violence.

In addition to individual street code beliefs, neighborhood levels of street cultures could be expected to have similar contextual effects. The neighborhood’s subcultural orientation might reduce fear of crime by providing rules about how to avoid being targeted for violence (i.e., target suitability) and how to protect oneself (i.e., guardianship). The presence of such rules may be seen by individuals as a way to reduce their target suitability and increase guardianship. Therefore, the presence of a violent subculture in the community may cause a perception that one is at lower risk for victimization, especially if one follows the rules laid out by the subculture, and this may also alleviate emotional fear of crime.

Exposure to motivated offenders: The code of the street and increased fear of crime

In contrast, there are reasons to believe that fear of crime may be higher among those whose attitudes are in line with the code of the street. First, the code of the street is likely related to one’s exposure to motivated offenders. Anderson (1999) provides evidence that followers of the street code may purposely engage in risky activities or spend time in risky locations. Also, the behavior advocated by the code can be perceived by others as insulting or disrespectful, possibly provoking attacks due to target antagonism (see McNeeley & Wilcox, 2015a; Stewart et al., 2006). Therefore, the street code may frequently place followers in dangerous situations, which can increase perceived risk and/or emotional fear of crime. Second, the code of the street may be associated with higher levels of fear of crime due to its association with vulnerability. Although research suggests that some people believe that the street code reduces their target vulnerability, empirical evidence suggests that the street code is actually related to higher risk of victimization. Therefore, the code of the street may be associated with an increase in fear due to its influence on vulnerability and victimization (see Melde & Esbensen, 2009). Finally, because many of the behavioral decisions made by those who hold street code–related beliefs are chosen to avoid victimization, the code may make the possibility of being victimized more salient, thereby increasing individuals’ fear of crime.

In addition, the presence of a “code of the street” in one’s neighborhood may also have a positive contextual effect on fear of crime. Previous work has suggested that neighborhood characteristics—such as the presence of disorder—can act as a signal or cue that the community is dangerous, thereby increasing fear of crime (Lee & Ulmer, 2000; Wilcox et al., 2003). Social characteristics, such as the presence or strength of street codes, may work the same way; therefore, neighborhood street codes may serve as a signal that the community suffers from violence. Because adherence to the street code is largely viewed as a form of self-protection, residents of communities in which the code of the street flourishes are likely to believe that their neighborhoods are home to potential offenders, placing them at risk for victimization. This belief may increase perceived risk and emotional fear of crime.

Research Methods

Data and Sample

To examine the relationships described above, we use the Seattle Neighborhoods and Crime Survey (SNCS), which was collected in 2002-2003 (Matsueda, 2010). Prior studies on the code of the street have often focused on highly disadvantaged and segregated urban areas. Seattle, however, has moderate levels of disadvantage and racial segregation. Still, previous work has identified the presence of neighborhood codes of violence in Seattle and have linked these codes to neighborhood violence and individual victimization (e.g., Matsueda, Drakulich, & Kubrin, 2006; McNeeley & Wilcox, 2015b).

The survey was conducted by computer-assisted telephone interviewing (CATI) and includes individuals residing within all 123 of Seattle’s census tracts (for more information on the research, see Matsueda, 2010). The number of respondents residing in a census tract ranged from 13 to 50, with an average of about 29 individuals per tract. This study uses 3,759 valid responses from two sampling frames. The first sampling frame randomly selected two block groups in each census tract, and eight households were selected for each block group, resulting in a sample of 2,220 households. The second sampling frame oversampled within census blocks with high percentages of racial and ethnic minorities, resulting in an additional 1,539 households. Missing data were handled using listwise deletion, resulting in a sample size of 2,989 when predicting perceived risk, and 2,982 when predicting fear of violence.

Around half (50.8%) of the sample was female. The age of the respondents ranged from 18 to 103 years, with an average age of 49. Approximately two thirds (67.7%) of the respondents were homeowners. The majority (81.9%) of the respondents categorized themselves as White, whereas 6.6% of the sample was Asian, 3.7% was Black, 4.7% was Hispanic or Latino, 2.8% was Native American, and 3.3% identified as Other. This social demographic information is consistent with U.S. Census data collected for Seattle in 2000.

Dependent Variables

Following prior operationalization of fear of crime (e.g., Wilcox Rountree & Land, 1996b), we use measures of perceived risk and fear of violence to capture the cognitive and emotional dimensions of fear, respectively. Perceived risk was measured by asking individuals, “How safe is your neighborhood from crime and criminals?” The answers ranged from 1 (very safe) to 4 (very unsafe). Individuals who answered very safe and somewhat safe were recoded as 0. Individuals who answered somewhat unsafe and very unsafe were recoded as 1.

To measure emotional fear of crime, we use a survey question in which individuals were asked how often they “worry or think about being physically attacked by a stranger in the neighborhood.” The responses ranged from 1 (less than once a month) to 4 (every day). Individuals who answered once a week and every day were recoded as 1 and those who answered less than once a month and once a month were recoded as 0. See Table 1 for descriptive statistics of the dependent and independent variables.

Table 1.

Descriptive Statistics.

	n	M	SD	Minimum	Maximum
Dependent variables
Fear of violent crime	3,532	0.115	0.319	0.000	1.000
Perceived risk	3,548	0.164	0.370	0.000	1.000
Individual-level predictors
Do not back down	3,461	0.342	0.475	0.000	1.000
Confrontations okay	3,515	0.156	0.363	0.000	1.000
Violence okay	3,521	0.398	0.490	0.000	1.000
Tough image	3,519	0.081	0.273	0.000	1.000
Individual-level control variables
Age	3,528	49.425	16.136	18.000	103.000
Female	3,554	0.508	0.500	0.000	1.000
Black	3,554	0.037	0.188	0.000	1.000
Household income	3,203	2.210	0.672	1.000	3.000
Homeownership	3,550	0.677	0.468	0.000	1.000
Education	3,551	5.741	1.327	1.000	7.000
Violent victimization	3,536	0.904	4.526	0.000	103.000
Property victimization	3,550	0.765	1.536	0.000	24.000
Prior offending	3,496	0.267	0.442	0.000	1.000
Crime-related discussions	3,551	2.162	0.870	1.000	4.000
Local social ties	3,544	0.890	0.771	0.000	4.000
Neighborhood-level predictors
Neighborhood street code	123	0.030	0.225	−0.330	0.640
Unemployment rate	123	0.311	0.114	0.071	0.769
Residential instability	123	0.834	0.380	0.240	2.220
Racial heterogeneity	123	0.207	0.145	0.000	0.650
Neighborhood incivilities	123	1.402	0.205	1.048	2.117

Independent Variables

First, individual belief in the code of the street is measured using four single items¹ indicating the extent to which the respondent has internalized values favorable to violence or experienced an attenuation of traditional values that discourage violence. The first item indicates the norm of never backing down when disrespected or threatened: “If someone insults you or threatens you, you should turn the other cheek.” The second item similarly reflects the notion that avoiding violence is seen as weak: “Out in public, it is important to avoid confrontation with strangers to avoid violence.” The third item captures the degree to which individuals have internalized violence: “Violence is never justified under any circumstances.” The fourth item captures the concept that respect is earned through projecting a tough image²: “It is important for young men to have a reputation as someone who is tough and not to be messed with.” These items are consistent with those used in prior studies (e.g., Matsuda et al., 2013; Schreck et al., 2012; Stewart & Simons, 2006) in that they measure the respondents’ approval of the use of violence to gain respect. Responses to these four items ranged from 1 (strongly agree) to 4 (strongly disagree). Individuals who answered strongly agree or agree were coded as 0 and those who answered strongly disagree or disagree were coded as 1. Therefore, a score of 1 indicates belief in the street code.³

Second, to examine whether fear of crime is higher in communities with pervasive street cultures, a measure of neighborhood-level street code is included. Respondents were asked to what extent their neighbors would agree with the following six statements regarding the importance of violence for gaining respect in their community (Cronbach’s α = .864):

In this neighborhood, for young people to gain respect among their peers, they sometimes have to be willing to fight.

In this neighborhood, if a loved one is disrespected, people retaliate even if it means resorting to violence.

In this neighborhood, young men who own guns are often looked up to and respected.

In this neighborhood, residents believe that sometimes you have to resort to crime to get ahead.

In this neighborhood, parents teach their kids to fight back if they are insulted or threatened.

In this neighborhood, young men often project a tough or violent image to avoid being threatened with violence.

A confirmatory factor analysis (CFA) was conducted to examine the consistency of these six items; the results yielded factor loadings ranging from 0.66 to 0.76. We extracted the factor scores from the CFA and aggregated these scores to the census tract level to approximate the neighborhood-level street code.

Individual-Level Control Variables

We also include a number of well-established predictors of fear of crime as controls. First, violent victimization was measured by summing the number of times within the past 2 years the respondent experienced robbery, assault, and verbal threats of violence. Property victimization was measured by summing the number of times within the past 2 years the respondent experienced theft, auto theft, vandalism, and breaking and entering. To capture the transmission of crime-related information among neighbors, respondents were asked how often they “talk informally with people on the block about nearby crime problems” (see Bursik & Grasmick, 1993; Skogan & Maxfield, 1981). Responses ranged from 1 (never) to 4 (frequently). Prior offending is measured by asking respondents if they agreed that “I have never committed a crime for which I could be arrested.” Strongly agree and agree were recoded as 0, and strongly disagree and disagree were coded as 1. Individual local social ties was measured by asking respondents how many of their relatives or close friends lived in the neighborhood; the responses ranged from 1 (none) to 3 (a lot). An indicator of individuals’ local social ties was created by summing these two items.

Finally, we controlled for several sociodemographic characteristics. Income ranged from 1 (less than US$25,000) to 3 (more than US$75,000). Race was coded as 1 (Black) and 0 (all else). Gender was a dummy variable in which females were coded as 1. Age in years is a continuous variable ranging from 18 to 103. Education was coded from 1 (eighth grade or less) to 7 (graduate/professional school). We also include a dichotomous measure of housing tenure in which homeowners are coded as 1.

Neighborhood-Level Control Variables

Neighborhood-level indicators that are expected to affect individual perceptions of crime were aggregated to explore neighborhood effects. First, neighborhood incivilities is measured using five questions (Cronbach’s α = .742) indicating the extent to which residents feel that their neighborhoods contain problematic amounts of the following types of physical and social disorder: litter, graffiti, abandoned buildings, noisy neighbors, and rowdy teenagers. The answer set ranged from 1 (not a problem) to 3 (a big problem). An addictive scale was created by summing across these five items; the scale was then averaged within census tracts to measure the extent to which communities suffered from social and physical incivilities. Higher scores on this scale indicated high levels of perceived community incivilities.

In addition, measures of social disorganization were included (e.g., Shaw & McKay, 1942). We were unable to utilize information from the U.S. Census because the official census tract codes and the survey census tract identifiers are unmatchable. Therefore, these items are estimated by aggregating individual survey responses to the census tract level. First, residential instability was measured by the average number of times the respondents within a census tract reported moving in the previous 5 years. Second, racial heterogeneity was calculated as $1 - \sum p_{i}^{2}$ , where p_i refers to the proportion of respondents from each racial group (Lieberson, 1969). Finally, to control for neighborhood social economic status, the proportion of unemployed respondents in the census tract is used to measure the neighborhood unemployment rate.

Analytical Strategy

Because the data are multilevel in nature, with respondents clustered within census tracts, multilevel modeling is used. Compared with traditional regression models, multilevel modeling improves statistical estimation of individual effects by adjusting the standard errors of the coefficients of the neighborhood-level factors. In addition, multilevel modeling partitions residual variance into between-neighborhood and within-neighborhood components, allowing us to simultaneously examine the effects of individual belief in the code and neighborhood-level street code on fear of crime (see Raudenbush & Bryk, 2002). We conduct logistic regression models due to the dichotomous nature of the outcome variables. Unconditional, intercept-only models (not presented here) revealed that a significant amount of variation in individual perceived risk (variance component = 1.002, p < .001) and fear of violence (variance component = 0.409, p < .001) exists at the neighborhood level.⁴

Because centering of predictor variables did not have substantive implications in this study, we kept the original metric of all the variables in all analyses. Multicollinearity diagnostics suggested that neighborhood street culture and neighborhood incivilities were highly correlated (r = .82; tolerance for neighborhood incivilities = 0.273); however, we chose to control for neighborhood incivilities in the main analyses despite this issue due to its theoretical importance in predicting fear of crime.⁵

Results

Perceived Risk

Results from the hierarchical logistic regression model predicting perceived risk are presented in Table 2. The belief that violence is sometimes justified was positively associated with perceived risk of victimization. The odds ratio associated with perceived risk was 27.8% higher for those who believed that violence is sometimes justified. None of the other individual-level street code beliefs were statistically associated with perceived risk. At the neighborhood level, the presence of a code of violence was positively associated with perceived risk; residents of neighborhoods with stronger street cultures were more likely to categorize their neighborhoods as unsafe than were those living in neighborhoods without strong oppositional cultures.

Table 2.

Hierarchical Logistic Regression Model Predicting Perceived Risk.

	Coefficient	SE	Odds ratio
Level 1
Intercept	−6.500	0.772	—
Do not back down	0.163	0.117	1.178
Confrontations okay	−0.090	0.153	0.914
Violence okay	0.245*	0.117	1.278
Tough image	−0.115	0.223	0.891
Age	−0.004	0.004	0.996
Female	0.413**	0.119	1.512
Black	0.003	0.258	1.003
Household income	0.083	0.098	1.087
Homeownership	−0.662**	0.140	0.516
Education	0.023	0.045	1.023
Violent victimization	0.036**	0.012	1.037
Property victimization	0.290***	0.035	1.337
Prior offending	0.151	0.125	1.163
Crime-related discussions with neighbors	0.425***	0.066	1.530
Local social ties	−0.260**	0.078	0.771
Level 2
Neighborhood street code	1.385**	0.400	3.994
Unemployment rate	−0.401	0.538	0.670
Residential mobility	−0.143	0.172	0.867
Racial heterogeneity	−0.057	0.441	0.944
Neighborhood incivilities	2.584***	0.441	13.247
Variance component	4.70E−18	0.000

Note. Results are based on 2,989 individuals within 123 census tracts.

†

p < .1. *p < .05. **p < .01. ***p < .001.

In addition, consistent with prior research, females were more likely to believe that their neighborhoods were unsafe. Prior violent victimization, property victimization, and crime-related discussions with neighbors were positively related to perceived risk. Homeownership and individual social ties were negatively associated with perceived risk. At the neighborhood level, the presence of physical and social incivilities was positively related to the perception that one’s community is unsafe.

Fear of Violence

Table 3 provides the results from the hierarchical logistic regression model predicting fear of violence. Individuals who believe that it is wrong to back down after an insult or that violence is sometimes justified worried more frequently about being physically attacked. The odds ratio associated with frequent fear of violence was 42.1% higher for those who believed that it is wrong to back down after an insult and 34.8% higher for those who believed that violence is sometimes justified. In addition, although the relationship was not statistically significant, emotional fear of violence was higher among those who believed that it is important to have a tough reputation. The presence of a neighborhood street code, however, was not statistically associated with fear of violence when controlling for other neighborhood characteristics.

Table 3.

Hierarchical Logistic Regression Model Predicting Fear of Violence.

	Coefficient	SE	Odds ratio
Level 1
Intercept	−5.183	0.917	—
Do not back down	0.351**	0.129	1.421
Confrontations okay	−0.208	0.175	0.812
Violence okay	0.298*	0.132	1.348
Tough image	0.397^†	0.225	1.488
Age	−0.009*	0.005	0.991
Female	1.066***	0.141	2.902
Black	−0.376	0.328	0.686
Household income	−0.226*	0.109	0.798
Homeownership	−0.530***	0.158	0.589
Education	−0.081^†	0.049	0.922
Violent victimization	0.023*	0.010	1.024
Property victimization	0.091**	0.033	1.095
Prior offending	0.307*	0.142	1.359
Crime-related discussions with neighbors	0.439***	0.074	1.551
Local social ties	−0.055	0.084	0.946
Level 2
Neighborhood street code	−0.030	0.499	0.970
Unemployment rate	0.362	0.640	1.436
Residential instability	0.545**	0.209	1.724
Racial heterogeneity	0.317	0.546	1.373
Neighborhood incivilities	1.439**	0.542	4.216
Variance component	0.071	0.070

Note. Results are based on 2,982 individuals within 123 census tracts.

†

p < .1. *p < .05. **p < .01. ***p < .001.

Six of the individual-level control variables were significantly related to fear of violence. Females and those who had committed prior criminal offenses reported more frequently being fearful of violent crime than did males or those who had never committed a crime. Violent victimization, property victimization, and crime-related discussions with neighbors were positively related to fear of violence. Individuals with higher household incomes and those who owned their homes were less likely to report fear of violence. Finally, at the neighborhood level, residential instability and neighborhood incivilities were positively related to fear of violence.

Discussion

Previous work has established an important role of the code of the street in the etiology of offending and victimization. However, research has not applied the code of the street toward understanding fear of crime. Our study extends prior work on neighborhood culture by examining the code of street (Anderson, 1999) at both the individual and neighborhood levels in an initial attempt to understand its relationship with perceived risk of victimization and emotional fear of crime. Emotional fear of crime was positively associated with three of the four individual-level code-related beliefs, while perceived risk of victimization was positively related with one—the belief that violence is sometimes justified. In addition, residents of neighborhoods in which the code of the street is more pervasive were more likely to perceive their neighborhoods as unsafe, even when controlling for other neighborhood characteristics that are likely to influence fear of crime.

These results have several theoretical implications. First, it was hypothesized that, because the code of the street discourages individuals from avoiding risky situations and emphasizes the need to stay vigilant due to imminent violent encounters, street code values may act as a proxy for exposure or proximity to motivated offenders, thereby increasing fear of crime. As expected, three of the street code values we examined had significant or near-significant associations with emotional fear of crime, and one (the belief that violence is sometimes justified) was also significantly associated with perceived risk. However, Anderson (1999) describes the code of the street as partially arising from individuals’ fear of victimization and the belief that they cannot rely on the police for protection (see also Black, 1983). Therefore, while we find an effect of street code beliefs on levels of fear, it is possible that this relationship is reciprocal in nature. This potentially more complex relationship between the code of the street and fear of crime is difficult to detect with cross-sectional data such as that used in the present study; therefore, longitudinal studies examining the association between fear and the code are needed to extend work on this topic.

Our alternative hypothesis was that the code of the street would be associated with lower fear of crime. Previous research has demonstrated that code followers believe that the code of the street is necessary for protection against victimization (Anderson, 1999; Brookman et al., 2011; Garot, 2007; Jacobs & Wright, 2006); therefore, adopting these values may reduce perceived risk or emotional fear of crime. Similarly, a study on gang members showed that even though risk of victimization was higher, gang membership was negatively associated with emotional fear of crime (Melde et al., 2009). Our results do not support this hypothesis.

Second, our results showed different patterns when examining perceived risk and emotional fear of crime. We found a contextual effect of neighborhood street codes on perceived risk of victimization or the extent to which respondents believed their communities were safe from crime and criminals. Our findings may indicate that neighborhood street culture serves as a signal demonstrating the potential dangerousness of the neighborhood⁶; this is consistent with research showing contextual effects of the code of the street on victimization (Berg et al., 2012; McNeeley & Wilcox, 2015a). However, based on our results, this signaling did not appear to translate into increased emotional fear of crime. Rather, emotional fear was more closely related to individual belief in the code of the street. These attitudes appear to be less consistently related to cognitive assessments regarding the riskiness of one’s community, but may instead be associated with one’s feelings about crime or victimization on an emotional level. If these findings are replicated in future studies, more theoretical work is needed to understand these differences.

Third, because the items measuring code-related beliefs included in the data had low internal reliability, it is possible that there are different aspects of the code of the street, and these aspects may have different relationships with fear of crime. There is debate in the literature regarding whether the beliefs provided by the code of the street are truly internalized by its followers or whether they are situationally adopted (Sampson & Bean, 2006; Sampson & Wilson, 1995); the low reliability between measures may suggest a situational nature of the code. The situational nature of the code of the street may have implications for understanding the relationship between the code and fear of crime. According to our findings, particular aspects of the street code appear to be more strongly associated with fear than others. In particular, only one of the four variables we included to proxy the street code—the belief that violence is sometimes justified—was significantly associated with both perceived risk and emotional fear of crime. More research is needed to better understand the extent to which the code of the street is a single unified concept or a set of tools that can be individually selected situationally.

Fourth, this study contributes to the fear of crime scholarship by examining how cultural adaptation and cultural context are related to fear of crime. The extant literature on fear of crime has not given much attention to the relationship between culture and fear of crime. Those that have acknowledged culture have examined racial and ethnic diversity, noting that ethnic groups often differ culturally. For example, prior research suggests that neighborhood cultural diversity influences individuals’ fear of crime (see Lane & Meeker, 2000; Merry, 1981). In this study, the presence of violent subcultures within a community had a positive contextual effect on perceived risk of victimization. Future research should examine other types of cultural influences to better understand how they contribute to perceptions of crime within the community.

Our findings also have potential implications for policy and practice. Scholars have previously noted the importance of understanding violent subcultures in disadvantaged areas to reduce their harmful effects on community residents’ health—in regard to injury that results from violent victimization (see, for example, Stewart, Schreck, & Brunson, 2008). Because our findings suggest a positive relationship between the code of the street and fear of crime, there may be additional harmful effects of the code of the street beyond those associated with victimization. There is evidence that fear of crime is related to poor physical and mental health due to consequences of fear such as stress and curtailed physical activity (e.g., Jackson & Stafford, 2009; Stafford, Chandola, & Marmot, 2007). Therefore, our findings, if replicated, suggest that reducing overall reliance on the code of the street may be more beneficial for health and quality of life than previously estimated. Several suggestions for reducing reliance on the code of the street have previously been discussed, such as restorative justice, community or problem-oriented policing, and bystander intervention (see McNeeley & Wilcox, 2015a; Stewart et al., 2008).

Although this study provides initial insights regarding the relationship between the code of the street and fear of crime, there are some limitations of this study that are worth noting. First, because of the cross-sectional nature of the data, our results demonstrate associations between these variables rather than causal relationships. To disentangle the causal relationships between the code of the street and fear of crime, researchers should pursue longitudinal research. Second, we recognize that some of the neighborhood-level measures used in our study need further improvement. Because we were unable to match the randomly generated census identifiers in the SNCS data with official census tract numbers, census-based contextual variables such as neighborhood concentrated disadvantage were not available for inclusion in the statistical analysis. Third, the results of this study are limited to a single city. It is unknown whether our theoretical propositions will hold in other places, especially in cities with more disadvantaged urban areas or greater crime problems than Seattle. Finally, scholars have recommended more advanced measures of fear of crime than were available in the survey data. For example, Farrall, Jackson, and Gray (2009) suggested that scholars interested in measuring fear of crime should use questions that capture the intensity and frequency of fear.

It is well documented in the psychology literature that a place’s culture shapes individual emotion, cognition, and behavior (e.g., Markus & Kitayama, 1991). This study extends prior studies on fear of crime by providing a preliminary investigation of the extent to which beliefs in the street code and neighborhood street code is associated with individual fear of crime, both in terms of cognitive assessment of neighborhood safety and emotional reactions to potential violent victimization. Despite the limitations discussed above, we believe that this study addresses an important research gap in the literature on fear of crime and the literature on the code of the street. Additional research on neighborhood culture, individual internalization of the values provided by the code of the street, and fear of crime will enhance the development of our understanding of fear of crime.

Footnotes

Author Contributions

The authors contributed equally to this work.

Declaration of Conflicting Interests

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

Funding

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

Notes

Author Biographies

Susan McNeeley is a visiting assistant professor in the Department of Criminal Justice at University of Arkansas at Little Rock. Her research focuses on developing and testing theories of crime and victimization.

Yue Yuan is a doctoral candidate in the Department of Criminal Justice at Indiana University-Bloomington. His research focuses on perceptions of crime, victimization, and juvenile delinquency.

References

Anderson

(1999). Code of the street: Decency, violence, and the moral life of the inner city. New York, NY: W.W. Norton.

Baron

S. W.

Forde

D. R.

Kennedy

L. W.

(2001). Rough justice: Street youth and violence. Journal of Interpersonal Violence, 16, 662-678.

Berg

M. T.

Stewart

E. A.

Schreck

C. J.

Simons

R. L.

(2012). The victim-offender overlap in context: Examining the role of neighborhood street culture. Criminology, 50, 359-390.

Black

(1983). Crime as social control. American Sociological Review, 48, 34-45.

Brookman

Bennett

Hochstetler

Copes

(2011). The “code of the street” and the generation of street violence in the UK. European Journal of Criminology, 8, 17-31.

Brunton-Smith

Jackson

Sutherland

(2014). Bridging structure and perception: On the neighborhood ecology of beliefs and worry about violent crime. British Journal of Criminology, 54, 503-526.

Bursik

Grasmick

(1993). Neighborhoods and crime: The dimensions of effective community control. New York, NY: Lexington Books.

Cohen

L. E.

Felson

(1979). Social change and crime rate trends: Routine activity approach. American Sociological Review, 44, 588-608.

Covington

Taylor

R. B.

(1991). Fear of crime in urban residential neighborhoods: Implications of between- and within-neighborhood sources for current models. The Sociological Quarterly, 32, 231-249.

10.

Farrall

S. D.

Jackson

Gray

(2009). Social order and the fear of crime in contemporary times. New York, NY: Oxford University Press.

11.

Felson

R. B.

Liska

A. E.

South

S. J.

McNulty

T. L.

(1994). The subculture of violence and delinquency: Individual vs. school contextual effects. Social Forces, 73, 155-173.

12.

Ferraro

K. F.

(1995). Fear of crime: Interpreting victimization risk. New York: State University of New York Press.

13.

Ferraro

K. F.

LaGrange

R. L.

(1987). The measurement of fear of crime. Sociological Inquiry, 57, 70-101.

14.

Ferraro

K. F.

LaGrange

R. L.

(1992). Are older people most afraid of crime? Reconsidering age differences in fear of victimization. Journal of Gerontology, Series B: Psychological Sciences & Social Sciences, 47, S233-S244.

15.

Finkelhor

Asdigian

N. L.

(1996). Risk factors for youth victimization: Beyond a lifestyles/routine activities theory approach. Violence and Victims, 11, 3-20.

16.

Garofalo

(1979). Victimization and the fear of crime. Journal of Research in Crime & Delinquency, 16, 80-97.

17.

Garot

(2007). Non-violence in the inner-city: “Decent” and “street” as strategic resources. Journal of African American Studies, 10, 94-111.

18.

Gialopsos

B. M.

(2011). For whom the bell tolls: Explaining students’ fear of crime and perceptions of risk (Doctoral dissertation). School of Criminal Justice, University of Cincinnati, OH.

19.

Gibson

C. L.

Zhao

Lovrich

N. P.

Gaffney

M. J.

(2002). Social integration, individual perceptions of collective efficacy, and fear of crime in three cities. Justice Quarterly, 19, 537-563.

20.

Hindelang

M. J.

(1974). Public opinion regarding crime, criminal justice, and related topics. Journal of Research in Crime & Delinquency, 11, 101-116.

21.

Hindelang

M. J.

Gottfredson

M. R.

Garofalo

(1978). Victims of personal crime: An empirical foundation for a theory of personal victimization. Cambridge, MA: Ballinger.

22.

Intravia

Wolff

K. T.

Stewart

E. A.

Simons

R. L.

(2014). Neighborhood-level differences in police discrimination and subcultural violence: A multilevel examination of adopting the code of the street. Journal of Crime & Justice, 37, 42-60.

23.

Jackson

Stafford

(2009). Public health and fear of crime: A prospective cohort study. British Journal of Criminology, 49, 832-847.

24.

Jacobs

B. A.

Wright

(2006). Street justice: Retaliation in the criminal underworld. Cambridge, UK: Cambridge University Press.

25.

LaGrange

R. L.

Ferraro

K. F.

(1989). Assessing age and gender differences in perceived risk and fear of crime. Criminology, 27, 697-719.

26.

LaGrange

R. L.

Ferraro

K. F.

Supancic

(1992). Perceived risk and fear of crime: Role of social and physical incivilities. Journal of Research in Crime & Delinquency, 29, 311-334.

27.

Lalli

Savitz

L. D.

Rosen

(1977). City life and delinquency: Summary report. Washington, DC: National Institute for Juvenile Justice and Delinquency Prevention, Office of Juvenile Justice and Delinquency Prevention.

28.

Lane

Meeker

J. W.

(2000). Subcultural diversity and the fear of crime and gangs. Crime & Delinquency, 46, 497-521.

29.

Lee

M. S.

Ulmer

J. T.

(2000). Fear of crime among Korean Americans in Chicago communities. Criminology, 38, 1173-1206.

30.

Lieberson

(1969). Measuring population diversity. American Sociological Review, 34, 850-862.

31.

Markowitz

F. E.

Felson

R. B.

(1998). Social-demographic attitudes and violence. Criminology, 36, 117-138.

32.

Markus

H. R.

Kitayama

(1991). Culture and the self: Implications for cognition, emotion, and motivation. Psychological Review, 98, 224-253.

33.

Matsuda

K. N.

Melde

Taylor

T. J.

Freng

Esbensen

(2013). Gang membership and adherence to the “code of the street.” Justice Quarterly, 30, 440-468.

34.

Matsueda

R. L.

(2010). Seattle Neighborhoods and Crime Survey, 2002-2003. Retrieved from https://dx-doi-org.web.bisu.edu.cn/10.3886/ICPSR28701.v1

35.

Matsueda

R. L.

Drakulich

Kubrin

C. E.

(2006). Race and neighborhood codes of violence. In Peterson

R. D.

Krivo

L. J.

Hagan

(Eds.), The many colors of crime: Inequalities of race, ethnicity, and crime in America (pp. 199-220). New York: New York University Press.

36.

McNeeley

Wilcox

(2015a). Street codes, routine activities, neighbourhood context, and victimization. British Journal of Criminology, 55, 921-943.

37.

McNeeley

Wilcox

(2015b). The code of the street and violent versus property crime victimization. Violence and Victims, 30, 1049-1067.

38.

Melde

Esbensen

(2009). The victim-offender overlap and fear of in-school victimization: A longitudinal examination of risk assessment models. Crime & Delinquency, 55, 499-525.

39.

Melde

Taylor

T. J.

Esbensen

(2009). “I got your back”: An examination of the protective function of gang membership in adolescence. Criminology, 47, 565-594.

40.

Merry

S. E.

(1981). Urban danger: Life in a neighborhood of strangers. Philadelphia, PA: Temple University Press.

41.

Miethe

T. D.

Lee

G. R.

(1984). Fear of crime among older people: A reassessment of the predictive power of crime-related factors. The Sociological Quarterly, 25, 397-415.

42.

Miller

J. M.

Gibson

Ventura

H. E.

Schreck

C. J.

(2005). Reaffirming the significance of context: The Charlotte School Safety Program. Journal of Criminal Justice, 33, 477-485.

43.

Ousey

G. C.

Wilcox

(2005). Subcultural values and violent delinquency: A multilevel analysis in middle schools. Youth Violence and Juvenile Justice, 3, 3-22.

44.

Parker

K. D.

Ray

M. C.

(1990). Fear of crime: An assessment of related factors. Sociological Spectrum, 10, 29-40.

45.

Raudenbush

S. W.

Bryk

A. S.

(2002). Hierarchical linear models: Applications and data analysis methods. Thousand Oaks, CA: Sage.

46.

Sampson

R. J.

Bean

(2006). Cultural mechanisms and killing fields: A revised theory of community-level racial inequality. In Peterson

R. D.

Krivo

L. J.

Hagan

(Eds.), The many colors of crime (pp. 8-35). New York: New York University Press.

47.

Sampson

R. J.

Wilson

W. J.

(1995). Toward a theory of race, crime and urban inequality. In Hagan

Peterson

R. D.

(Eds.), Crime and inequality (pp. 37-57). Redwood City, CA: Stanford University Press.

48.

Sampson

R. J.

Wooldredge

J. D.

(1987). Linking the micro- and macro-level dimensions of lifestyle-routine activities and opportunity models of predatory victimization. Journal of Quantitative Criminology, 3, 371-393.

49.

Savitz

L. D.

Lalli

Rosen

(1977). City life and delinquency—Victimization, fear of crime, and gang membership. Washington, DC: National Institute for Juvenile Justice and Delinquency Prevention, Office of Juvenile Justice and Delinquency Prevention.

50.

Schreck

C. J.

Miller

J. M.

(2003). Sources of fear of crime at school: What is the relative contribution of disorder, individual characteristics, and school security? Journal of School Violence, 2, 57-79.

51.

Schreck

C. J.

Ousey

Fisher

B. S.

Wilcox

(2012). Examining what makes victims of violence unique: Extending statistical methods for studying specialization to the analysis of crime victims. Journal of Quantitative Criminology, 28, 651-671.

52.

Shaw

C. R.

McKay

H. D.

(1942). Juvenile delinquency and urban areas: A study of rates of delinquents in relation to differential characteristics of local communities in American cities. Chicago, IL: University of Chicago Press.

53.

Skogan

W. G.

Maxfield

M. G.

(1981). Coping with crime: Individual and neighborhood reactions. Beverly Hills, CA: Sage.

54.

Snijders

T. A. B.

Bosker

R. J.

(2012). Multilevel analysis: An introduction to basic and advanced multilevel modeling (2nd ed.). London, England: Sage.

55.

Stafford

Chandola

Marmot

(2007). Association between fear of crime and mental health and physical functioning. American Journal of Public Health, 97, 2076-2081.

56.

Stewart

E. A.

Schreck

C. J.

Brunson

R. K.

(2008). Lessons of the street code: Policy implications for reducing violent victimization among disadvantaged citizens. Journal of Contemporary Criminal Justice, 24, 137-147.

57.

Stewart

E. A.

Schreck

C. J.

Simons

R. L.

(2006). “I ain’t gonna let no one disrespect me”: Does the code of the street reduce or increase violent victimization among African American adolescents? Journal of Research in Crime & Delinquency, 43, 427-458.

58.

Stewart

E. A.

Simons

R. L.

(2006). Structure and culture in African-American adolescent violence: A partial test of the code of the street thesis. Justice Quarterly, 23, 1-33.

59.

Stewart

E. A.

Simons

R. L.

(2010). Race, code of the street, and violent delinquency: A multilevel investigation of neighborhood street culture and individual norms of violence. Criminology, 48, 569-605.

60.

Taylor

R. B.

Covington

(1993). Community structural change and fear of crime. Social Problems, 40, 374-397.

61.

Warr

(1990). Dangerous situations: Social context and fear of victimization. Social Forces, 68, 891-907.

62.

Wilcox Rountree

Land

K. C

. (1996a). Burglary victimization, perceptions of crime risk, and routine activities: A multilevel analysis across Seattle neighborhoods and census tracts. Journal of Research in Crime & Delinquency, 33, 147-180.

63.

Wilcox Rountree

Land

K. C

. (1996b). Perceived risk versus fear of crime: Empirical evidence of conceptually distinct reactions in survey data. Social Forces, 74, 1353-1376.

64.

Wilcox

Quisenberry

Jones

(2003). The built environment and community crime risk interpretation. Journal of Research in Crime & Delinquency, 40, 322-345.