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“From Your First Cigarette to Your Last Dyin’ Day”: The Patterning of Gang Membership in the Life-Course

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Abstract

Objective

Motivated by the reorientation of gang membership into a life-course framework and concerns about distinct populations of juvenile and adult gang members, this study draws from the criminal career paradigm to examine the contours of gang membership and their variability in the life-course.

Methods

Based on nine annual waves of national panel data from the NLSY97, this study uses growth curve and group-based trajectory modeling to examine the dynamic and cumulative prevalence of gang membership, variability in the pathways into and out of gangs, and the correlates of these pathways from ages 10 to 23.

Results

The cumulative prevalence of gang membership was 8 %, while the dynamic age-graded prevalence of gang membership peaked at 3 % at age 15. Six distinct trajectories accounted for variability in the patterning of gang membership, including an adult onset trajectory. Gang membership in adulthood was an even mix of adolescence carryover and adult initiation. The typical gang career lasts 2 years or less, although much longer for an appreciable subset of respondents. Gender and racial/ethnic disproportionalities in gang membership increase in magnitude over the life-course.

Conclusions

Gang membership is strongly age-graded. The results of this study support a developmental research agenda to unpack the theoretical and empirical causes and consequences of gang membership across stages of the life-course.

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Notes

  1. Both official and survey estimates involve self-report methodology to measure gang membership, although the former also includes additional filters. Barrows and Huff (2009) documented the criteria used by 10 states to document a gang member; self-identification was the only criterion used by all states and with the exception of Virginia, every state required at least two categories before someone can be defined as a gang member.

  2. Esbensen and Huizinga (1993) reported four years of data on gang membership and values were extrapolated based on ages that applied to at least two of the DYS cohorts (youth born in 1972, 1974, 1976, and 1978).

  3. Delinquent group participation was measured as follows: “During the past 12 months, were you part of a group or gang that did reprehensible acts?” (Lacourse et al. 2003, p. 186, emphasis added). The delinquent group component of this definition may contribute to such high rates of gang membership (e.g., 21 % at age 14 in Craig et al. (2002)).

  4. The definition that the NLSY97 presents to respondents is more restrictive than the commonly used Eurogang definition—“a street gangs is any durable, street-oriented youth group whose involvement in illegal activity is part of its group identity” (Klein and Maxson 2006: 4). Individual-level gang research does not typically preface gang membership self-nomination questions with a definition of a gang, therefore it is unknown whether such a procedure unduly influences results. The NLSY97 is commonly used to study gang member behavior (e.g., Bellair and McNulty 2009; Bjerk 2009; Tapia 2011) and the findings from these studies are consistent with research from sites using potentially less restrictive definitions.

  5. A measure of “ever” gang membership was presented to all respondents at Waves 1–5, although those who did not answer the measure of “current” gang membership were the universe for this question. There are some instances (~ 2 %) where respondents deny “current” gang membership, only report to “ever” gang membership and provide ages of onset and termination that overlap with Waves 2–5. Those who do not own up to gang membership until later waves are worth studying for conceptual and methodological reasons, including identity, gang embeddedness, criminal and noncriminal consequences, and the reliability and validity of self-nomination. There are defensible reasons for inclusivity, but the goal of the current study was to measure gang membership as close to the state as possible, therefore only Wave 1 “ever” gang membership was used to retrospectively capture onset and termination.

  6. The concerns about GBTM (see Sampson and Laub 2005; Skardhamar 2010) are centered mostly on the reification of “groups.” For the current study, careful consideration was given to avoid reification. In line with Brame et al. (2012: 485), GBTM is viewed as a valuable tool to identify “etiologically significant” trajectories of gang membership that may be used for “developing new theoretical propositions and testable hypotheses.” The observation of adulthood onset of gang membership would be most obvious example of the utility of GBTM—adolescent onset of gang membership is a common assumption. When common developmental growth patterns are assumed, a multivariate normal distribution of the growth parameters (i.e., HLM) is ideal (Nagin 2005; Raudenbush 2001). Of course, the life-course framework presented above anticipates qualitative differences in the growth patterns, with some research confirming such an expectation (e.g., Lacourse et al. 2003).

  7. The reported prevalence rate of gang membership in Snyder and Sickmund’s (2006) report using the NLSY97 is also 8 %. Their figure was based on the first five annual survey waves (p. 70) and an “ever” measure. It is unclear whether this estimate was nationally weighted. Using the methods described above, the current study finds a cumulative gang membership prevalence of 7 % by wave 5.

  8. The parameters for the models are as follows: cumulative (intercept = 1.67, linear term = 2.05, quadratic term = 0.29, and cubic term = 0.45) and dynamic (intercept = −1.32, linear term = −1.42, quadratic term = −0.48, and cubic term = 0.62), where p < .05 for all estimates.

  9. A 6-trajectory solution best fit the data according to several determinants of model fit, including the Bayesian Information Criterion (BIC = −4130), the group weighted Average Posterior Probability (AvePP = 0.81), and the mean Odds of Correct Classification (OCC = 35). All of the fit statistics exceed Nagin’s (2005) recommendations. More parsimonious 4- and 5-trajectory solutions produced better AvePP and OCC values, although statistically worse BIC values. The 6-trajectory solution was chosen because the objective of the current study was to understand a more complex reality surrounding the age grading of gang membership. The emergence of an adult-onset trajectory, comprising nearly one-fifth of the gang subsample, and better discerning the onset of adolescence gang membership, indicates that this solution better approximated this reality, consistent with the GBTM (Brame et al. 2012; Nagin 2005) and gang (Krohn and Thornberry 2008) literatures. While beyond the scope of the current study, the etiological and behavior significance of these trajectories remain a priority for future inquiry.

  10. Consistent with the hypothesis, these results are based on analyses using the full sample. When conducting the analysis using only the gang subsample it is noteworthy that statistical differences across the demographics of interest did not emerge until ages 14–15. In other words, in relation to Fig. 4, disproportionality is less a story of the “front half” of the growth curve than it is the “back half,” in terms of persistence and late onset.

  11. This value drops to 36 and 31% when the “adulthood” cut-point shifts to 19 and 20, respectively. Arnett’s (2000) proposed new developmental period of “emerging adulthood” confronts the traditional conceptualization of adolescence-to-adulthood transitions. It is unclear how well Arnett’s concept extends into the study of gangs, although Krohn et al. (2011) offer evidence on adolescent gang membership and precocious transitions during the transition to adulthood.

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Acknowledgments

This research was supported by a Graduate Research Fellowship from the National Institute of Justice (2011-JP-FX-0101) and the Office of Juvenile Justice and Delinquency Prevention (2011-JV-FX-0004). I am grateful for their support. The content and opinions expressed in this document are solely those of the author and do not necessarily reflect the views of these agencies. I would like to thank Scott Decker, Rick Moule, Gary Sweeten, and Vince Webb for their comments on this manuscript, and well as the editors of JQC and the anonymous reviewers.

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    David C. Pyrooz

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Pyrooz, D.C. “From Your First Cigarette to Your Last Dyin’ Day”: The Patterning of Gang Membership in the Life-Course. J Quant Criminol 30, 349–372 (2014). https://doi.org/10.1007/s10940-013-9206-1

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