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Understanding the Gap in Self-Reported Offending by Race: a Meta-Analysis

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Abstract

Self-report data is valuable to criminologists for its potential at revealing offending patterns free from biases affecting official data obtained by police. An issue of great interest is whether racial differences in crime rates evident in official data persist when analyzing self-report offending data. In their landmark study, Elliott and Ageton (1980) argued that early self-report crime studies failed to find evidence of race differences primarily due to measurement limitations. They argued previous studies focused on minor offenses, contained item overlap and did not precisely measure high frequency offending, all of which obscured differences by race. After addressing these limitations through the design of the National Youth Survey, Elliott and Ageton reported evidence more consistent with official crime data, though differences were somewhat contingent on offense type and scaling method employed. Lessons of the Elliott and Ageton study placed an important imprint on the study of race and self-reported offending. Yet, a core question persists: Are Elliott and Ageton’s conclusions regarding the race-crime relationship confirmed by nearly four decades of research? To address this question, the current study uses meta-analysis methods to synthesize research since 1980 that estimates the association between self-reported measures of racial identification and self-reported offending. Findings suggest that while there is evidence of a statistically significant association between some measures of race and self-reported crime, nearly all measured relationships are extremely weak, generally approaching zero.

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Notes

  1. Our focus in this study is on self-reported offending. We note that data from the National Crime Victimization Survey (NCVS) may also provide some insights regarding race of offenders in crime incidents. It tends to show racial differences in offending closer to racial differences found in official data than self-reported offending data (Sampson and Lauristen, 1997; Steffensmeier et al., 2011). However, a limitation of using victim data is that it only offers measures of offender race in offenses that occur face-to-face with a solo-offender. Moreover, as a measure of race-differences in offending, victimization data requires that victims are able to identify the offender’s race and do so with accuracy.

  2. It is worth noting that as others have explored (Brame, Fagan, Piquero, Schubert and Steinberg, 2004; Farrington, Loeber, Stouthamer-Loeber, Van Kammen and Schmidt, 1996; Hindelang, Hirschi and Weis, 1981; Huizinga and Elliott, 1986; Maxfield, Weiler and Widom, 2000) there is a potential that members of different races may not be equally forthcoming in admitting past crimes, leading to potential differences in the validity of self-report measures. Previous research is mixed as to whether such differences exist, and if they do, as to which racial groups over or under report. While this is a potentially important issue, it is beyond the scope of the current paper, and we believe that it is vital to at least have a baseline understanding of what self-report data currently reveals in regard to self-report offending.

  3. A few studies included in our analysis measured drug offenses in addition to other crimes. Often, drug use measures are included into broader crime indices. If drug items were included in crime indices with a range of other serious and minor offenses, we coded them in the “general” offending category described later. Otherwise, they were included in our “minor” offending category.

  4. Estimating this statistic from different reported statistics may add some measurement error, the impact of which we acknowledge is unknown. An alternative approach, which has its own substantial limitations, would be to only make comparisons between small numbers of studies that report the exact same statistics. Because of our interest in synthesizing results across all available studies in a common metric, we have chosen the former approach and any limitations that choice entails.

  5. We note that studies employed both ordinal and interval-ratio frequency scales. The former are those that lump together a range of specific offense counts (e.g., 1 = “1 or 2 times”, 2 = “three to four times”) whereas interval-ratio measures use the specific raw count of offenses reported by a respondent.

  6. Although these four datasets are the only ones with sufficient information to code for separate analysis, the studies included in our full analysis draw on a much larger body of criminological datasets. In addition to studies of locally selected samples—such as undergraduate university students—several additional datasets of prominence in criminology are used in one or more studies included in the meta-analysis. Examples include the Denver Youth Survey, Project on Human Development in Chicago Neighborhoods, Pathways to Desistance Study, Seattle Social Development Study, National Longitudinal Survey of Youth, and the Rochester Youth Development Study.

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Authors and Affiliations

  1. Department of Sociology and Criminal Justice, Old Dominion University, 6000 Batten Arts and Letters, Norfolk, VA, 23529, USA

    Tracy WP Sohoni

  2. Department of Sociology, College of William & Mary, 100 Ukrop Way, Williamsburg, VA, 23185, USA

    Graham C. Ousey & Alisha Mehdi

  3. Department of Sociology and Criminal Justice, Old Dominion University, 6000 Batten Arts and Letters, Norfolk, VA, 23529, USA

    Erica Bower

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  1. Tracy WP Sohoni
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  2. Graham C. Ousey
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  3. Erica Bower
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  4. Alisha Mehdi
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Correspondence to Tracy WP Sohoni.

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Appendices

Appendix 1. List of Articles Included in the Meta-Analysis

Bachman, R., & Peralta, R. (2002). The relationship between drinking and violence in an adolescent population: Does gender matter? Deviant behavior, 23(1), 1–19.

Barbieri, N., & Craig, J. M. (2018). Do the Effects of Strain and Religiosity on Criminal Coping Differ by Race and Ethnicity? Crime & Delinquency, 64(6), 807–828.

Barnes, G. M., Welte, J. W., & Hoffman, J. H. (2002). Relationship of alcohol use to delinquency and illicit drug use in adolescents: Gender, age, and racial/ethnic differences. Journal of Drug Issues, 32(1), 153–178.

Bellair, P. E., & McNulty, T. L. (2005). Beyond the bell curve: Community disadvantage and the explanation of black-white differences in adolescent violence. Criminology, 43(4), 1135–1168.

Brauer, J. R. (2009). Testing social learning theory using reinforcement’s residue: A multilevel analysis of self-reported theft and marijuana use in the national youth survey. Criminology, 47(3), 929–970.

Chauhan, P., Reppucci, N. D., Burnette, M., & Reiner, S. (2010). Race, neighborhood disadvantage, and antisocial behavior among female juvenile offenders. Journal of Community Psychology, 38(4), 532–540.

Eitle, D., & Turner, R. J. (2003). Stress exposure, race, and young adult male crime. The Sociological Quarterly, 44(2), 243–269.

Elliott, D. S., & Ageton, S. S. (1980). Reconciling race and class differences in self-reported and official estimates of delinquency. American sociological review, 95–110.

Farrington, D. P., Loeber, R., & Stouthamer-Loeber, M. (2003). How can the relationship between race and violence be explained. Violent crimes: Assessing race and ethnic differences, 213–237.

Felson, R. B., Deane, G., & Armstrong, D. P. (2008). Do theories of crime or violence explain race differences in delinquency? Social Science Research, 37(2), 624–641.

Felson, R. B., & Kreager, D. A. (2015). Group differences in delinquency: What is there to explain? Race and Justice, 5(1), 58–87.

Giordano, P. C., Cernkovich, S. A., & Rudolph, J. L. (2002). Gender, crime, and desistance: Toward a theory of cognitive transformation. American journal of sociology, 107(4), 990–1064.

Haynie, D. L., & Payne, D. C. (2006). Race, friendship networks, and violent delinquency. Criminology, 44(4), 775–805.

Haynie, D. L., Weiss, H. E., & Piquero, A. (2008). Race, the economic maturity gap, and criminal offending in young adulthood. Justice quarterly, 25(4), 595–622.

Hoffmann, J. P. (2003). A contextual analysis of differential association, social control, and strain theories of delinquency. Social forces, 81(3), 753–785.

Hoffmann, J. P., & Dufur, M. J. (2008). Family and school capital effects on delinquency: Substitutes or complements? Sociological Perspectives, 51(1), 29–62.

Hoffmann, J. P., & Xu, J. (2002). School activities, community service, and delinquency. Crime & Delinquency, 48(4), 568–591.

Holtfreter, K., Reisig, M. D., Leeper Piquero, N., & Piquero, A. R. (2010). Low self-control and fraud: Offending, victimization, and their overlap. Criminal Justice and Behavior, 37(2), 188–203.

Hong, J. S., Ryou, B., & Piquero, A. R. (2017). Do family-level factors associated with bullying perpetration and peer victimization differ by race? Comparing European American and African American youth. Journal of interpersonal violence, 0886260517714441.

Huizinga, D., & Elliott, D. S. (1987). Juvenile offenders: Prevalence, offender incidence, and arrest rates by race. Crime & Delinquency, 33(2), 206–223.

Jones, S., & Lynam, D. R. (2009). In the eye of the impulsive beholder: The interaction between impulsivity and perceived informal social control on offending. Criminal Justice and Behavior, 36(3), 307–321.

Kaufman, J. M. (2005). Explaining the race/ethnicity–violence relationship: Neighborhood context and social psychological processes. Justice quarterly, 22(2), 224–251.

Lee, D. R., & Cohen, J. W. (2008). Examining strain in a school context. Youth Violence and Juvenile Justice, 6(2), 115–135.

Loeber, R., Farrington, D. P., Hipwell, A. E., Stepp, S. D., Pardini, D., & Ahonen, L. (2015). Constancy and change in the prevalence and frequency of offending when based on longitudinal self-reports or official records: Comparisons by gender, race, and crime type. Journal of developmental and life-course criminology, 1(2), 150–168.

Lynam, D. R., Caspi, A., Moffit, T. E., Wikström, P.-O., Loeber, R., & Novak, S. (2000). The interaction between impulsivity and neighborhood context on offending: the effects of impulsivity are stronger in poorer neighborhoods. Journal of abnormal psychology, 109(4), 563.

Matsueda, R. L., Kreager, D. A., & Huizinga, D. (2006). Deterring delinquents: A rational choice model of theft and violence. American sociological review, 71(1), 95–122.

McCarthy, B., & Casey, T. (2008). Love, sex, and crime: Adolescent romantic relationships and offending. American sociological review, 73(6), 944–969.

McNulty, T. L., & Bellair, P. E. (2003). Explaining racial and ethnic differences in adolescent violence: Structural disadvantage, family well-being, and social capital. Justice quarterly, 20(1), 1–31.

McNulty, T. L., & Bellair, P. E. (2003). Explaining racial and ethnic differences in serious adolescent violent behavior. Criminology, 41(3), 709–747.

Melde, C., & Esbensen, F.-A. (2013). Gangs and violence: Disentangling the impact of gang membership on the level and nature of offending. Journal of quantitative criminology, 29(2), 143–166.

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Ousey, G. C., & Kubrin, C. E. (2018). Immigration and crime: Assessing a contentious issue. Annual Review of Criminology, 1, 63–84.

Pardini, D., Bechtold, J., Loeber, R., & White, H. (2015). Developmental trajectories of marijuana use among men: examining linkages with criminal behavior and psychopathic features into the mid-30s. Journal of research in crime and delinquency, 52(6), 797–828.

Pesta, R. (2018). Labeling and the Differential Impact of School Discipline on Negative Life Outcomes: Assessing Ethno-Racial Variation in the School-to-Prison Pipeline. Crime & Delinquency, 64(11), 1489–1512.

Peterson, D., Esbensen, F.-A., Taylor, T. J., & Freng, A. (2007). Youth violence in context: The roles of sex, race, and community in offending. Youth Violence and Juvenile Justice, 5(4), 385–410.

Piquero, N.L., & Sealock, M. D. (2010). Race, crime, and general strain theory. Youth Violence and Juvenile Justice, 8(3), 170–186.

Pratt, T.C., Turanovic, J.J., Fox, K.A., & Wright, K.A. (2014). Self-control and victimization: A meta-analysis. Criminology, 52, 87–116.

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Ray, J. V., Frick, P. J., Thornton, L. C., Wall Myers, T. D., Steinberg, L., & Cauffman, E. (2017). Callous–unemotional traits predict self-reported offending in adolescent boys: The mediating role of delinquent peers and the moderating role of parenting practices. Developmental psychology, 53(2), 319.

Reisig, M. D., Wolfe, S. E., & Holtfreter, K. (2011). Legal cynicism, legitimacy, and criminal offending: The nonconfounding effect of low self-control. Criminal Justice and Behavior, 38(12), 1265–1279.

Rocque, M., Posick, C., & Paternoster, R. (2016). Identities through time: An exploration of identity change as a cause of desistance. Justice quarterly, 33(1), 45–72.

Sampson, R. J., Morenoff, J. D., & Raudenbush, S. (2005). Social anatomy of racial and ethnic disparities in violence. American Journal of Public Health, 95(2): 224–232.

Schroeder, R. D., Bulanda, R. E., Giordano, P. C., & Cernkovich, S. A. (2010). Parenting and adult criminality: An examination of direct and indirect effects by race. Journal of Adolescent Research, 25(1), 64–98.

Smith, C. A., Ireland, T. O., & Thornberry, T. P. (2005). Adolescent maltreatment and its impact on young adult antisocial behavior. Child abuse & neglect, 29(10), 1099–1119.

Steffensmeier, D., Feldmeyer, B., Harris, C. T., & Ulmer, J. T. (2011). Reassessing trends in black violent crime, 1980–2008: Sorting out the “Hispanic effect” in Uniform Crime Reports arrests, National Crime Victimization Survey offender estimates, and US prisoner counts. Criminology, 49(1), 197–251.

Tsang, S. (2018). Troubled or traumatized youth? The relations between psychopathy, violence exposure, posttraumatic stress disorder, and antisocial behavior among juvenile offenders. Journal of aggression, maltreatment & trauma, 27(2), 164–178.

Walters, G. D. (2015). A multi-wave cross-lagged regression analysis of the Youth Psychopathic Traits Inventory and Self-Reported Offending. Journal of Criminal Justice, 43(4), 327–336.

Watts, S. J. (2018). When Does Religion Matter With Regard to Crime? Examining the Relationship Between Genetics, Religiosity, and Criminal Behavior. Criminal Justice and Behavior, 45(8), 1192–1212.

Watts, S. J., & McNulty, T. L. (2015). Delinquent peers and offending: Integrating social learning and biosocial theory. Youth Violence and Juvenile Justice, 13(2), 190–206.

Williams, J. H., Ayers, C. D., Abbott, R. D., Hawkins, J. D., & Catalano, R. F. (1999). Racial differences in risk factors for delinquency and substance use among adolescents. Social Work Research, 23(4), 241–256.

Williams, J. H., Van Dorn, R. A., Ayers, C. D., Bright, C. L., Abbott, R. D., & Hawkins, J. D. (2007). Understanding race and gender differences in delinquent acts and alcohol and marijuana use: A developmental analysis of initiation. Social Work Research, 31(2), 71–81.

Wolfe, S. E. (2015). Low self-control, gender, race, and offending in late life. Psychology, Crime & Law, 21(5), 426–451.

Wolfe, S. E., Reisig, M. D., & Holtfreter, K. (2016). Low self-control and crime in late adulthood. Research on aging, 38(7), 767–790.

Wright, B. R. E., & Younts, C. W. (2009). Reconsidering the relationship between race and crime: Positive and negative predictors of crime among African American youth. Journal of research in crime and delinquency, 46(3), 327–352.

Zimmerman, G. M., & Messner, S. F. (2010). Neighborhood context and the gender gap in adolescent violent crime. American sociological review, 75(6), 958–980.

Zimmerman, G. M., & Messner, S. F. (2016). Examining change in adolescent street efficacy and its association with violent outcomes. Violence and victims, 31(6), 1183–1196.

Appendix 2

Table 5 Basic Characteristics of Studies Included in Meta-Analysis
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Sohoni, T.W., Ousey, G.C., Bower, E. et al. Understanding the Gap in Self-Reported Offending by Race: a Meta-Analysis. Am J Crim Just 46, 770–792 (2021). https://doi.org/10.1007/s12103-020-09571-z

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