Gang Membership Risk Factors for Eighth-Grade Students

Gang Membership Risk Factors for Eighth-Grade Students

Nonpartisan Education Review / Articles, Volume 9, Number 1

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Gang Membership Risk Factors for Eighth-Grade Students



James Martinez, Jeremy Tost, Larry Hilgert, & Tracy Woodard-Meyers,*

Valdosta State University


 

 

 

 

 

Abstract


The purpose of this study is to identify the major risk factor domains for gang membership and the relationships of these risk factors to eighth grade students. The domains of risk factors include: individual characteristics, peer group influences, family conditions, school experiences and the community context, along with demographic information obtained from the Student Gang Survey items. Through logistic multiple regression, risk factors associated with school, peer, community-neighborhood, and family were used to predict gang membership. Demographic data were also used as predictor variables. Results indicated that an increase in Community-Neighborhood Risk was associated with a decrease in joining a gang. Non-significant findings for Peer Risk, School Risk, Family Risk and demographic variables are additionally discussed. The current research identifies issues which middle school youth encounter in a county setting; provides a homegrown report to assist stakeholders (administrators, teachers, parents, students, and law enforcement) in identifying locally relevant risk factors of gang behavior; and substantiates risk factors for gang membership proliferation in those neighborhoods with no recently documented history of gangs.

 

Key words: Gang risk factor domains, gang membership, cliques, middle school

 

 

 

 

Introduction

It is not sufficient to say that gang members come from lower-income areas, from minority populations, or from homes more often characterized by absent parents or reconstituted families. It is not sufficient because most youths from such areas, such groups, and such families do not join gangs.                                                                          --Malcolm Klein, 1995

 

The term “gang” often sets a tone of negativity related to crime, violence, and fear. Are school personnel doing all they can to redirect potential gang members? Are educators properly equipped to assist young people in avoiding a possible life of crime, drugs, and violence? A better understanding of risk factors for gang membership proliferation in neighborhoods with no recently documented history of gangs could help identify those students most likely to engage in negative behaviors and could lead to corrective measures. Early intervention could alter the future for many children (Klein & Maxson, 2008). In an effort to prevent and ameliorate negative outcomes, this study identifies the most prominent predictors of “gang” and “clique” membership for middle grade students.

Due to the sensitivity associated with school and community research, student survey materials, as mandated by the school district, asked students about their current and past involvement in “cliques” with the word “gangs” beside it, and then asked for further detail about the involvement of their peers (e.g., Curry, Decker, & Egley, 2002; Spergel, 1995). In this manuscript, the term “clique” is used with the word “gang” referring to neighborhood or street-based youth groups. In concurrence with Bjerregaard (2002), Curry, Decker, & Egley, (2002), Esbensen, Winfree, He, & Taylor (2001), Fleisher (2006), Papachristos (2006), Starbuck, Howell, & Lindquist (2001), and Valdez (2007), the authors argue that the differences of U.S. gang culture and area youth culture that blend with American gang ideals in the formation of a local youth gang definitions are problematic and may distract research importance.

In much of the United States gangs are considered to be ethnic, organized, and engaged in criminal activity (Decker & Van Winkle, 1996; Klein, 1995). In this study, a street gang or clique “is any durable street oriented youth group whose involvement in illegal activity is part of its group identity” (Klein & Maxson, 2008, p. 4). This nominal definition applied to the current study is based on the consensus of the eurogang program of more than 100 American and European researchers and policy makers from more than a dozen nations (Klein & Maxson, 2008).

As with many behavioral studies, the evolution of gang membership research has become increasingly complex. Early studies concerning gang behaviors (e.g., Ashbury, 1927; Puffer, 1912; Riis, 1902) focused on a limited number of variables, including fewer than present day demographic characteristics, to predict gang membership. In the early days, Klein (1995) proposed that researchers and police had little useable information about gangs and that gang intelligence shared minimal social research during the mid-1950s through the 1960s. This period, which fused theory and policy, lead to key gang research and intervention projects. The work of Short in the 1960s and 1970s highlighted the psychosocial nature of gangs and is argued to have provided “more valuable gang-related data per square inch than any other volume yet marketed” (Klein, 1995, p. 54).

During the 1980s and 1990s, gang membership research expanded to offer an increasingly complex variety of predictors and outcomes associated with membership (e.g., Klein, 1995; Sachs, 1997; Spergel, 1995; Yablonsky, 1997). Gang membership is now regarded as a more complicated and intricate phenomenon with multiple margins and attention to the edges of a “fluid social structure” employing terms such as “wannabe, core, fringe, associate, hardcore, and O.G. (original gangster)” with a continuum of membership (Maxson, 1998). Following approximately 30 years of advancement, the literature no longer describes these outcomes (e.g., substance abuse, property damage, violence, and delinquency) as synonymous but rather as synchronous with gang membership (Cohen, 1972; Decker, Bynum, & Weisel, 1998; Hagedorn 1988, 1991; Klein, 1995; Sanchez-Jankowski, 1991; Taylor, 1990). Increased complexity of both negative and positive outcomes has called attention to the importance of the type of individual predictors of gang membership, especially where prevention is the focus (Hill, Howell, Hawkins, & Battin-Pearson, 1999). While categories known as risk factors remain constant, the value of individual predictors within these risk factors, including demographics, may indeed be heterogeneous. Until more recently, gender seemed of lesser importance than in older studies (Bell, 2009; Bowker & Klein, 1983; Campbell, 1984; Esbensen & Deschenes, 1998; Miller, 2001; Miller & Brunson, 2000; Moore, 1991; Padilla, 1992; Peterson, Miller, & Esbensen, 2001; Taylor, 1993; Vigil, 2002). The unique contributions of ethnicity, gender, age, and details associated with the physical aspects of urban vs. rural, suburban vs. inner-city have become more meaningful (e.g., Moore, 1991; Sanders, 1994; Short & Strodtbeck, 1965; Spergel, 1995; Thrasher, 1963; Vigil, 1988). The importance of generalization across demographics is balanced by the importance of currently available geographical specificity.

The present study contributes to the field in three ways: (1) identifies issues that middle school youth encounter in a suburban county setting; (2) provides a homegrown report to assist stakeholders (administrators, teachers, parents, students, and law enforcement) in identifying locally relevant risk factors of gang behavior; and (3) substantiates risk factors for gang membership proliferation in those neighborhoods with no recently documented history of gangs.

This study employs a quantitative methodology and uses a 42-item survey instrument to examine school, peer, community-neighborhood, and family risk factors as predictors of gang (clique) membership for eighth grade students. The study addresses one specific question: What are the major risk factors for clique / gang membership?

 

Factors for Gang Membership

Early findings appear to build upon the traditional explanations of the etiology of any gang. However, the current conceptualizations that employ the use of risk factor domains have proven helpful, insightful and have added depth and credibility to the literature and are incorporated herein.

This section will discuss risk factors to gangs. Risk factors are not causes of gang membership but rather forces that “pull” and “push” youth toward gangs (Decker & Van Winkle, 1996). While gang membership cannot be predicted with certainty, and although researchers do not always agree on the most important risk factors for gang membership (Howell, 2010; Howell & Egley, 2005; Maxson, 1996), they have identified certain risk factors, particularly characteristics / symptoms or environmental circumstances that contribute to the start, permanence, or intensification of gang membership (Howell, 2005). The collective body of research suggests that the more risk factors and/or the greater number of multiple risk factors experienced, the greater the chance of joining a gang (Esbensen, Peterson, Taylor, & Osgood, 2012; Howell, 2010; Howell & Egley, 2005; Wyrick & Howell, 2004). Still, gang membership is not a direct result of a number of particular risk factors, but an anticipated consequence of many varied types of risk factors (Krohn & Thornberry, 2008). Developed from multiple types of research studies (i.e., cross-sectional, longitudinal, and ethnographic / observational), Howell's (1998) table of risk factors (Table 1) for youth gang membership is organized into five domains: school, individual, peer, community-neighborhood, and family.

 


Table 1. Risk Factors for Youth Gang Membership

Domain

Risk Factors

Sources

Com-munity

Social disorganization, including poverty & residential mobility

Curry & Spergel, 1988

Organized lower-class communities

Miller, 1958; Moore, 1991

Underclass communities

Bursik & Grasmick, 1993; Hagedorn, 1988; Moore, 1978, 1985, 1988, 1991; Moore, Vigil, & Garcia, 1983; Sullivan, 1989

Presence of gangs in the neighborhood

Curry & Spergel, 1992

Availability of drugs in the neighborhood

Curry & Spergel, 1992; Hagedorn, 1988, 1994a, 1994b; Hill et al., in press; Kosterman et al., 1996; Moore, 1978, 1991; Sanchez-Jankowski, 1991; Taylor, 1989

Availability of firearms

Lizotte et al., 1994; Miller, 1992; Newton & Zimring, 1969

Barriers to & lack of social & economic opportunities

Cloward & Ohlin, 1960; Cohen, 1960; Fagan, 1990; Hagedorn, 1988, 1994b; Klein, 1995; Moore, 1990; Short & Strodtbeck, 1965; Vigil, 1988

Lack of social capital

Short, 1996; Sullivan, 1989; Vigil, 1988

Cultural norms supporting gang behavior

Miller, 1958; Short & Strodtbeck, 1965

Feeling unsafe in neighborhood; high crime

Kosterman et al., 1996; Vigil, 1988

Conflict with social control institutions

Vigil, 1988

 

Family

Family disorganization, including broken homes & parental drug/alcohol abuse

Bjerregaard & Smith, 1993; Esbensen, Huizinga, & Weiher, 1993; Hill et al., in press; Vigil, 1988

Troubled families, including incest, family violence, & drug addiction

Moore, 1978, 1991; Vigil, 1988

Family members in a gang

Curry & Spergel, 1992; Moore, 1991; Moore, Vigil, & Garcia, 1983

Lack of adult male role models

Miller, 1958; Vigil, 1988

Lack of parental role models

Wang, 1995

Low socioeconomic status

Almost all studies

Extreme economic deprivation, family management problems, parents with violent attitudes, sibling antisocial behavior

Hill et al., in press; Kosterman et al., 1996

 

School

Academic failure

Bjerregaard & Smith, 1993; Curry & Spergel, 1992; Kosterman et al., 1996

Low educational aspirations, especially among females

Bjerregaard & Smith, 1993; Hill et al., in press; Kosterman et al., 1996

Negative labeling by teachers

Esbensen & Huizinga, 1993; Esbensen, Huizinga, & Weiher, 1993

Trouble at school

Kosterman et al., 1996

Few teacher role models

Wang, 1995

Educational frustration

Curry & Spergel, 1992

Low school commitment, attachment; high level of antisocial behavior in school; low achievement test scores; & identification as learning disabled

Hill et al., in press

 

Peer

High commitment to delinquent peers

Bjerregaard & Smith, 1993; Esbensen & Huizinga, 1993; Vigil & Yun, 1990

Low commitment to positive peers

Esbensen, Huizinga, & Weiher, 1993

Street socialization

Vigil, 1988

Gang members in class

Curry & Spergel, 1992

Friends who use drugs or who are gang members

Curry & Spergel, 1992

Friends who are drug distributors

Curry & Spergel, 1992

Interaction with delinquent peers

Hill et al., in press; Kosterman et al., 1996

 

Indiv-idual

Prior delinquency

Bjerregaard & Smith, 1993; Curry & Spergel, 1992; Esbensen & Huizinga, 1993; Kosterman et al., 1996

Deviant attitudes

Esbensen, Huizinga, & Weiher, 1993; Fagan, 1990; Hill et al., in press; Kosterman et al., 1996

Street smartness; toughness

Miller, 1958

Defiant & individualistic character

Miller, 1958; Sanchez-Jankowski, 1991

Fatalistic view of the world

Miller, 1958

Aggression

Campbell, 1984a, 1984b; Cohen, 1960; Horowitz, 1983; Miller, Geertz, & Cutter, 1962; Sanchez-Jankowski, 1991

Proclivity for excitement & trouble

Miller, 1958; Pennell et al., 1994

Locura (acting daring, courageous & especially crazy in the face of adversity)

Moore, 1991; Vigil, 1988

Higher levels of normlessness in the context of family, peer group, & school

Esbensen, Huizinga, & Weiher, 1993

Social disabilities

Short & Strodtbeck, 1965; Vigil, 1988

Illegal gun ownership

Bjerregaard & Lizotte, 1995; Lizotte et al., 1994; Vigil & Long, 1990

Early or precocious sexual activity, especially among females

Kosterman et al., 1996; Bjerregaard & Smith, 1993

Alcohol & drug use

Bjerregaard & Smith, 1993; Curry & Spergel, 1992; Esbensen, Huizinga & Weiher, 1993; Hill et al, in press; Thornberry et al, 1993; Vigil & Long, 1990

Drug trafficking

Fagan, 1990; Thornberry et al., 1993

Desire for group rewards such as status, identity, self-esteem, companionship, & protection

Curry & Spergel, 1992; Fagan, 1990; Horowitz, 1983; Horowitz & Schwartz, 1974; Moore, 1978, 1991; Short & Strodtbeck, 1965

Problem behaviors, hyperactivity, externalizing behaviors, drinking, lack of refusal skills, & early sexual activity

Hill et al., in press; Kosterman et al., 1996

Victimization

Fagan, 1990

Howell, J.C. (1998). Youth gangs: An overview. OJJDP Bulletin



School risk. Early academic failure is associated with delinquency and gang membership. Middle school students who joined gangs did not perform well in elementary school, and had a weak attachment to teachers (Thornberry, Lizotte, Krohn, Smith, & Porter, 2003) and a low attachment to and involvement in school (Bjerregaard, & Smith, 1993; Hill et al., 1999; Le Blanc & Lanctot, 1998). Hemphill, Toumborou, Herrenkohl, McMorris, and Catalano (2006), Huizinga and Henry (2008), Kaplan and Damphouse (1997), and Valencia (2010) found that negative conditions already within at-risk schools increased future delinquency, which also increased gang membership (Esbensen & Huizinga, 1993; Hill, et al., 1999; Thornberry, et al., 2003). Taking into consideration the “student engagement” (Appleton, 2008; Betts, Appleton, Reschly, Christenson, & Huebner, 2010) and student “connectedness” to schools and “school climate” (Gottfredson, G.D., Gottfredson, D.C., Payne, & Gottfredson, N.C., 2005; Resnick, Ireland, & Borowsky, 2004), contemporary studies on school risk experiences are more sound than previous mixed findings.

Peer risk. Regardless of how peer risk affiliation is measured, association with deviant or delinquent peers provides one of the strongest predictors for gang membership (Hawkins, Smith, Hill, Kosterman, Catalano, & Abbott, 2003; Howell, 2010; Huizinga, Weiher, Espiritu, & Esbensen, 2003; Klein & Maxson, 2006; Lipsey & Derzon, 1998; Thornberry, Lizotte, et al., 2003; Tremblay, Vitaro, Nagin, Pagani, & Seguin, 2003). Studies confirm that delinquent/antisocial peers or aggressive youths start hanging out in early childhood and that this pattern of destructive friendships may continue through their teenage years (Cairns & Cairns, 1991; 1994). Through associations with delinquent peers (Lacourse, Nagin, Vitaro, Cote, Arseneault, & Tremblay, 2006), the amplified probability and regularity of physical aggression and violence contributes to the possibility of gang membership in early teens (Craig, Vitaro, & Tremblay, 2002; Eitle, Gunkel, & Gundy, 2004; Hill et al., 1999). Experiences of being rejected by peers (Huizinga & Lovegrove, 2009), along with these childhood patterns of aggressive friendships and affiliations with antisocial youth often continue through adolescence and are long-lasting predictors of gang membership (Craig et al., 2002; Kupersmidt, Coie, & Howell, 2003; Lahey, Gordon, Loeber, Stouthamer-Loeber, & Farrington, 1999; Warr, 2002). Thornberry and Krohn (2001) found that this pattern of delinquency may be the result of declining pro-social bonds.

Individual risk. The Individual risk factor is not examined in the current study due to school district data collection limitations. However, in order to provide a complete picture of the risk factor domains it is included in this review. The individual risk domain has received notable attention from researchers, particularly the role of personal attitudes on behavior. For example, adolescent violence is linked to early antisocial beliefs, like blatant deceitfulness, moral disengagement, aggression, and having destructive outlooks toward authority (Locura—Moore, 1991, Vigil, 1988). Likewise, these youth of prior delinquency and who tend to have confrontational attitudes and/or sociopathic characteristics (mental health problems—Davis & Flannery, 2001; Howell & Egley, 2005) are more at risk of gang membership (Esbensen, Peterson, Taylor, & Freng, 2009, 2012; Fagan, 1990; Gottfredson & Gottfredson, 2001; Hawkins et al., 2000; Hill et al., 1999; Howell, 1998, 2003).

Community risk. Community risk is the most frequently examined domain for both the development of gangs and the variables associated with gang membership (Esbensen, 2000). Among other researchers listed below, Howell and Egley (2005) reported that gangs have a tendency to be in areas with a small level of neighborhood attachment. Established gangs are likely to be present when the primary social institutions, including families, schools, and economic systems, function poorly (Moore, 1998; Vigil, 2002). Such dysfunctional communities often have a large number of teens involved in illegal behaviors, easily acquired firearms and drugs, and high crime rates. In an outline of four community conditions that often pave the way for gang indoctrination, Moore (1998) found that (1) conventional adult supervision is absent; distancing families and unproductive schools, (2) youth are not consumed by pro-social roles and therefore have a great deal of free time, (3) if gangs are not intergenerational, they become established because the members have limited access to attractive career options/respectable adult jobs, and (4) the youth assemble regularly within a particular neighborhood. These studies have noted that economically disadvantaged neighborhoods (i.e., poverty, unemployment, lack of meaningful jobs, marginalization, and social disorganization) contribute to the presence of gangs (Esbensen et al., 2009; Esbensen et al., 2012; Howell, 1998, 2010; Pyrooz, Fox, & Decker, 2010; Thornberry, Krohn, Lizotte, Smith, & Tobin, 2003; Moore, 1991; Valdez, 2007; Vigil, 1988, 2002).

Family risk. Findings related toquality” of family relationships suggest that family difficulties (e.g., parent-adolescent conflict, and/or marital discord) may not be associated with gang membership any more than other disruptive behaviors (Bowker & Klein, 1983; Esbensen, 2000; Howell, 2010; Jankowski, 1991; Lyon, Henggeler, & Hall, 1992). Despite mixed evidence, Loeber & Farrington (2001) found that parents still play a crucial role in their children’s development of self-control. Howell and Egley’s (2005) found that youth are more likely to join gangs when they experience poor parental monitoring, weak attachment to parents, and minimal involvement in family activities and/or have parents with negative attitudes that promote antisocial behavior, violence, abuse or neglect (Esbensen, et al., 2009; Esbensen, et al., 2012). Research that examines outcomes associated with family characteristics has shown better consistency with gang life. Youth are more likely to join gangs due to alienation from a healthy family life where family members are associated with gangs or criminal behavior. A risk factor for joining a gang for some young Black males and Latinos is a single family home (Curry & Spergel, 1992; Moore, 1991, 1998; Vigil, 1988, 2002; Walker-Barnes & Mason, 2001), yet only in its proper context. There is an elevated risk but “This does not mean, however, that because a child lives with her/his mother or father only that s/he will join a gang any more than an overweight person will have a heart attack” (Esbensen, et al., 2009, p. 311).

Having considered the risk factor domains, the present study employs a quantitative methodology and uses a survey to examine school, peer, community-neighborhood, and family risk factors as predictors of gang (clique) membership for eighth grade students.

 

Method

Participants

The target population of this study came from a large suburban public middle school located in a Southeastern state, metro-city area. The school was selected due to location, Title 1 status, being an urban profile school, and for its uniqueness of having gangs that are not predominantly intergenerational.

The sample consisted of 407 eighth-grade student-participants (54.3% female, 42.5% male, 3.2% not responding). The sample was drawn from the total grade level population of eighth-grade students (n = 502) in the middle school. At the time of the study 95 students were either absent, refused to participate or did not provide parental consent, thus reducing the sample to 407 students.

Students reported the following ethnicities: 40.0% Hispanic (n = 163), 33.2% African American (n = 135), 10.8% Asian/Pacific Islander (n = 44), 3.9% White (n = 16), and 7.9% other (n = 32). Of the 407 students surveyed, 4.2 % (n = 17) did not report an ethnicity. Of the total number of reporting students, 70.0% (n = 285) indicated being eligible for free or reduced-price lunch.

 

Procedure

The University Social Science Institutional Review Board (SSIRB), along with the school district and county’s research department, granted permission to survey all students attending class during survey administration. As a result, a trained home-room teacher was able to administer the survey to the class as a whole rather than singling out randomly selected students and removing them from class to take the survey.

The Student Survey was administered to a sample of eighth-grade students from one of twenty middles schools from a large suburban school district. A strategy was utilized that has been proven successful in prior studies (Esbensen et al., 2012; Esbensen et al., 2008; Unger, Gallaher, Palmer, Baezconde-Garbanati, Trinidad, Cen, & Johnson, 2004). Home-room teachers administered the survey to groups of students using a standardized protocol that included a short description of the research project. Using a scripted answer sheet, survey administrators allowed students to ask questions about the project before and during the survey administration. The terms “gang,” “crew,” and “posse,” were used in describing a “clique.” In order to control for the reading level of students, survey administrators read the standardized directions for the survey and then read each item aloud, allowing approximately three to five seconds for students to record their responses on the survey form.

Home-room teachers administered the Student Survey to students in a general eighth grade home-room class over a period of thirty minutes, with one make-up session (for those absent but had a signed parent consent form) the next morning. To encourage honest survey responses, participants were verbally reminded that all responses would be anonymous and all data would be kept secure. Following district and county protocol, upon survey completion, a responsible student was asked to collect all the face-down completed surveys and placed them in a large envelope. The student then sealed the envelope and returned the sealed envelope to the 8th grade front office. The SSIRB and district research department both approved an active parental informed consent process. Additionally, student informed consent was obtained.

 

Variables and Measures

A 42-item paper self-report student survey was designed to assess the following risk factor domains: School Risk (SR), Peer Risk (PR), Community-Neighborhood Risk (CNR) and Family Risk (FR). Basic demographic information, clique / gang involvement and items concerning promotion readiness were also assessed. The survey was constructed based on a thorough review of the literature in the areas of the risk factors of gang membership. The items on the Student Survey were author-generated though adapted from current measures found in previous youth gang research (Spergel, 1995; Office of Juvenile Justice and Delinquency Prevention, 2002).  

Gang membership. A single dichotomous item was used to assess if students “are a member of a clique now” (Clique membership: yes = 1 and no = 0). The terms “gang,” “crew,” and “posse,” were used in describing a “clique.”

Demographics. Gender, free / reduced lunch eligibility (i.e., poverty) and ethnicity were assessed as a means to account for basic demographic information. Gender was coded as either Male = 0 or Female = 1. Free / reduced lunch eligibility was coded as either Ineligible = 0 or Eligible = 1. For analysis purposes ethnicity was dummy coded into five different variables. Each of the reported ethnicities (Asian/Pacific Islander, Black, Hispanic, other & White) were coded such that 0 = not a member of the ethnic group, 1 = member of the ethnic group.

School Risk. Five items were used to assess school risk. Respondents indicated the extent to which they agreed with statements like, “My teachers are there for me when I need them” and “Students here respect what I say” using a 4-point Likert scale (1 = NO! definitely not true and 4 = YES! definitely true). Responses were averaged so that each student had an average score that could range from 1 to 4, with a larger number indicating less risk. School risk had a rather low internal consistency rating (Cronbach’s a = .61).

Peer Risk. Five items were used to assess risk associated with peer relationships. Respondents were instructed to think of their four best friends and how many of those four friends engaged in activities such as “sold illegal drugs” and had “been arrested” in the past year. Students responded using a 5-point scale (1 = None and 5 = four). Responses were averaged so that each student’s score had a range from 1 to 5 with a larger number indicating greater risk. Peer risk had an acceptable level of internal consistency (Cronbach’s a = .79).

Community-Neighborhood Risk. Four items were used to assess community risk. Students responded to questions regarding their ability to access drugs, cigarettes, alcohol and a handgun using a 4-point Likert scale (1 = very hard and 4 very easy) with a larger number indicating greater risk. Five items were used to assess neighborhood risk. Students responded to statements describing their neighborhood as having “lots of graffiti” and “fights” using a 4-point Likert scale (1 = NO! definitely not true and 4 = YES! definitely true) with a larger number indicating greater risk. One of the five items was reverse-scored (“I feel safe in my neighborhood”). Responses for community risk and neighborhood risk (nine items total) were averaged together to create one factor (Community-Neighborhood) so that each student had an average score that could range from 1 to 4, a larger number indicating greater risk. Community-Neighborhood Risk had an acceptable level of internal consistency (Cronbach’s a = .82).

Family Risk. Four items were used to assess family risk. Students responded to statements like “When I have a personal problem, my family/guardian(s) are willing to help me” and “When I am not at home, my family/guardian(s) know where I am and whom I am with” using a 4-point Likert scale (1 = never or almost never and 4 = all the time). Responses were averaged so that each student had an average score that could range from 1 – 4 with a larger average indicating less risk. Family risk had an acceptable level of internal consistency (Cronbach’s a = .74).  

 

Research Design & Analysis

Prior to analysis the data was assessed for univariate and multivariate outliers. Assessments of multi-collinearity of predictor variables in the regression models were also conducted.

To identify the factors associated with clique / gang membership bivariate correlations and logistic multiple regression were employed. Standardized Beta Values (β), indicate the direction and degree of relationship each predictor variable has to the criterion variable. Additionally, the reported Odds Ratio estimates the change in the odds of gang membership for a one unit increase in each predictor variable. An odds ratio exceeding one indicates an increased likelihood of clique / gang membership while an odds ratio less than one indicates a decrease in the likelihood of clique / gang membership. Both standard logistic regression and block entry logistic regression were employed though given the identical nature of the results, only standard regression will be reported. The data were analyzed using Statistical Package for the Social Sciences (SPSS) version 20.

 

Results

What are the major risk factors for clique / gang membership?

             To address the major risk factors for clique / gang membership, a series of bivariate correlations were conducted examining the relationship of the criterion variable (current clique membership; dummy coded as 0 = No, 1 = Yes) with each of the predictor variables (gender, poverty, Asian/Pacific Island, Black, Other, White, School Risk, Peer Risk, Community-Neighborhood Risk and Family Risk) (see Table 2). Of the variables entered, only Peer Risk, Community-Neighborhood Risk and Family Risk correlated significantly with current clique / gang membership. The correlations of Peer Risk & Community-Neighborhood Risk to clique / gang membership were counterintuitive. In both cases, the relationship is such that increased likelihood of clique / gang membership is associated with decreased risk factor. The correlation for Family Risk is intuitive in that decreased likelihood of clique / gang membership is associated with greater family support.

 


 

Table 2.  Inter-Correlation of Current Clique / Gang Membership with Demographic & Risk Factor Predictors

 

Clique

Gender

Poverty

Asian

Black

Hispanic

Other

White

School

Peer

Comm.

Family

Clique / Gang Member

1

-.028

.034

-.016

.087

-.072

.014

-.023

-.093

-.284**

-.352**

-.153**

Gender

 

1

-.043

-.056

-.027

.005

.080

.029

.026

.087

-.050

.028

Poverty

 

 

1

-.039

-.143**

.214**

-.016

-.113*

-.026

-039

-.013

-.054

Asian/Pacific Islander

 

 

 

1

-.259**

-.302**

-.107*

-.074

.023

.143**

.089

-.013

Black

 

 

 

 

1

-.617**

-.218**

-.150*

.068

.019

.078

-.014

Hispanic

 

 

 

 

 

1

-.253**

-.175**

-.088

-.092

-.013

-.051

Other

 

 

 

 

 

 

1

.062

.005

-.044

-.140**

.084

White

 

 

 

 

 

 

 

1

.011

.017

-.111*

.069

School Risk

 

 

 

 

 

 

 

 

1

.176**

.315**

.401**

Peer Risk

 

 

 

 

 

 

 

 

 

1

.549**

.310**

Community-Neigh. Risk

 

 

 

 

 

 

 

 

 

 

1

.401**

Family Risk

 

 

 

 

 

 

 

 

 

 

 

1

*Significant at the .05 level, ** Significant at the .01 level

 


A logistic regression analysis was conducted using the demographic variables and risk factors as predictor variables and the response to the question “Are you a member of a clique / gang now?” as the criterion variable (see Table 3). Due to students failing to complete the entire Student Survey, the initial sample size of 407 was reduced to 316. The initial attempt at predicting current clique / gang membership provided a model including only the intercept (SPSS default). This baseline model produced a -2 Log Likelihood of 285.83 and correctly categorized the membership of 83.2% of students. Upon adding the predictor variables (i.e., gender, free or reduced lunch status, Asian/Pacific Islander, Black, Hispanic, Other, White and the SR (School Risk), PR (Peer Risk), CNR (Community Neighborhood Risk), and FR (Family Risk) to the baseline model, the -2 Log Likelihood value was reduced by 55.50 to 230.33 which represents a significant reduction; χ2 (10, N = 316) = 55.50, p < .001). The Nagelkerke R-squared in this case indicates that the variation explained by the model is modest, at 27 percent (Nagelkerke R-squared = .271). Further examination of the variables indicated that only CNR (Exp (β) = 0.21, p = .001) was a significant predictor of current clique membership, specifically that as CNR increased by a unit of 1, students were 4.76 times less likely to be clique members.

A partial correlation between Community-Neighborhood Risk and clique / gang membership was conducted, controlling for variability attributed to Peer Risk, r(352) = -.247, p < .001. The correlation between Community-Neighborhood Risk and clique / gang membership prior to partialling the variability of Peer Risk was, r (353) = -.352, p < .001. This partial correlation reveals a robust relationship between Community-Neighborhood Risk and clique / gang membership, though slightly mediated by Peer Risk.


 

Table 3.  Logistic Regression Model Predicting Clique / Gang Membership from Demographics & Risk Factors

 

 

 

 

Variables

M

SD

Β

Odds

Gender

0.56

0.50

0.06

1.06

Poverty

0.77

0.42

0.55

1.74

Asian/Pacific Islander

0.12

0.32

1.2

3.33

Black

0.35

0.48

1.16

3.18

Hispanic

0.42

0.49

0.01

1.00

Other

0.08

0.28

0.07

1.07

White

0.04

0.20

0.00

1.00

School Risk

2.49

0.54

0.48

1.62

Peer Risk

4.01

0.87

-0.31

0.73

Community-Neighborhood Risk

2.97

0.67

-1.55**

0.21

Family Risk

3.01

0.76

-0.23

0.80

*Significant at the .05 level, ** Significant at the .01 level

 

 

 

 


Discussion

 

The current study sought to identify the major risk factors for clique and gang membership in an eighth grade student sample. The predictor variables consisted of demographic measures as well as established risk factors. None of the demographic variables significantly correlated with gang membership. The risk factors of Community-Neighborhood, Peer and Family all showed significant individual correlations with gang membership. The inter-relationship of these risk factors and their bearing on gang membership were examined. When all variables were entered in a logistic regression model, only Community-Neighborhood was found to be a significant predictor. Contrary to previous findings (Esbensen, 2000; Howell & Egley, 2005; Moore, 1998) the current study suggests increased risk associated with Community-Neighborhood is related to a decrease in the likelihood of gang membership.

Community-Neighborhood Risks or disadvantages have frequently been seen as a contributing factor to gang membership in past research (Esbensen, et al., 2012; Pyrooz, Fox, & Decker, 2010; Thornberry, Krohn, Lizotte, Smith, & Tobin, 2003; Moore, 1998; Valdez, 2007; Vigil, 2002). Other studies do not support these findings. According to Bell (2009), Dukes and Stein (2003), Klein (1995), and Thornberry et al., (2003), being a disadvantaged inner-city or poverty area is not an essential element of gang membership. Similarly, the results of a Chicago study (Papachristos & Kirk, 2006) found that neighborhoods with a high level of general violence were not necessarily the same neighborhoods that have high levels of gang violence. Howell (2010) found that more suburban regions (small cities, town and rural areas) are experiencing gang problems for the first time. However, the current finding run contrary to previous research showing that Community-Neighborhood Risk increases or, at the very least, has no association with gang membership. The current findings reveal that Community-Neighborhood Risk is associated with a decrease in gang membership. Of primary interest is the counterintuitive relationship between increased Community-Neighborhood Risk and a decrease in the likelihood of gang membership. On the surface it appears as though the negative elements of a risky community / neighborhood (i.e. instances of fights, increased crime, availability of drugs, alcohol, and guns) could act as an insulator from gang membership. Possible interpretations of this is that there is (1) not a logical explanation, the way a forest ranger fights fire with fire (Bell, 1997), (2) no need to join a gang in communities with high CNR because youth are having enough fun (Howell, 2010), (3) a protective factor perspective that might discourage youth from joining a gang (still in its infancy, protective factor data is far too limited to be presented at this time) (Howell, 2010), (4) despite all significant findings having this potential, a type I statistical error, concluding that the CNR relationship exists with decreased gang membership when really it doesn't.

Peer Risk and Family Risk were both found to be significantly correlated with gang membership, though they were not found to be significant predictors when entered in the regression model alongside the demographic variables and other risk factors. Due to the strong correlation between Community-Neighborhood Risk and Peer Risk (r = .549), it may be difficult to tease these two factors apart. Similar to Community-Neighborhood Risk, increased Peer Risk contributed significantly to a decreased likelihood of gang membership. It is likely that students’ peers are also members of the students’ same community / neighborhood. In this case, peers and community become interchangeable. The nature of the current data does not enable any casual interpretation, rather the simple understanding that an inverse relationship may also exist regarding Peer Risk and gang membership. The current findings make clear that additional research into the dynamics of gangs and peer circles is needed to better understand the why’s of gang membership.

Previous research supports the notion that children who experience a healthy family environment are less likely to become members of a gang (Esbensen, et al., 2009; Howell & Egley, 2005; Loeber & Farrington, 2001; Moore, 1991; Vigil, 1988). Similar to the finding reported by Bowker & Klein (1983), Esbensen (2000), Jankowski (1991), Lyon, Henggeler, and Hall (1992), the current study found a significant, but small effect for Family Risk with a correlation of r = -.153. While significant, the r squared is a negligible 2.34%. School Risk was also shown to be unrelated to gang membership for both males and females.

In congruence with previous studies, the nature, process, and development of gang membership is not easily explainable. While researchers have been attempting to minimize risk factors associated with gang membership for middle school and elementary youth in recent decades, more studies on middle school students are needed to obtain and utilize the often ignored perspectives of youth to a greater extent. Although the participants for this study were all 8th grade students, in one school and neighborhood, the descriptions of the role of Community-Neighborhood Risk in gang membership are within the broad scope of gang literature. The authors recommend that more comprehensive and definitive research be conducted to better understand what, at times, are counterintuitive findings. Thornberry (1998) provides the following summary on whether or not an individual, potentially an 8th grader, joins a gang:

“there is no single risk factor or set of factors that are predictive of gang membership; rather, risk is present in the domains of the community, family, school, peer, and individual characteristics—there are similarities and differences within each of these domains by gender” (as cited in Deschenes & Esbensen, 1999, p. 71).

 

Limitations

Participants completed the survey during a homeroom class. The home-room teachers explained the purpose of the study to the students and informed them that the information would be given to school administrators and used to improve the school experience for students. While classroom teachers encouraged students to respond truthfully, students had no concrete incentive to complete the survey honestly. Additionally, some students may have lacked the motivation to carefully consider the survey items and respond in a manner that reflected their actual perceptions and behaviors. Therefore, it is possible that students’ responses on the Student Survey did not reflect their actual beliefs.

A second limitation relates to district size and the “school effect” (too many immeasurable variables within the school) which may impact the scope of the study. School researchers maintain that too many variables exist in the educational setting to consider them all (Betts, Appleton, Reschly, Christenson, & Huebner, 2010; Gottfredson, Gottfredson, D.C., Payne, & Gottfredson, N.C., 2005; Hughes & North, 2012; Resnick, Ireland, & Borowsky, 2004).
The current study was conducted in one public middle school with only eighth grade middle school students. The school system used at the time of this study had over 100 facilities—elementary schools, middle schools, high schools, and other educational facilities—enrollment tops 160,000 students. The school system is the county’s largest employer, with nearly 25,000 full- and part-time positions and available substitutes. The group of students used in this study represents only a small fraction of the students in the district and the surrounding counties. Consequently, it will be difficult to generalize the findings to students outside of the district used in this study.

As was previously mentioned, the use of the word “clique” along with the word “gang” in this study was unavoidable and may have influenced students’ responses about gang membership. Although it is not unusual for schools to deny having gang problems to appease the public or recognize that gangs are a problem within the school (Gottfredson & Gottfredson, 2001; Huff, 1998; Maxson, 1998), it is possible that the school district in which data were collected did not want to ask about “gang” membership specifically to avoid acknowledging the existence of gangs. In this sense, using the word “cliques” enabled the researchers to still address the concern and move forward with the study. Particularly on this vital social issue where intervention is warranted, and the social, political and cultural context always being a concern, the insight gained from the relevant data provided by students can benefit everyone within the school and community.

Lastly, as directed by the school district, the researchers were not permitted to ask students about the factor of Individual Risk. Therefore, in order to provide a complete picture of the risk factor domains, Individual Risk needs to be included alongside other relevant predictor variables.

Given the findings of the current study for risk factors that predict gang membership, it is understandable that there is a need for further discourse. Current findings that conflict with some of the gang literature would suggest the need for ongoing review. The suburban youth of this study reported weakened social controls and limited resources, yet most avoided gang life; similar to Fagan (1990), "inner-city youths in this study live in areas where social controls have weakened and opportunities for success in legitimate activities are limited. Nevertheless, participation in gangs is selective, and most youths avoid gang life" (p. 207). As for what is known now, it remains a challenge to lay a finger on the specific pushes and pulls that move youth toward and away from gang membership. The current work clearly speaks to the continued need for a multi-faceted approach in which there is no one-size-fits all-solution.

 

Acknowledgments

Authors gratefully acknowledge the valuable specialist assistance of our team of colleagues, and the county schools research and evaluation department. A special thank you to the student-participants who made this study possible by completing the survey; and to the school principal and research coordinator, without their willing hearts and generous help, the study that you see here would not have been possible.

 

 

*The Authors

James Martinez, Ph.D., is an Assistant Professor of Education at Valdosta State University. He received his doctorate in Education and Sociology from the University of Missouri-Kansas City. His research interests include identity development during adolescence and risk factors for youth gangs; critical race theory; critical pedagogy; critical consciousness; middle and high school education; and racial/ethnic inequality.


Jeremy R. Tost, Ph.D., is an Assistant Professor of Psychology at Valdosta State University. He received his doctorate in Experimental Psychology from New Mexico State University. His research interests include the study of consciousness, religious experiences, and self-control.


Larry D. Hilgert, Ph.D., NCSP is an Associate Professor and Coordinator of the School Psychology program at Valdosta State University. He received his doctorate in School Psychology from Ball State University. As a nationally certified school psychologist and a Georgia licensed psychologist, his research interest is in multicultural settings where he supervises practicum students and interns.


Tracy Woodard-Meyers, Ph.D., is a Professor of Sociology and the Director of the Women’s and Gender Studies program at Valdosta State University. She received her doctorate in Family Relations from Florida State University. Her research interests include Latina women’s experience with intimate partner violence, global feminism, and social justice movements. She has published articles and book chapters regarding secondary traumatic stress in child protective service workers and strategies for conducting successful sexual assault interviews.


 

 

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Citation: Martinez, J., Tost, J., Hilgert, L., & Woodard-Myers, T. (2013). Gang Membership Risk Factors for Eighth-Grade Students. Nonpartisan Education Review / Articles, 9(1).

 

 

 


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