Clarifying the Theoretical Tenets of the Symbolic Threat Perspective

Abstract

Although Tittle and Curran in 1988 found support for the symbolic threat hypothesis, no further empirical investigations of the perspective have occurred to explain the contingencies of juvenile justice decision-making. We argue that past research has neglected this multilevel theory by only focusing on the “symbolic threat” thesis component, mischaracterizing the perspective as an inequality theory, or classifying the model as a derivative of Blalock’s minority group threat perspective. We contend that the original formulation of the symbolic threat hypothesis is a distinctive theory and offers a viable alternative to inequality and other racial/threat theoretical perspectives. The current study empirically tests the perspective in its entirety by examining the interrelationships between county-level characteristics (i.e. youth and minority populations), a juvenile’s race/ethnicity, and engaging in “moral offenses” with juvenile justice decision-making. The findings provide insight into the influence of contextual factors on the social control of youth of different racial/ethnic backgrounds.

Keywords:

• Theory
• symbolic threat
• minorities
• juveniles
• juvenile court outcomes

Acknowledgement

The authors are grateful to Dr. Richard (Rick) Moule and Dr. John Cochran for their helpful insights on previous drafts of this article. The opinions in this article are solely those of the authors.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Michael J. Leiber is Chair and Professor in Criminology at the University of South Florida. He earned his doctorate in criminal justice from the State University of New York at Albany. His main research interests and publications lie in juvenile delinquency, juvenile justice, and race/ethnicity. Currently, he serves as the editor of the Midwestern Criminal Justice Association journal, the Journal of Crime & Justice.

Jennifer H. Peck is an Assistant Professor in the Department of Criminal Justice at the University of Central Florida. Her most recent research has been published in Crime and Delinquency, Criminal Justice and Behavior, and Law and Human Behavior. Her research interests include the role of race and ethnicity in the juvenile justice system and treatment of disadvantaged groups throughout juvenile court proceedings.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1 Tittle and Curran (1988) provide no theoretical or empirical justification for their “age threat” argument. Rather, they identify “age threat” as part of their “SES threat” hypothesis. According to Tittle and Curran, “High income people may be threatened by those with lower income; Whites may be threatened by minorities; or adults may be threatened by youth” (1988: 46). However, and as noted in the text, Tittle and Curran failed to find empirical support for the claim of an economic threat, and thus, it was not included as a theoretical component of their final perspective.

2 None of Tittle and Curran’s (1988) hypotheses or conclusions referenced Hispanic, Asian, or “Other” youth but rather nonwhites. One possible reason for a failure to discover differences between blacks and “Other” youth, notably Hispanics, may be due to the small number of “Other” minorities in the sample (N = 87) relative to blacks (N = 1,381) (p. 34).

3 Juveniles who were transferred by prosecutorial direct-file, statutory exclusion, or “once an adult, always an adult” are not in the data because their cases are automatically prosecuted in adult court. Judicially waived youth are not included because they would not be present at adjudication or judicial disposition. Tittle and Curran’s (1988) study also only focused on youth in the juvenile justice system.

4 Checks for multicollinearity indicated acceptable levels of shared correlation.

5 Tittle and Curran (1988) combined alcohol and drugs into one variable labeled as “drug offenses”. Alcohol offenses originally comprised 1.7% of our sample (N = 1,535), but only 19 of these referrals resulted in out-of-home placement at judicial disposition. Further, only 106 blacks and 142 Hispanics were charged with an alcohol offense. Due to this lack of variation, all referrals for alcohol offenses were removed from the sample.

6 Tittle and Curran (1988) did not specify the age range related to their concept of youthful populations. We measure the percentage of all individuals under the age of 18 in each county to use as a conservative indicator of the population of youth.

7 Prior studies that have examined the link between “threatening populations” and social control (see King & Wheelock, 2007) included a measure of Republican voting as a contextual indicator of punishment. Counties that represent greater proportions of conservative/Republican voters may be more punitive in their juvenile justice decision-making/sanctioning and therefore included as a control variable in multilevel models of court outcomes.

8 Although past research has found race effects by differentiating various out-of-home placements as a dispositional outcome (i.e., group homes, foster care, training schools.) (Fader, Kurlychek, & Morgan, 2014; Cochran & Mears, 2015), we treated judicial disposition as a dichotomous variable. This decision is based on our sample which only includes delinquent referrals, and none of the cases resulted in certain placement options (i.e., foster care, group homes). While it is important to delve deeper into different types of out-of-home placement youth receive, having a youth taken out of his or her home, whether for good intentions or the result of bias or fear on the part of decision-makers, has a significant negative psychological and social impact on a youth (Feld, 1999; Platt, 1977). As our findings will show, being black or Hispanic increased the likelihood of receiving an out-of-home placement relative to comparable whites. Thus, our operationalization of judicial disposition did not obscure the findings of racial/ethnic effects at this stage.

9 The calculated z-scores from coefficient comparison tests are available upon request from the lead author. Heckman’s (1974) two-stage estimator was originally employed with a hazard rate to correct for potential sample selection bias at the dispositional stage. The second step in the Heckman procedure is to include the hazard rate as a predictor in an ordinary least squares (OLS) regression equation. Both dependent variables in the current study are categorical outcomes; therefore, it is inappropriate to utilize the Heckman bias correction procedure in a multilevel model with binary dependent variables.