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Journal of Quantitative Criminology ISSN 0748-4518Volume 29Number 2 J Quant Criminol (2013) 29:251-272DOI 10.1007/s10940-012-9178-6

Delinquent Behavior, Violence, and GangInvolvement in China

David C. Pyrooz & Scott H. Decker

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ORI GIN AL PA PER

Delinquent Behavior, Violence, and Gang Involvementin China

David C. Pyrooz • Scott H. Decker

Published online: 1 July 2012� Springer Science+Business Media, LLC 2012

AbstractObjectives This study examines the relationship between delinquent behavior and gang

involvement in China. We assess the feasibility of self-report methodology in China and

whether established findings in US and European settings on the relationship between gang

involvement, violence specialization, and delinquent behavior extend to the Chinese context.

Methods Data were gathered from 2,245 members of a school-based sample in

Changzhi, a city of over 3 million people in Northern China. Drawing from a detailed

survey questionnaire that measures prominent theoretical constructs, multi-level item

response theory modeling was used to examine the association of gang involvement with

general and specific forms of delinquency, notably violence specialization.

Results Over half of the sample engaged in some form of delinquency over the prior

year. Eleven percent of the sample reported gang involvement. Large bivariate differences

in overall delinquency and violence specialization between gang and non-gang youth were

observed. Multivariate analyses with measures of low self-control, household strains,

family and school attachment, parental monitoring, and peer delinquency reduced the

bivariate effect sizes, but current and former gang members had higher log odds of overall

delinquency and violence specialization.

Conclusion In helping fill gaps of knowledge on gangs and delinquency in the world’s

most populous country, this study observed self-reported rates of delinquency and gang

involvement not unlike Western countries. Findings on the relationship between gangs and

delinquency, particularly violence, are consistent with the current literature and support the

invariance hypothesis of gang involvement.

Portions of this article were presented at the annual meeting of the American Society of Criminology, heldin San Francisco, CA, and the meeting of the Eurogang research network, held in Neustadt an derWeinstrasse, Germany.

D. C. Pyrooz (&)College of Criminal Justice, Sam Houston State University, Box 2296, Huntsville, TX 77341, USAe-mail: david.pyrooz@asu.edu; David.Pyrooz@shsu.edu

S. H. DeckerSchool of Criminology and Criminal Justice, Arizona State University, Phoenix, AZ, USA

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Keywords Delinquency � Violence � Specialization � Gang involvement � China

Introduction

In the 1980s, gangs spread throughout the United States. No longer were they concentrated

in Chicago or Los Angeles, or even in large cities. By the end of the century, gangs

received attention in Europe (Klein et al. 2001; Decker and Weerman 2005). Gangs in

Europe were described in terms generally similar to those used to describe American

gangs. Membership was largely neighborhood based, gangs lacked an extensive organi-

zational structure, membership was of relatively short duration, and while in a gang,

delinquent involvement was elevated. Evidence of gangs in Central and South America,

Africa and parts of Asia also emerged (Bruneau et al. 2011; Covey 2010; Decker and

Pyrooz 2010; Gatti et al. 2011). Taken together, this research led to a growing body of

global knowledge on the level and nature of gang behaviors.

Despite this progress in understanding the spread and nature of gangs in the global

context, there is little evidence about gangs in the world’s most populous country: China. To

be sure, there is not solid empirical evidence about whether gangs are even present in China,

and if so, how their characteristics converge and diverge from what is known elsewhere.

This is unfortunate for several reasons. China has undergone profound economic, social and

political changes over the past two decades. The historic isolation of Chinese society from

international trends in behavior, particularly youth culture, changed dramatically. These

trends have been linked to increases in crime as Chinese citizens struggle to adapt to the

challenges of a new internal order and increased global influences on behavior (Deng and

Cordilia 1999; Zhang et al. 2008). These factors make an examination of the presence and

consequences of youth gangs in China particularly appropriate at this time.

This article examines several questions about gang involvement and delinquent

behavior in China. Based on self-reports from a sample of 2,245 secondary students in a

large Chinese city, we address five questions: (1) Is the measurement of delinquency and

youth gang involvement in the Chinese context feasible using self-report methodology? (2)

Do Chinese school youth self-report gang involvement? If so, do rates of gang involvement

follow the patterns of other countries? (3) Do gang-involved youth engage in delinquency

at higher rates than non-gang youth? If so, is there a preference for violent over nonviolent

delinquency (i.e., violence specialization)? (4) What is the role of demographic charac-

teristics in predicting delinquent behavior? and (5) Do school, household, and peer mea-

sures confound the relationship between gang involvement and delinquency? Our strategy

in answering these questions includes descriptive and bivariate analyses as well as the use

of multi-level item response theory (IRT) modeling (Osgood and Schreck 2007) to

simultaneously examine delinquency involvement and violence specialization. This line of

inquiry extends knowledge about gang involvement and delinquency in important ways,

most notably by providing a multivariate analysis of the association of gang involvement

with delinquent behaviors in the Chinese context and by applying recently developed

analytic techniques to detect violence specialization outside of North American settings.

Documenting the Global Diffusion of Gangs

The spread of youth gangs across the US has been well documented. Miller (1982)

established the presence of gangs in large US cities. Based on a survey of law enforcement

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officials, his results provided a foundation for future work. Spergel and Curry (1990)

differentiated cities according to whether gang activity was ‘‘chronic’’ or ‘‘emergent.’’ The

former tended to be urban metropolitan cities with large populations that were clustered

geographically (e.g., Los Angeles, Long Beach, San Diego) and gang problems that

emerged prior to 1980. The emergence of gangs outside of chronic gang cities not only

elevated concerns about drugs and violence, but also raised questions about whether such

movement reflected organized migration patterns. Maxson (1998) reported that this was

not the case. Instead, the cultural aspects of gangs led to a national gang presence spread by

the transmission of gang attributes, particularly clothing and personal styles of appearance,

often fueled by movies and music.

The transmission of gang culture was not confined to the United States, however.

Indeed, gangs expanded dramatically in the 1990s. Examples of the global transmission of

gang culture could be found in Canada and Europe (Klein 1995; Klein et al. 2001). The

research and law enforcement communities in Europe paid increased attention to these

symbols and behavior beginning in the late 1990s. While some cities (e.g., Glasgow,

Manchester) had observed gangs much earlier, for the most part European cities did not

have traditional youth gangs. Though lacking the comprehensive law enforcement surveys

available in the US, a number of pioneering studies emerged in the European context that

clearly documented the emergence of American-style youth gangs in Europe and Great

Britain. Klein (1995) has documented the presence of gangs in more than a dozen countries

including most of Western and Eastern Europe. Klein’s research laid the groundwork for a

common definition of a gang and a set of measurement tools resulting in the development

of the Eurogang program of research, which concentrates on comparative, multi-method

research (Weerman et al. 2009). No longer was gang research exclusive to the United

States. Instead, European research on gangs in the late 1990s and early 2000s used the

United States as a comparative reference point. Indeed, many of the conclusions about

gangs in European settings—delinquent involvement, ethnic composition, risk factors for

gang involvement—were reinforced in the volumes of Eurogang research, including Klein

et al. (2001), Decker and Weerman (2005), Van Gemert et al. (2008) and Esbensen and

Maxson (2012).

Two recent streams of research provide an even greater comparative context for

understanding gangs. First, Decker and Pyrooz (2010) examined the presence of gangs and

gang violence in a global context. Much like Hagedorn (2007) and Covey (2010), they

found gangs in each of the highly populated continents—North and South America,

Europe, Africa and Asia—but levels of gang violence were conditioned by access to

firearms. Second, the understanding of gangs in a comparative context has recently been

supplemented by the work of the International Self Report Delinquency project (ISRD,

2010; Gatti et al. 2011). Using ISRD data representing 30 countries in Northern, Western,

Eastern, and Central European, Anglo-Saxon, Mediterranean, and Latin American regions,

Gatti et al. (2011) reported deviant youth group prevalence rates between .4 and 17 % in

youth samples. These projects are important steps forward in understanding the global

nature of gang activity.

However, with well over one billion people, the world’s most populous country—

China—is notably absent from the research discussed above. Given what is known about

the transmission of gang culture, there remains a poverty of knowledge about gangs in

many regions of the world. Indeed, the gang diffusion process has likely been accelerated

by widespread access to the Internet (Decker and Pyrooz 2011; Decker et al. 2009;

Papachristos 2005). Even in areas where the Internet is censored—in places such as China

(Liang and Lu 2010)—it may still play a prominent role in the process of transmitting ideas

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and information such as gang styles and behavior from established gang countries to new

continents and countries. When mixed with changes in social and economic conditions this

can lead to the emergence of gang activity; thus our interest in studying students in China.

The focus on gang and delinquent behavior in China is particularly appropriate. Despite

its population size and increased global importance, little is known about delinquency and

gangs in China, much less their correlates. There is speculation that increases in crime in

China are related to a number of cultural and structural changes in the country, although

knowledge of this topic is still nascent (Zhang et al. 2008; Liu 2008; Liu et al. 2001). Deng

and Cordilia (1999) identified rising expectations regarding the standard of living, growing

income inequality and a relaxation in social control as primary forces behind the increase

in crime in China. Dutton (1997) reviewed the three volume report on crime released by

the Chinese government in 1989, linking increases in crime to the relaxation of state

control and an increase in influences from outside nations. The report specifically identifies

an increase in ‘‘gang-land crimes’’ and documented the number of gangs (36,000) and gang

members (138,000) in China.1 While changing social and economic conditions, global-

ization and the development of the Internet (Decker et al. 2009; Liang and Lu 2010) might

help explain the presence of gangs in China, these factors fall short of detailing the nature

and extent of delinquent behaviors among adolescents and behaviors that differentiate gang

and non-gang youth in other geographic settings.

Studying Delinquency and Gang Involvement in China

Self-report research on delinquency and gang involvement enjoys a long history in the

United States (Hindelang et al. 1981; Hirschi and Selvin 1967; Krohn and Thornberry

2008; Piquero et al. 2002; Sweeten 2012; Thornberry and Krohn 2000). Federally funded

panel studies have provided a wealth of findings examining their association in Denver,

Pittsburgh, Rochester, and Seattle (Battin et al. 1998; Esbensen and Huizinga 1993;

Gordon et al. 2004; Thornberry et al. 2003). This research shows several consistent

findings, including: (1) gang membership facilitates involvement in crime such that crime

increases during periods of membership and declines once an individual leaves their gang,

(2) gang membership is relatively short-term, typically lasting less than 2 years, and (3) a

consistent set of risk factors are related to gang membership.

Self-reported research on delinquency, much less gang involvement, does not enjoy the

same history in China as it does in the United States. Liu (2008) recently decried the

absence of quantitative data on crime in China. While noting that crime in China has

‘‘increased significantly’’ (p. 131) his review documented that official data tend to be

available at the national level and cannot reliably be disaggregated to the province or

smaller units. He noted the availability of the Wuhan Birth Cohort study (Friday et al.

2003) but argued that other than this, there has been little primary data collection in China.

Liu underscored the difficulties in collecting self-report data, identifying only two such

studies, the Tianjin prison survey data and Bao, Haas and Pi’s (2007) study of self-reported

delinquency in three cities.

The use of self-reported methods is important to understanding delinquency. These

methods are a primary way of learning about youthful misconduct and an important

1 The estimate of 36,000 gangs and 138,000 gang members in China compares to estimates in the US of28,100 gangs and 731,000 gang members (Egley and Howell, 2011). On average, this means that gangs inChina have fewer than four members per gang compared to 26 in the US.

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counterpart to official statistics on crime. Self-reported delinquency studies are particularly

important in China at this time, where official offense data is not routinely available and

lacks the measurement stability found in such data collected in the US, Canada and many

European nations. Because of the lack of prior work in China, concerns about the use of

self-reported methodologies exist. These concerns reflect the novelty of the technique in

China, as well as concerns that Chinese students may under-report delinquency and other

forms of negative behavior (e.g., parental mistreatment, poor academic performance,

disrespect for authority; see Webb et al. 2011). Because of its central role in understanding

delinquency, efforts to implement self-reported techniques in a variety of Chinese settings

are of great significance. There are a number of important recent attempts to better

understand crime and delinquency in China. Zhang (2008) observed that while efforts to

better understand juvenile justice and delinquency have emerged, they remain largely

descriptive and offer little basis for explanations of patterns or trends. Zhang et al. (2008)

arrived at similar conclusions. They concluded that despite their potential importance, the

use of self-report studies in China has been ‘‘very limited’’ (126).

Despite this pessimism, there are a few examples of the successful use of self-reported

methodologies in Chinese settings. Using the Wuhan birth cohort of 1973 data, Friday et al.

(2005) examined the correlates of officially recorded offending. They found that theoret-

ically-oriented criminological covariates—negative peer influences, troubled familial

relationship, and poor school attachment and attainment—could explain variability in

offending. The findings emerged despite ‘‘the exceptionally low rate of offending’’ within

the cohort (pp. 130–131). Greenberger et al. (2000) used self-reported delinquency and

behavior questionnaires with high school students in Los Angeles, Seoul and Tianjin. They

reported high levels of study participation across the three groups, with nearly 95 % of

Chinese students completing a useable questionnaire. American youth self-reported higher

levels of delinquent behavior than their Chinese or Korean counterparts. Despite those

differences, a common set of predictors held across the three samples, including the

behavior of close friends and the sanctions close friends would offer for misconduct.

Similarly, Wei et al. (2004) used self-reported offending data to compare the behavior of

high school aged students in Shanghai and Brisbane. Levels of self-reported delinquent

behavior were significantly lower in the Chinese sample, however, co-offending was more

common in the Shanghai sample.

Bao and Pi (2007) used self-reported methods to test General Strain Theory (GST) in a

population of middle and high school students from a rural and urban area. Ninety-eight

percent of students participated in the study, demonstrating the potential of this method-

ology in China. They found that strain, particularly among boys, was related to partici-

pation in group delinquency. While not a direct study of gangs using self-reported

delinquency measures, Jessor et al. (2003) compared school based samples from Beijing

and a metropolitan area in the Rocky Mountain area of the US. Students from the 7th

through 9th grades participated in the study. The key finding of interest to the current work

is the relationship between measures of the presence of gang related activity in the

neighborhood and multiple problem behaviors. While the differences were significant,

comparable proportions of US and Chinese boys and girls reported the presence of gangs in

their neighborhoods. Fifty-two percent of US boys and girls reported the presence of gangs

in their neighborhoods, while 49 % of Chinese boys and 47 % of Chinese girls reported the

presence of gangs in their neighborhoods. These studies suggest that the self-reported

methodology is indeed feasible in a Chinese setting, and that the differences in exposure to

youth gangs across US and Chinese samples may be comparable.

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While these studies demonstrate the potential for using self-reported delinquency

methodologies, they do not inform us about the presence of gangs among Chinese youth.

These studies do suggest that group context and co-offending are important correlates of

juvenile offending in China, perhaps more than in the US. Zhang et al. (1997) examined

self-reported data from inmates in prison and reform camps in Tianjin. This study also

identified four key characteristics of gangs in China. First, gang organization was rather

low, with few characteristics of gangs that mirror those of formal organizations. Second,

this study found that membership was transitory and age-graded. Third, gangs in China

were territorial, identifying with delimited geographical areas. Finally, gang crime was

cafeteria style and not especially serious, though the crimes that gang members committed

were subject to severe penalties under Chinese law. In addition, gang members were more

likely to recidivate and reoffend at shorter periods (see Liu 1999). With the exception of

crime seriousness, these findings are consistent with research in United States and Euro-

pean settings. Ngai et al. (2007) examined the correlates of gang involvement in a sample

of 838 delinquents in Guangzhou, Hong Kong and Shanghai. They found that prior gang

involvement predicted expected future gang involvement and that prior participation in

gang activity predicted expected gang involvement. However, there is concern about the

measurement of prior and future gang involvement, where the former was operationalized

‘‘How many times did you participate in gang activities in the past month?’’ and the latter

was operationalized ‘‘How likely is it [0, 25, 50, 75, or 100] that you will participate in

gang activities in the coming month?’’ As such, basic prevalence rates of gang involvement

and differential patterns of offending could not be derived from this research.

Webb et al. (2011) was the first study of gangs in China using the administration of a

school based, self-reported questionnaire. They used the International Self-Report Delin-

quency (ISRD-2) questionnaire to compare a US and Chinese sample. Data for the US

sample were collected from fifteen schools in five cities, while the Chinese data was

collected in the city of Hangzhou. Webb et al. (2011) concluded that the administration of

self-reported questionnaires to Chinese students was feasible, consistent with earlier self-

report research in China (Jessor et al. 2003; Greenberger et al. 2000). They also found

evidence of youth gangs in China using the ISRD scale items for self-nomination, although

the prevalence rates were very low (2 %). Overall, they found lower levels of self-reported

delinquent behavior among Chinese than US youth as well as lower levels of self-reported

gang membership. That said, gang youth were involved in more offending and were more

likely to be victimized than non-gang youth. While these findings break new ground in the

study of gangs in China, the small number of self-identified gang members and low levels

of delinquency and victimization make further conclusions difficult. The study notes that

their sample was largely homogenous in terms of measures of ethnicity and describes the

schools where their samples were drawn as urban and characterized by a heavy academic

load, thereby allowing less freedom for students to engage in delinquent or gang activities.

The advance in the Webb et al. (2011) research is found in its sophisticated use of

measures of gang definition and the introduction of victimization measures into self-

reported delinquency questionnaires administered in China.

What remains missing from the current inventory of research in China is a multivariate

assessment of the relationship between gang involvement and youth delinquency. The

extant literature in China provides a brief window into this relationship, but falls short of

ruling out extraneous influences on youth behavior. One of the central findings in the

literature on gangs and delinquent involvement is that gang members engage in higher

rates of delinquency above and beyond individual (e.g., poor self-control) and environ-

mental (e.g., deviant peers) influences, and that they tend to specialize in violence (Battin

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et al. 1998; Krohn and Thornberry 2008; Melde and Esbensen 2012). The current study

provides an opportunity to extend this line of research to a Chinese setting, examining the

relationship between gang involvement, delinquent behavior, and violence specialization

relative to a host of theoretical correlates of crime and delinquency. As we elaborate on

below, we employ recently developed analytic techniques used to detect violence spe-

cialization in a multi-level framework (Osgood and Schreck 2007), which allows us to

model delinquency and violence specialization simultaneously. Such an analytic strategy is

an important advancement from the current state of the literature on delinquency in China,

and is the first application of this framework outside of North American settings.

Accordingly, we examine five specific research questions:

1. Is the measurement of delinquency and youth gang membership using a self-reported

methodology feasible in a Chinese context?

2. Do Chinese school children self-report gang involvement? If so, do rates of gang

involvement follow the patterns of other countries?

3. Do gang-involved youth engage delinquency at higher rates than non-gang youth? If

so, is there a preference for violent over nonviolent delinquency (i.e., violence

specialization)?

4. What is the role of demographic characteristics (age, ethnicity, gender, SES, region) in

predicting delinquent involvement?

5. Do school, family, and peer measures confound the relationship between gang

involvement and delinquency?

Methods

Data

Data were collected from students in six schools in the city of Changzhi. Changzhi is a

prefecture-level city of 3.3 million people located in the province of Shanxi of the People’s

Republic of China. Changzhi is considered a transportation and industrial center with large

agricultural economic interests. The heavy industry (iron, steel and machinery) is fueled by

the coal that is mined nearby. The province is bordered by large mountain ranges to the

east and west of the city, providing some degree of isolation from the rest of the country.

The presence of large mining interests and the heavy industry that runs on the coal mined

in more rural areas creates a diverse population mix that brings rural and ethnic minority

populations into the city. These characteristics are reflected in our sample, and provide for

a diverse set of respondents.

Overall, 2,500 questionnaires were handed out to students in six schools. We used a

convenience sample in selecting the classes within each school. One of the schools is a

college, two of the schools are high schools, one is a school comprised of college students

and vocational school students, and the final two are vocational schools. This mix of

schools was selected to maximize variation in student academic performance and life

chances, especially job prospects and risks for levels of delinquency and crime. One

consequence of this sampling strategy is that our respondents are slightly older than

students found in typical American high schools. As such, these students may be more

likely to have matured out of crime, relative to their American counterparts. The ques-

tionnaire was translated from English to Chinese by a native of Changzhi, reviewed and

back-translated by a school teacher at the school where the questionnaire was to be

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administered, and reviewed by a group of three Chinese doctoral students in an American

PhD program. A total of 2,245 usable questionnaires were returned, for a response rate of

90 percent. The sample was reduced by 4 % because of missing information on the

dependent variable. Accordingly, this is a study of delinquent behavior among 2,163 youth

and young adults in Changzhi, China.

Dependent Variables

We are interested in the law-violating and deviant behaviors of Chinese youth and young

adults. We examine these behaviors in several ways. Youth were asked to self-report their

involvement in 15 offenses over the previous 12 months. All offenses were dummy coded,

where ‘‘yes’’ or ‘‘no’’ responses to whether respondents engaged in an offense were

recorded 1 or 0, respectively. The items ranged in seriousness from ‘‘skipping classes’’ to

‘‘attacking someone with a weapon,’’ which allows us to capture a wide assortment of

offenses. The associated prevalence rates for the 15 items can be found in ‘‘Appendix’’. We

later detail how we decompose our measures of delinquent behaviors to model overall

delinquency rates, or criminality, and violent behaviors using item response theory

(Osgood and Schreck 2007). In our descriptives table we report variety scores for a

dependent variables (Sweeten 2012).2

Independent Variables

Gang Involvement

The key independent variable in this study is gang involvement. Respondents were asked

two questions about their involvement in gangs, including (1) ‘‘Do you consider your

group of friends to be a gang?’’ followed by (2) ‘‘If you are not now, have you ever been in

such a gang?’’ Those responding ‘‘yes’’ to 1 were recorded as being currently involved in a

gang, while those responding ‘‘yes’’ to 2 were recorded as being formerly involved in a

gang. Those responding ‘‘no’’ to both of these questions served as the reference category.

Self-nominating to involvement in a gang has been found to be reliable and valid for

operationalizing gang membership (Esbensen et al. 2001; Thornberry et al. 2003; Webb

et al. 2006).

Theoretical Constructs

Measures of several individual-level criminological theories were included in this study,

including self-control, social learning, social bond, general strain, and opportunity theories.

By including measures derived from these five dominant theories in criminology, our

analysis provides the opportunity to determine the vitality of these theories in different

cultural contexts. If these theories only predict the delinquency of students in the United

2 We concentrate on violence specialization based on theory and research (Osgood and Schreck, 2007;Piquero, 2000; Piquero et al., 2003), as the facilitative effects of gang membership are hypothesized to bestrongest in the context of violence (Decker, 1996; Thornberry et al., 2003). Melde and Esbensen (2012)demonstrated this in a US school-based sample, using (1) an analytic technique to detect specialization thatwe also use, and (2) an identical set of survey items (although they omitted three theft-related items that weuse). Although inconsistent with our hypotheses, we observed no relationship between gang involvementand specialization in property offending or substance use. Thus, we concentrate solely on violencespecialization.

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States, they would be less likely to find empirical support among students in other coun-

tries, including China, and be culturally specific. This study is among the first to examine

these theoretical perspectives among Chinese students.

Low self-control is comprised of eleven items drawn from the Brief Self-Control Scale

(Tangney et al. 2004), which has been used in criminological research.3 Together these

items capture dimensions of Gottfredson and Hirschi’s (1990) low self-control theory,

including healthy habits, work ethic, and impulsivity. The items were averaged and scaled

from 0 to 4, where higher scores reflect poorer levels of self-control (Cronbach’s

alpha = .73, mean inter-item r = .20). Derived from the differential association compo-

nent of social learning theory, peer delinquency is an indirect or ego-centric perceptual

construct comprised of items asking how many of the respondent’s close friends have

committed 15 types of delinquent behaviors. The items ranged in seriousness from

‘‘skipping classes’’ to ‘‘armed robbery’’ and were scaled from 0 ‘‘none of my friends’’ to 4

‘‘all of my friends.’’ The items were averaged and exhibited acceptable levels of internal

consistency (Cronbach’s alpha = .93, mean inter-item r = .45).

Attachment to family and school tap components of Hirschi’s (1969) social bond theory.

Family attachment captures the respondent’s connection to their parents. Seven items were

used to measure family attachment, asking respondents how strongly they agree with

statements such as ‘‘You can talk to your parents about anything’’ and ‘‘You depend on

your parents for advice and guidance.’’ The items were averaged so that the construct is

scaled between 0 and 4, where higher scores indicate stronger attachment to parents

(Cronbach’s alpha = .77, mean inter-item r = .32). School attachment consists of 10

items that evaluate respondents’ views of school. Respondents were asked how strongly

they agree with statements such as ‘‘You try hard in school’’ and ‘‘Grades are very

important to you.’’ The items were averaged so that the construct is scaled between 0 and 4,

where higher scores indicate a stronger attachment to school (Cronbach’s alpha = .77,

mean inter-item r = .25).

The final constructs—school performance, parental monitoring, and negative family

events—tap elements of routine activities and strain theories. As a measure of effort and

hard work in the classroom, school performance consists of self-reported grades in Chi-

nese, Math, and English, ranging from 0 ‘‘poor’’ to 4 ‘‘excellent.’’ Because students who

performed well in one subject tended to perform well in other subjects (mean inter-item

r = .32), these items were averaged. Parental monitoring consists of four items that

measure the extent to which respondents report that their parents monitor their activities

and whereabouts. Respondents were presented with statements such as ‘‘Your parents

know who you are with if you are not at home’’ and ‘‘Your parents know where you are

when you are not at home or at school.’’ These items were averaged and scaled between 0

‘‘strongly disagree’’ and 4 ‘‘strongly agree’’ (Cronbach’s alpha = .79, mean inter-item

r = .49). Household strains is a dichotomous indicator drawing from an index of four

indicators exploring strains within the household. Respondents reporting parental or sibling

3 See, for example, the recent works of Holtfreter et al. (2010), Reisig and Pratt (2011), Reisig et al. (2011).Examples of these items include ‘‘I have a hard time breaking bad habits’’ (healthy habits), ‘‘Pleasure andfun sometimes keep me from getting work done’’ (work ethic), and ‘‘I often act without thinking through allof the alternatives’’ (impulsivity). This study used 11 and the 13 items included in the Brief Self-ControlScale. A principal components factor analysis revealed that several items did not perform as expected,especially those related to self-discipline (e.g., ‘‘I wish I had more self-discipline’’). Given the school andcultural context of this study, this is not entirely unexpected. Removing these items improved the internalconsistency of the scale.

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death, parental substance addiction, or constant parental fighting were recorded as ‘‘1,’’

while their counterparts were coded ‘‘0’’.

Additional Control Variables

A number of statistical controls were included to adjust for demographic, social, and

economic differences and guard for potential spuriousness, including age (in years), male(=1, ‘‘female’’ = 0), minority (=1, ‘‘Han ethnicity’’ = 0), broken home (‘‘divorced/sepa-

rated parents’’ = 1, ‘‘two parent household’’ = 0), parent(s) education (‘‘grade

school’’ = 0, ‘‘graduate or professional school’’ = 5), and rural (=1, ‘‘urban’’ = 0).

Analytic Strategy

We begin our analysis by first reporting the descriptive statistics of the study variables. As

noted above, there has been limited attention to this area of research—delinquency and

gang involvement in China—in criminology; therefore we detail the summary statistics for

self-reports of involvement in gangs and delinquency among Chinese students. Next, we

compare differences between gang-involved and non-gang respondents across the depen-

dent variables.

In the key stage of the analysis, we present the results from a series of multi-level

logistic item response theory (IRT) models using the technique introduced by Osgood and

Schreck (2007; see also Raudenbush et al. 2003). This technique is most commonly used to

detect a preference for a collection of similar behaviors over other forms, and is typically

applied to violent offending specialization (but see Bouffard et al. 2008). To our knowl-

edge, this is the first application of this framework outside of North American settings and

poses interesting questions about whether Chinese youth and young adults specialize in

violence. Osgood and Schreck’s methodology was developed in a hierarchical modeling

framework, which is the main advantage it offers over other methods used to detect

specialization.

We briefly outline the model in multi-level notation. As a mixed-effects approach,

individual delinquency items (level-1) are nested within respondents (level-2). The model

takes the following form:

Log odds Yij ¼ 1� �� �

¼ b0j þ b1jSpecþX16

i¼2

bijDij ð1Þ

b0j ¼ c00 þ c01X1j þ � � � þ u0j ð2Þ

b1j ¼ c11X2j þ � � � þ u1j ð3Þ

bij ¼ ci0 ð4Þ

Because we use a dummy coding scheme for our 15 delinquency items, our level-1

outcome (Eq. 1) refers to the log-odds of a ‘‘yes’’ response for person j to committing

offense i. Responses are determined by three factors in the measurement model: a latent

measure of overall delinquency (b0j), a latent measure of violence specialization (b1j), and

delinquency item severity (bij). The latent determinants of offending thus are allowed to

vary across respondents, captured by the residual terms u0j and u1j in Eqs. 2 and 3, and

correlates, such as gang involvement, are entered on the right-hand side to determine their

relationship with overall delinquency and violence specialization. The final equation, bij, is

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fixed to adjust for item base rates in the sample, and we report the item parameters in

‘‘Appendix’’.

As Osgood and Schreck (2007) outlined, the central feature of this model is the ability

to simultaneously estimate the overall tendency to engage in delinquency and the tendency

to engage in violent delinquency over non-violent delinquency. The index of specializa-

tion, Spec, is defined by a dummy variable with violent items coded 1 (and non-violent

items coded 0), which was group-mean centered so that violent items take on positive

values and non-violent items take on negative values. In our case, 5 of the 15 items

measured involvement in violent offenses, resulting in a ?.66 to -.33 coding scheme with

no delinquency item non-response. Spec, then, represents the balance of violent to non-

violent offenses, where those reporting 0 or 15 offenses contribute little to the special-

ization model. Osgood and Schreck highlight that the direction—positive, negative, or non-

significant—of the coefficients for the explanatory covariates tell us their association with

violence specialization. For example, if the coefficient for current gang involvement is

positive and statistically significant, this would indicate an association between gang

membership and engaging in a predominance of violent over non-violent delinquency (see

Melde and Esbensen 2012; Osgood and Schreck, p. 286). Likewise, a non-significant

relationship would indicate that current gang involvement is associated with a balance of

violent and non-violent delinquent offenses. Finally, because the intercept is fixed in Eq. 3,

this avoids any confounding with the overall tendency to offend (Osgood and Schreck,

p. 285). All of our analyses were carried out in Stata 12.0 using xtmelogit (StataCorp,

College Station, TX).4

Results

Descriptive Statistics

Table 1 displays the summary statistics for the study variables. Respondents reported

engaging in a variety of delinquent activities. Indeed, the mean number of delinquent

behaviors reported exceeds one over the previous 12 months. Further inspection of our key

dependent variable revealed that engaging in at least one form delinquency was the modal

category—44 % of our sample did not report any delinquent activities. Skipping classes or

fraudulently representing one’s age, arguably the least serious items in the index, were

those most commonly reported. Indeed, over half of the sample reported engaging in at

least one of the non-violent items, with the variety score slightly exceeding a mean of one.

Violent items, alternatively, were reported by 20 % of respondents, and less than 10 % of

the sample engaged in multiple forms of violence, which is reflected in a mean violence

variety score of .42. Whether we concentrate on general or specific forms of delinquency,

4 As with many studies in criminology, item non-response presents issues for individual-level research(Brame et al. 2010). There were 506 missing cells (0.24 %) across 298 cases at level-2 (or in wide form).Listwise deletion would reduce the sample by 14 percent. To preclude respondents from listwise deletion,Stata 12.0’s multiple imputation suite (mi impute) was used for the independent variables. MI is a simu-lation-based approach based on M = 20 imputations, with the imputation model specified using all studyvariables. MI is a well-established approach for handling missing data (Allison 2001; Rubin 1987, 1996). Abenefit of the multi-level IRT framework, compared to say, negative binomial regression with delinquencyvariety scores, is the ability to group-mean center Spec to avoid eliminating cases based on our decision tonot impute on the dependent variable. As a result, we retained 96.4 % the total respondents, and removedthose missing at least one-half of their delinquency responses.

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these figures indicate that the youth and young adults in this study were involved in non-

trivial amounts of deviant and law-violating activities during the year prior to taking the

survey.

The average age of our sample was just under age 18, the majority of respondents were

male, from rural areas, and very few were not ethnically Han. The respondents did not

come from highly educated backgrounds. Indeed, on average the parents of the respondents

did not complete high school, with the modal category being grade school or less. The

respondents’ fathers were more educated than their mothers, but only 10 percent of fathers

completed college compared to 7 % of mothers. Very few respondents reported that their

parents divorced or separated, although nearly one-quarter reported some typed of

household strain (e.g., death, addiction, fighting). Among the theoretical constructs,

respondents trended toward higher self-control, indicated agreement that they were

attached to school, and performed ‘‘average’’ in school. Respondents indicated uncertainty

in their attachment to the parents, but agreed that their parents monitored their behaviors.

Finally, respondents reported that very few to none of their friends, on average, engaged in

delinquent behavior.

Turning to our key independent variable—gang involvement—we find that 248

respondents (11.4 %) reported involvement in gangs. This level of gang involvement is

Table 1 Summary statistics for the study variables (N = 2,163)

TotalM or % (SD)

Non-GangM or % (SD)

GangM or % (SD)

Dependent variables

Delinquency variety 1.49 (2.46) 1.22 (1.93) 3.57 (4.40)*

Violence variety 0.42 (1.01) 0.31 (0.82) 1.27 (1.72)*

Non-violence variety 1.07 (1.69) 0.91 (1.37) 2.28 (2.95)*

Independent variables

Current gang involvement 7.6 % – 66 %

Former gang involvement 3.8 % – 34 %

Age 17.47 (2.15) 17.44 (2.13) 17.71 (2.26)

Male 60 % 59 % 69 %*

Minority 1 % 1 % 2 %*

Parent(s) education 1.09 (1.13) 1.07 (1.13) 1.18 (1.08)

Broken home 3 % 3 % 5 %

Rural 62 % 61 % 66 %

Household strain 21 % 21 % 25 %

Low self-control 1.30 (0.53) 1.29 (0.52) 1.40 (0.58)*

School attachment 2.48 (0.67) 2.52 (0.65) 2.13 (0.78)*

School performance 1.92 (0.76) 1.93 (0.74) 1.88 (0.90)

Parental attachment 1.81 (0.80) 1.82 (0.80) 1.73 (0.86)

Parental monitoring 2.62 (0.95) 2.67 (0.79) 2.16 (1.04)*

Delinquent peers 0.42 (0.50) 0.36 (0.39) 0.92 (0.82)*

N/% 2,163 1,915/89 % 248/11 %

Independent sample t tests and Chi-square tests were used to compare mean differences between non-gangyouth (reference group) and current and former gang youth

M mean, SD standard deviation

* p \ .05

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important, as it translates to one in nine study participants who were involved in gangs. A

prevalence rate of 11 % is comparable to what has been observed in United States settings

(Klein and Maxson 2006). About twice as many individuals reported current rather than

former gang involvement; at this age, such a margin is what we might expect. The larger

question, however, is how the demographic, behavioral, and socioeconomic profiles

change as we compare gang and non-gang respondents. We pool current and former gang

members together because their profiles are remarkably similar to one another. In fact, the

only statistical difference from non-gang youth when separating current and former gang

members is that low self-control no longer differs for the latter.5 Gang involved youth self-

report higher levels of involvement in both overall and violent forms of delinquency.

Respondents with a history of gang membership reported nearly three times as much

overall delinquency and four times as much violent delinquency compared to non-gang

respondents. These findings are consistent with what has been observed in United States

and European settings (see, e.g., Esbensen and Weerman 2005) when the behavior of gang

and non-gang youth is compared.

With regard to demographic characteristics, there are slight differences between gang

and non-gang respondents. Gang-involved respondents are more likely to be male than

their non-gang counterparts, but there are no differences in parental education, broken

home, and rural characteristics. These findings are consistent with what is known in other

settings. With regard to the theoretical constructs, gang-involved respondents have slightly

lower levels of self-control, are less attached to school, are monitored less by their parents,

and have peers who engage in over twice as many forms of delinquency than their non-

gang counterparts. No statistical differences were observed for household strains and

parental attachment, and gang-involved youth did not report that their school performance

suffered in relation to non-gang respondents.

By examining the summary statistics of the study variables, we have shed light on the

demographic, social, economic, and behavioral profiles of youth and young adults in a

Chinese setting. Indeed, these findings converge with what is known about gang-involved

individuals in United States and European settings. We now turn to the results of our

multivariate models to determine whether the bivariate differences observed above

between gang-involved and non-gang respondents persist when accounting for a number of

powerful criminological predictors of crime and delinquency.6

Two-Level Logistic IRT Mixed-Models Predicting Overall Delinquency

Table 2 presents the results of the structural regression model (Eq. 2, above) relating the

covariates to the latent scores for overall delinquency. We present three stepwise models to

highlight the relationship between current and former gang involvement and the tendency

5 These findings—especially with regard to delinquency—might be contrary to some expectations. Wereturn to this in the final section of the paper.6 A reviewer raised a point that our data are not derived from what is typically viewed as a school-basedsample. As such, given the modal age of our respondents, there is the possibility that some of our ado-lescence-oriented criminological covariates might perform differently among older respondents. Weaddressed this concern by correlating age with school attachment (b = -.05, p \ .05), school performance(b = .05, p \ .05), parental attachment (b = .02, p [ .05), parental monitoring (b = -.04, p \ .05), andpeer delinquency (b = .06, p \ .05). Given the prominent role of delinquent peers in our models, we carriedout supplementary analyses with it interacted with age, but observed no statistically significant relationship.In summary, we believe that the school context creates similarity across these measures, and there is littleevidence to suggest otherwise.

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to engage in delinquency. In Model 1, the coefficients essentially take the form of a

bivariate association. In Model 2, we add demographic and theoretical constructs. Because

of its importance to the understanding of gangs and delinquency, we introduce the effect of

delinquent peers in Model 3 to allow a comparison of models with and without this group-

based measure.

In Model 1, consistent with Table 1 above, involvement in a gang—whether current or

former—corresponds with higher log-odds of overall delinquency. The coefficients for

current and former gang involvement were nearly identical, and they collectively reduced

the variance in the random intercept from 5.4 to 4.7 (13 % explained).

Model 2 displays the results of this relationship after the addition of a host of covariates.

The introduction of the demographic and theoretical constructs further reduces the variance

to 3.7, explaining 31 % from the unconditional model. The associations between current

and former gang involvement and overall delinquency were reduced by about 30 % from

Model 1. Yet, all else equal, gang involved respondents have a higher tendency to engage

in delinquency than their non-gang counterparts. This finding could be described as rel-

atively robust considering that the model accounts for individual predispositions, bonds to

conventional institutions, parental monitoring, and strains and opportunities conducive to

offending—all of which are theoretically and empirically linked to involvement in

delinquency. Additionally, males and respondents from broken homes had higher log-odds

delinquency than females and respondents from intact households. Finally, poor self-

control and household strains correspond with increased involvement in delinquent

Table 2 Relationships of explanatory variables to overall offending from two-level logistic mixed-models

Overall offending

Model 1 Model 2 Model 3

b SE b SE b SE

Current gang involvement 2.05 (.21)* 1.39 (.19)* 0.38 (.18)*

Former gang involvement 2.03 (.28)* 1.49 (.26)* 0.76 (.23)*

Age -0.03 (.03) -0.03 (.03)

Male 1.24 (.12)* 0.77 (.11)*

Minority 0.29 (.49) 0.18 (.44)

Parent(s) educationa 0.08 (.06) 0.06 (.06)

Broken home 0.73 (.29)* 0.70 (.26)*

Rural 0.06 (.13) 0.02 (.12)

Household strain 0.43 (.13)* 0.34 (.12)*

Low self-controla 0.27 (.06)* 0.13 (.05)*

School attachmenta -0.47 (.06)* -0.29 (.06)*

School performancea 0.01 (.06) -0.02 (.05)

Parental attachmenta 0.03 (.07) -0.04 (.06)

Parental monitoringa -0.29 (.07)* -0.20 (.06)*

Delinquent peersa 0.94 (.05)*

Intercept -1.15 (.08)* -2.31 (.44)* -1.93 (.41)*

Variance (SE) 4.67 (.29) 3.72 (.24) 2.82 (.19)

b coefficient, SE standard error, unconditional model variance = 5.38

* p \ .05; N = 2,163, Persons 9 items = 32,406a Standardized (M = 0, SD = 1)

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behavior, while school attachment and parental monitoring decreased, delinquency

involvement. These finding extend our understanding of criminological theory to China.

Expanding the test of major postulates of criminological theory in a different cultural

setting is an important contribution to criminological research as it provides a broader test

of the robustness of such theory.

By introducing a measure of delinquent peers, Model 3 accounts for the nature of

respondents’ peer networks. A key finding in the literature is that gang involvement

contributes to delinquency above and beyond simply associating with delinquent peers

(Battin et al. 1998; Klein and Maxson 2006). We use this measure with caution, however,

as studies have shown that the relationship between delinquent peers and individual

delinquency could be inflated due to the projection of individual behaviors onto peers’

behaviors (Haynie and Osgood 2005; Meldrum et al. 2009; Weerman and Smeenk 2005).

We find that the introduction of the delinquent peers variable reduces the magnitude of the

relationship between gang involvement and delinquency by about 70 % from Model 1.

Given what is known about the nature of group processes and peer influence in groups such

as gangs, this finding is not unexpected. Similarly, the coefficients for the other explanatory

variables are reduced in magnitude; however, none were confounded entirely by the

addition of delinquent peers to the model. Once accounting for several of the most robust

predictors of crime and delinquency (Pratt and Cullen 2000; Pratt et al. 2010), our findings

indicate that the association between current and former gang involvement and the overall

tendency to engage in delinquency persists in the Chinese context. The fact that the effect

of former gang involvement remains net of influential theoretical controls is somewhat

unexpected, but we reserve discussion for the concluding section.

Two-Level Logistic IRT Mixed-Models Predicting Violence Specialization

Table 3 presents the results of the structural regression model (Eq. 3, above) relating the

covariates to the latent scores for violence specialization. Before detailing our findings, we

examine if there are individual differences in violence specialization. Following Osgood

and Schreck (2007), we divide the variance by the standard errors from an unconditional

model without explanatory covariates at level-2 to approximate a z test. The resulting value

of 13.9 is statistically significant (p \ .001), indicating that individual violence special-

ization is observed in these data and not attributed to chance. This is consistent with Melde

and Esbensen’s (2012) recent findings in a US school-based sample. We proceed by adding

level-2 explanatory covariates in a manner similar to the previous section.

Model 1 provides initial evidence that gang involvement is associated with violence

specialization in China. These findings indicate that, after adjusting for item severity (i.e.,

the base rate differences), current and former gang members engage in violent over non-

violent offenses by a log odds of 1.16 and 1.59, respectively. Turning to Model 2, these

relationships are hardly affected by the introduction of the explanatory covariates (with the

exception of the delinquent peers variable). Indeed, the log odds that current and former

gang members specialize in violent delinquency change by less than 5 percent. Further, the

variance in violence specialization declined from 3.7 in the unconditional model, to 3.3 and

2.7 in Models 1 and 2 (10 and 27 % explained, respectively). Peer delinquency is added in

the final model, Model 3. Unlike overall delinquency, where the magnitude of the gang

involvement coefficients reduced by about 70 % altogether, the log odds for the current

and former gang involvement coefficients remained remarkably robust. Notably, the for-

mer gang involvement coefficient not only remains statistically significant, the magnitude

of the effect exceeded that for current gang involvement. In addition to gang involvement,

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males and parental monitoring were associated with violent delinquency, while age and

parental attachment were associated with a predominance of non-violent delinquency,

which bears similarities and differences with what is known about specialization (McGloin

et al. 2011; Osgood and Schreck 2007; Piquero et al. 1999).

In summary, the results of these analyses demonstrate convergence with what is known

about differences between gang and non-gang youth in settings with different demographics,

political structures, social and economic structures, and cultural orientations. Not only is gang

involvement associated with increased involvement in delinquency, this finding is most

pronounced in the domain of violence. With regard to violence, our findings among Chinese

youth are consistent with what is known about gangs, gang membership, and violence con-

ceptually (e.g., Decker 1996), and what emerging research is reporting empirically (Melde

and Esbensen 2012). Perhaps most importantly, these findings are observed net of a host of

criminological theoretical constructs that have demonstrated predictive ability in diverse

research contexts (e.g., Antonaccio et al. 2010; Vazsonyi et al. 2001).

Discussion

Despite its size and world prominence, little is known about crime and delinquency in

China. While there is an emerging literature, many gaps in our knowledge remain. Unlike

the United States, where crimes known to the police, arrests, and victimization data have

Table 3 Relationships of explanatory variables to violent offending from two-level logistic mixed-models

Violent offending

Model 1 Model 2 Model 3

b SE b SE b SE

Current gang involvement 1.16 (.27)* 1.11 (.26)* 0.62 (.26)*

Former gang involvement 1.59 (.34)* 1.52 (.33)* 1.17 (.32)*

Age -0.20 (.04)* -0.20 (.04)*

Male 1.56 (.20)* 1.29 (.20)*

Minority 0.06 (.69) -0.08 (.67)

Parent(s) educationa 0.12 (.09) 0.11 (.09)

Broken home 0.52 (.39) 0.51 (.38)

Rural 0.24 (.19) 0.21 (.18)

Household strain 0.23 (.19) 0.19 (.18)

Low self-controla -0.06 (.08) -0.16 (.08)#

School attachmenta -0.02 (.09) 0.08 (.09)

School performancea -0.01 (.09) -0.02 (.09)

Parental attachmenta -0.21 (.10)* -0.25 (.10)*

Parental monitoringa 0.19 (.10)* 0.23 (.10)*

Delinquent peersa 0.45 (.09)*

Variance (SE) 3.31 (.47) 2.69 (.41) 2.45 (.37)

b coefficient, SE standard error, unconditional model variance = 3.69, N = 2,163, Persons 9Items = 32,406

* p \ .05; # p = .058a Standardized (M = 0, SD = 1)

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been collected for decades and validated through a number of procedures, the state of

Chinese crime statistics remains underdeveloped. Decker and Pyrooz (2010: 149) noted

that the ‘‘picture [of gangs and violence] in Africa and Asia–Pacific remains partly obscure

because of a lack of reliable data.’’ This places added importance on the use of method-

ologies that can provide alternatives to official crime statistics. In the US and Europe, self-

reported methodologies were used to provide alternatives to official crime statistics as well

as additional information about the nature of offenders and victims that was not available

from official data. In the US, self-reported delinquency studies provide important alter-

natives to official crime statistics on a number of important issues, notably the relationship

between race and involvement in delinquency (Hindelang et al. 1981) and male–female

differentials in delinquent participation. Self-reported delinquency methodologies also

allow for the addition of important demographic and theoretical constructs that allow for

fuller explanations of the causes of delinquency.

The use of multi-level IRT modeling to examine overall delinquency and violence

specialization makes an important contribution to understanding the nature of delinquency

and its correlates in China. Osgood and Schreck (2007) highlighted how this methodology

avoids the limitations of other approaches to detect specialization (e.g., forward special-

ization coefficient, diversity index). The application of this methodology to China allowed

us to assess whether there are systematic individual differences among youth and young

adults in types of offending. We answer this question in the affirmative, finding patterns of

violence specialization and statistical correlates of such patterns. Given the strong theo-

retical and empirical link between gang involvement and violence (Decker 1996; Thorn-

berry et al. 2003), we extended the recent work of Melde and Esbensen (2012) by

providing a multivariate assessment of the relationship, albeit with cross-sectional data.

With this in mind, we concentrate on larger points that merit further discussion.

First, this study has demonstrated that the use of self-report methodology in China is

feasible, with school-based administration producing high response rates and reliable and

valid findings. The rate of response exceeded 90 % and item non-response, while present, did

not introduce serious problems to the analyses. In addition, the rank ordering of involvement

in violent, property, and substance use offenses is consistent with prior work in the US. The

results reported here are consistent with many of the school-based self-report studies con-

ducted in the United States (Esbensen and Weerman 2005). A substantial proportion of the

respondents reported levels of involvement in various forms of delinquency and gang

involvement. Eleven percent of respondents indicated that they had been involved in a gang

and over one-half of the sample reported engaging delinquency over the previous 12 months.

This indicates that at least for these respondents in this location, social constraints against

reporting involvement in anti-social behavior do not inhibit levels of reporting.

Second, the results affirm the successful transferability of theoretical constructs in

criminology to explaining delinquency among Chinese youth and emerging adults. The

levels of self-reported delinquency, while lower than in the US, were sufficient to provide

enough variation to examine well-known criminological theories. We find that household

strains, low self-control, school and parental attachment, parental monitoring, and delin-

quent peers were associated with the tendency to engage in delinquency or the tendency to

specialize in violence. These findings take their place alongside other international work

(e.g., Vazsonyi et al. 2001) that documents the utility of well-developed criminological

theory in diverse international populations. The finding regarding the effect of delinquent

peers stands out as particularly important in our results. Having delinquent peers is an

important variable in research on participation in crime in a large body of American

research (Akers 2009). However, the effect in our data is particularly strong, and partially

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accounts for the association between gang involvement and overall and violent delin-

quency. Caution should be exercised when evaluating the robustness of the peer delin-

quency effect, as conceptual and methodological concerns have been raised about

projecting individual onto peer behaviors and viewpoints (Haynie and Osgood 2005;

Meldrum et al. 2009; Weerman and Smeenk 2005). Groups matter in the commission of

delinquency in China—potentially more strongly than in American and European research.

Collective action is at work influencing the behaviors of youth and young adults. This

suggests that future research in the Chinese context must examine the role of gang

membership as well as delinquent peers to understand offending in this context. Identifying

both the similarities and differences in the behaviors and the mechanisms linked to such

behaviors between gang and non-gang delinquent peer groups would be beneficial not only

conceptually for thinking about the nature of peers, but also for crafting responses to

address peer-related delinquency. In addition, future research in China should more closely

examine the age-crime curve, in order to more accurately determine the convergence

between findings in the US and China.

Third, the Chinese context joins a number of settings where a positive association

between gang involvement and delinquency was found. Respondents involved in gangs had

a greater tendency to engage in delinquency than their non-gang counterparts. This rela-

tionship becomes more pronounced in terms of violent offending, diverging from Zhang

et al.’s (1997) findings that gang crime was not disproportionately serious, but is consistent

with emerging US evidence that the onset of gang membership corresponds to increased

violence specialization (Melde and Esbensen 2012). It is important to note that these

findings were observed net of several prominent correlates of crime and delinquency (Pratt

and Cullen 2000; Pratt et al. 2010). This parallels consistent findings from the US and

emerging findings from Europe supporting a gang membership invariance hypothesis. That

is, at the individual level the positive statistical relationship between gang involvement and

delinquency is invariant despite the geographic, cultural, and political differences across

contexts. The literature on gangs and delinquency has matured in significant ways over the

last two decades, to the point that after modeling within- and between-individual differ-

ences that account for a host of confounding selection factors, causal language can be

invoked (Krohn and Thornberry 2008). Of course, it is premature to reach this conclusion

based on the findings presented in the current study given the cross-sectional data and

analytic strategy. Yet, this study has moved this line of research forward by at least ruling

out several prominent extraneous influences that might explain away the association of

gang involvement with delinquency in a Chinese setting. We encourage further tests of this

relationship using longitudinal data; however, the current state of research design in China

does not appear to support such tests.

With the above point in mind, the finding that former gang involvement predicts the

overall tendency to offend and violence specialization at a rate equal to or greater than

current gang involvement exposes a limitation of our research. Cross-sectional data present

challenges to evaluating the causal order of this relationship, therefore we rely on theory

and research to guide our study (Akers 2009; Krohn and Thornberry 2008; Thornberry

et al. 2003). Yet, the former gang involvement finding is atypical in gang research.

Although our data prevent us from more fully parsing out this relationship, we offer several

reasons that may account for this finding. First, the stigma of gang membership may last

beyond disengaging from gangs. If the social exclusion associated with gang membership

is not supplanted with integration into conventional social support systems in China, a

former gang member could be without the backing of his or her gang and without adequate

‘‘hooks’’ to support the avoidance of criminal involvement, such as employment or ties to

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family. Second, former gang members could have recently left the gang, therefore the

12 month time span could be referencing delinquent activities from time spent in the gang.

We point out, however, that most of the research on the gang/delinquency link specifies

contemporaneous rather than lagged effects. While this is consistent with Thornberry and

colleagues’ arguments (2003: 106), it opens up the possibility for findings comparable to

ours. Third, former gang members could have non-zero levels of gang embeddedness

(Pyrooz and Decker 2011; Pyrooz et al. 2012). Thus, while they are in the process of

reducing their social and emotional ties to the gang, gang embeddedness still influences

their behavior (Decker and Lauritsen 2002; Pyrooz et al. 2010; Pyrooz et al. 2012). In the

overall delinquency model (Table 2), the introduction of theoretical mechanisms and

statistical controls reduces the bivariate current gang involvement coefficient by over 80

percent, but the former gang involvement coefficient by 61 percent. This is consistent with

Melde and Esbensen’s (2011, 2012) and Bjerk’s (2009) reports on how dynamic selection

bias likely reduces the magnitude of current gang involvement effects. In other words, the

criminogenic mechanisms thought to influence delinquency remain influential for current

gang members (i.e., mediating gang membership), but are likely to improve for former

gang members as they are removed from gang processes thereby offering an alternative

explanation for this unusual finding. These are issues for data that are longitudinal with

measures of gang embeddedness to address. We are aware of no such data in the Chinese

context.

This research has established two important findings that can serve as a foundation for

future research. First, the use of self-reported methods of measuring involvement in

delinquency, gangs and theoretical constructs is feasible and yields information useful for

measuring delinquent involvement and testing criminological theories. Future research

should focus specifically on the correlates of violence, particularly among individuals who

self-identify as gang members. In addition, such research should examine more closely the

role of delinquent peers. Our findings provide strong support for understanding the group-

based nature of criminal involvement in China. Second, the level of delinquent involve-

ment provides sufficient statistical power to conduct multivariate analyses of such topics.

Future research should expand the use of such methodologies to additional cities and larger

samples. Including more diverse sites is an important next step in learning more about the

delinquent behavior of youth in China.

Acknowledgments We gratefully acknowledge the editors, Alex Piquero and Cathy Widom, and theanonymous reviewers for their valuable comments and suggestions.

Appendix

See Table 4.

Table 4 Descriptive statistics and item parameters of self-reported offending measures

% Yes Item severity SE

Non-violent offenses

Skipped classes without an excuse 34.9 % [Reference category]

Lied about your age to get into some place or to buy something 23.9 % -0.83 .09

Avoided paying for things such as movies, bus or subway rides 8.1 % -2.75 .12

Purposefully destroyed property that did not belong to you 8.8 % -2.62 .11

Illegally spray painted a wall or building 12.1 % -2.07 .10

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References

Akers RL (2009) Social learning and social structure: a general theory of crime and deviance. Transaction,New Brunswick

Allison PD (2001) Missing data. Sage, Thousand OaksAntonaccio O, Tittle CR, Botchkovar E, Kranidiotis M (2010) The correlates of crime and deviance:

additional evidence. J Res Crime Delinquency 47:297–328Bao W-N, Pi Y (2007) An empirical test of General Strain Theory from a matching perspective in social

support. Int J Offender Therapy Compar Criminol 51:9–24Battin SR, Hill KG, Abbott RD, Catalano RF, Hawkins JD (1998) The contribution of gang membership to

delinquency beyond delinquent friends. Criminology 36:93–116Bjerk D (2009) How much can we trust causal interpretations of fixed-effects estimators in the context of

criminality? J Quant Criminol 25:391–417Bouffard LA, Wright KA, Muftic LR, Bouffard JA (2008) Gender differences in specialization in intimate

partner violence: comparing the gender symmetry and violent resistance perspectives. Justice Q23:570–594

Brame R, Turner MG, Paternoster R (2010) Missing data problems in criminological research. In: WeisburdD, Piquero A (eds) Handbook of quantitative criminology. Springer, New York, pp 273–288

Bruneau T, Dammert L, Skinner E (2011) Maras: gang violence and security in Central America. Universityof Texas Press, Austin

Covey H (2010) Street gangs throughout the world. Charles C. Thomas, SpringfieldDecker SH (1996) Collective and normative features of gang violence. Justice Q 13:243–264Decker SH, Lauritsen J (2002) Leaving the gang. In: Ronald Huff C (ed) Gangs in America, 3rd edn. Sage,

Thousand OaksDecker SH, Pyrooz DC (2010) Gang violence across the world: In: Small arms survey 2010: gangs, groups,

and guns. Cambridge University Press, Cambridge, pp 128–155Decker SH, Pyrooz DC (2011) Gangs and the Internet: logging off and moving on. Council on foreign

relations. http://www.cfr.org/counterradicalization/save-supporting-document-leaving-gang/p26590Decker SH, Weerman F (2005) European street gangs and troublesome youth groups. AltaMira, LanhamDecker SH, Van Gemert F, Pyrooz DC (2009) Gangs, migration, and crime: the changing landscape in

Europe and the USA. J Int Migrat Integr 10:393–408Deng X, Cordilia A (1999) To get rich is glorious: rising expectations, declining control, and escalating

crime in contemporary China. Int J Offender Therapy Compar Criminol 43:211–229Dutton M (1997) The basic character of crime in contemporary China (Translation). The China Quarterly,

pp 160–177Egley A, Howell JC (2011) Highlights of the 2009 National Youth Gang Survey. Office of Juvenile Justice

and Delinquency Prevention, Washington, DC

Table 4 continued

% Yes Item severity SE

Stolen or tried to steal something worth less than RMB50 7.3 % -2.90 .12

Stolen or tried to steal something worth more than RMB50 3.8 % -3.96 .16

Gone into or tried to go into a building to steal something 4.6 % -3.64 .15

Stolen or tried to steal a motor vehicle 2.1 % -4.87 .21

Sold illegal drugs 2.0 % -4.99 .22

Violent offenses

Carried a hidden weapon for protection 11.2 % -0.71 .72

Hit someone with the idea of hurting them 8.1 % -1.39 .72

Attacked someone with a weapon 6.0 % -2.03 .72

Used a weapon or force to get money or things from people 3.0 % -3.48 .74

Been involved in gang fights 13.5 % -0.29 .71

Lower values of item severity (ci0) indicate greater item seriousness

270 J Quant Criminol (2013) 29:251–272

123

Author's personal copy

Esbensen F-A, Huizinga DJ (1993) Gangs, drugs and delinquency in a survey of urban youth. Criminology31:565–589

Esbensen F-A, Maxson CL (2012) Youth gangs in international perspective: results from the Eurogangprogram of research. Springer, New York

Esbensen F-A, Weerman F (2005) Youth gangs and troublesome youth groups in the United States and theNetherlands: a cross-national comparison. Eur J Criminol 2:5–37

Esbensen F-A, Winfree LT Jr, He N, Taylor TJ (2001) Youth gangs and definitional issues: when is a gang agang and why does it matter? Crime Delinquency 47:105–130

Friday PC, Ren X, Weitekamp E (2003) Delinquency in a Chinese Birth Cohort. Final Report. U.S.Department of Justice, Washington, DC

Friday PC, Ren X, Weitekamp E, Kerner H-J, Taylor T (2005) A Chinese birth cohort: theoretical impli-cations. J Res Crime Delinquency 42:123–146

Gatti U, Haymoz S, Schadee HMA (2011) Deviant youth groups in 30 countries: results from the secondInternational Self-Report Delinquency Study. Int Crim Justice Rev 21:208–224

Gordon RA, Lahey BB, Kawai E, Loeber R, Stouthamer-Loeber M, Farrington DP (2004) Antisocialbehavior and youth gang membership: selection and facilitation. Criminology 42:55–87

Gottfredson MR, Hirschi T (1990) A general theory of crime. Stanford University Press, StanfordGreenberger E, Chen C, Beam M, Whang S-M, Dong Q (2000) The perceived social contexts of adoles-

cents’ misconduct: a comparative study of youths in three cultures. J Res Adolesc 10:365–388Hagedorn J (2007) Gangs in the global city. University of Illinois Press, UrbanaHaynie DL, Osgood DW (2005) Reconsidering peers and delinquency: how do peers matter? Soc Forces

84:1109–1130Hindelang M, Hirschi T, Weis J (1981) Measuring delinquency. Sage, Beverly HillsHirschi T (1969) Causes of delinquency. University of California Press, BerkeleyHirschi T, Selvin HC (1967) Delinquency research: an appraisal of analytic methods. Free Press, New YorkHoltfreter K, Reisig MD, Piquero NL, Piquero AR (2010) Low self-control and fraud: offending, victim-

ization, and their overlap. Crim Justice Behav 37:188–203Jessor R, Turbin MS, Costa FM, Dong Q, Zhang H, Want C (2003) Adolescent problem behavior in China

and the United States: a cross-national study of psychosocial protective factors. J Res Adolesc13:329–360

Klein MW (1995) The American street gang: its nature, prevalence, and control. Oxford University Press,New York

Klein MW, Maxson CL (2006) Street gang patterns and policies. Oxford University Press, New YorkKlein M, Kerner H-J, Maxson CL, Weitekamp E (2001) The Eurogang paradox: street gangs and youth

groups in the U.S. and Europe. Springer, DordrechtKrohn MD, Thornberry TP (2008) Longitudinal perspectives on adolescent street gangs. In: Liberman AM

(ed) The long view of crime: a synthesis of longitudinal research. National Institute of Justice,Washington, DC, pp 128–160

Liang B, Lu H (2010) Internet development, censorship, and cyber crimes in China. J Contemp Crim JusticeI:103–120

Liu J (1999) Social capital and covariates of re-offending risk in the Chinese context. Int Crim Justice Rev9:39–55

Liu J (2008) Data sources in Chinese crime and criminal justice research. Law Soc Change 50:131–147Liu J, Zhang L, Messner SE (2001) Crime and social control in a changing China. Greenwood Press,

WestportMaxson CL (1998) Gang members on the move. Office of Juvenile Justice and Delinquency Prevention,

Washington, DCMcGloin JM, Schreck CJ, Stewart EA, Ousey GC (2011) Predicting the violent offending: the discriminant

validity of the subculture of violence. Criminology 49:767–794Melde C, Esbensen F-A (2011) Gang membership as a turning point in the life course. Criminology,

49:513–552Melde C, Esbensen F-A (2012) Gangs and violence: Disentangling the impact of gang membership on the

level and nature of offending. J Quantitat Criminol (in press) doi:10.1007/s10940-012-9164-zMeldrum RC, Young JTN, Weerman FM (2009) Reconsidering the effect of self-control and delinquent

peers: implications of measurement for theoretical significance. J Res Crime Delinquency 46:353–376Miller W (1982) Crime by youth gangs and groups in the United States. National Institute of Juvenile Justice

and Delinquency Prevention, Washington, DCNgai N-P, Cheung C-K, Ngai SS-Y (2007) Cognitive and social influences on gang involvement among

delinquents in three Chinese cities. Adolescence 42:381–403

J Quant Criminol (2013) 29:251–272 271

123

Author's personal copy

Osgood DW, Schreck CJ (2007) A new method for studying the extent, stability, and predictors of individualspecialization in violence. Criminology 45:273–312

Papachristos AV (2005) Gang world. Foreign Policy, March/April, pp 48–55Piquero AR (2000) Frequency, specialization, and violence in offending careers. J Res Crime Delinquency

37:392–418Piquero AR, Paternoster R, Brame R, Mazerolle P, Dean CW (1999) Onset age and specialization in

offending behavior. J Res Crime Delinquency 36:275–299Piquero AR, MacIntosh R, Hickman M (2002) The validity of a self-reported delinquency scale: compar-

isons across gender, age, race, and place of residence. Sociol Methods Res 30:492–529Piquero AR, Farrington DP, Blumstein A (2003) The criminal career paradigm: Background and recent

developments. In: Tonry M (ed) Crime and justice: a review of research. University of Chicago Press,Chicago, vol 30, pp 359–506

Pratt TC, Cullen FT (2000) The empirical status of Gottfredson and Hirschi’s general theory of crime: ameta-analysis. Criminology 38:931–964

Pratt TC, Cullen FT, Sellers CS, Winfree LT Jr, Madensen TD, Daigle LE, Fearn NE, Gau JM (2010) Theempirical status of social learning theory: a meta-analysis. Justice Q 27:765–802

Pyrooz DC, Decker SH (2011) Motives and methods for leaving the gang: understanding the process of gangdesistance. J Crim Justice 39:417–425

Pyrooz DC, Decker SH, Webb VJ (2010) The ties that bind: desistance from gangs. Crime Delinquency (inpress) doi:10.1177/0011128710372191

Pyrooz DC, Sweeten G, Piquero AR (2012) Continuity and change in gang membership and gang em-beddedness. J Res Crime Delinquency (in press) doi:10.1177/0022427811434830

Raudenbush SW, Johnson C, Sampson RJ (2003) A multivariate, multilevel Rasch model with application toself-reported criminal behavior. Sociol Methodol 33:169–211

Reisig MR, Pratt TC (2011) Low self-control and imprudent behavior revisited. Deviant Behav 32:589–625Reisig MD, Wolfe SE, Holtfreter K (2011) Legal cynicism, legitimacy, and criminal offending: the non-

confounding effect of low self-control. Crim Justice Behav 38:1265–1279Rubin DB (1987) Multiple imputation for nonresponse in surveys. Wiley, New YorkRubin DB (1996) Multiple imputation after 18 ? years. J Am Stat Assoc 91:473–489Spergel IA, Curry GD (1990) Strategies and perceived agency effectiveness in dealing with the youth gang

problem. In: Huff CR (ed) Gangs in America. Sage Publications, Newbury Park, pp 288–309Sweeten G (2012) Scaling criminal offending. J Quantitat Criminol (in press)Tangney JP, Baumeister RF, Boone AL (2004) High self-control predicts good adjustment, less pathology,

better grades, and interpersonal success. J Pers 72:271–324Thornberry TP, Krohn MD (2000) The self-report method for measuring delinquency and crime. In:

Criminal Justice 2000 (vol. 4): Measurement and analysis of crime and justice. National Institute ofJustice, Washington, DC

Thornberry TP, Krohn MD, Lizotte AJ, Smith CA, Tobin K (2003) Gangs and delinquency in develop-mental perspective. Cambridge University Press, Cambridge

Van Gemert F, Peterson D, Lien I-L (2008) Street gangs, migration, and ethnicity. Willan, Portland, ORVazsonyi A, Pickering LE, Junger M, Hessing D (2001) An empirical test of a general theory of crime: a

four-nation comparative study of self-control and the prediction of deviance. J Res Crime Delinquency38:91–131

Webb VJ, Katz CM, Decker SH (2006) Assessing the validity of self-reports by gang members: results fromthe Arrestee Drug Abuse Monitoring program. Crime Delinquency 52:232–252

Webb VJ, Ren L, Zhao J, He N, Marshall IH (2011) A comparative study of youth gangs in China and theUnited States: definition, offending and victimization. Int Crim Justice Rev 21:225–242

Weerman F, Smeenk WH (2005) Peer similarity in delinquency for different types of friends: a comparisonusing two measurement methods. Criminology 43:499–524

Weerman F, Maxson CL, Esbensen F-A, Aldridge J, Medina J, van Gemert F (2009) Eurogang programmanual: background, development, and use of the Eurogang instruments in multi-site, multi-methodcomparative research. http://www.umsl.edu/*ccj/eurogang/EurogangManual.pdf

Wei Z, Homel R, Prichard J, Xu J (2004) Patterns of juvenile offending in Shanghai and Brisbane. Aust N ZJ Criminol 37:32–51

Zhang L (2008) Juvenile delinquency and justice in contemporary China: a critical review of the literatureover 15 Years. Crime Law Soc Change 50:149–160

Zhang L, Messner SF, Lu Z, Deng X (1997) Gang crime and its punishment in China. J Crim Justice25:289–302

Zhang L, Messner SF, Liu J (2008) A critical review of recent literature on crime and criminal justice inChina: research findings, Challenges and prospects. Crime Law Soc Change 50:125–130

272 J Quant Criminol (2013) 29:251–272

123

Author's personal copy