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Using Path Analysis to Explain Racialized Support for Punitive Delinquency Policies

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Abstract

Objectives

Recent evidence suggests that typifying violent juvenile delinquency as a Black phenomenon may increase support for punitive juvenile justice policies. However, the research to date has not yet explored various theoretical explanations for this relationship. In particular, theory suggests that racialized punitiveness may be explained by (1) the adoption of dispositional attributions toward delinquency, (2) the failure to empathetically identify with delinquents, and (3) the belief that juveniles possess adult criminal intent and lack childhood naivety. The current study addresses this gap to determine the mediating associations between each of these factors and the racial stereotypes-punitiveness link.

Methods

Path analysis is conducted to determine the direct and indirect associations of each of the proposed mediators. In deriving the measures for the analyses, we also make the first attempt at operationalizing empathy specifically toward offenders.

Results

The findings suggest that those who racially typify violent delinquency are more likely to attribute juvenile crime to dispositional causes, empathize less with violent juvenile offenders, and believe young violent offenders possess adult criminal intentions, which in turn, leads to increased punitiveness.

Conclusion

The findings provide support for three theoretical predictions of racialized punitiveness. Empathy emerges as the strongest predictor of punitive attitudes and accounts for the largest proportion of the relationship between racial typification and support for punitive delinquency policies.

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Notes

  1. Parens patriae translates to “father of the people.” As part of the doctrine of parens patriae, the court was given the ability to intervene as a parental figure to determine what is in the best interests of the child (Feld 1999a, b; Soung 2011).

  2. Cook and Campbell (1979: 83) are clear that in their view, in studies focused on testing theories, “external validity is of relatively little importance.”

  3. Respondents were also asked to indicate what percent of the offenders were Latino.

  4. The data indicate that, on average, respondents perceive that Black juveniles commit about 25 % more violent crimes than White juveniles, such that Blacks commit an average of about 48 % of murders, robberies, and aggravated assaults, while Whites commit an average of about 23 % of these crimes. In 2011, the UCR reported that 54 % of the murders, 68.5 % of the robberies, and 42.3 % of the aggravated assaults were committed by Black juveniles, while 45.1 % of the murders, 30.4 % of the robberies, and 55.7 % of the aggravated assaults were committed by White juveniles. This means that, on average, Blacks committed about 55.1 % of these violent crimes and Whites committed 43.7 % of them, making for an average difference of 11.4 %. Therefore, in actuality, there is a much smaller gap between Black and White violent juvenile crime than the perceptual measures indicate (11.4 vs. 25 %).

  5. To maximize comparability with prior work, we opted to use a Dispositional Attribution Style scale similar to those used by Grasmick and McGill (1994) and Cochran et al. (2003). The alpha reported for the Dispositional Attribution Style index is comparable to the alpha level for the dispositional attribution indices in these studies. While a higher alpha level would be ideal, it is important to note that “poorer reliability typically makes statistical tests more conservative, hence the strength of the focal concerns would be attenuated” (Iacobucci and Duhachek 2003, p. 479). Therefore, any of the findings reported below involving the Dispositional Attribution Style measure may be underestimates of the relationships of interest. Also, alphas are heavily influenced by the number of items in the index (Cortina 1993), so the lower alpha value may just be a result of having only three indicators.

  6. While the dependent variable is designed to measure respondents’ support for policies that treat juvenile offenders like adults (Pickett and Baker 2014), this variable measures respondents’ perceptions of the characteristics (i.e., adult-like vs. child-like) of violent juvenile offenders. It is proposed that these perceptions will increase support for the use of adult sanctions against violent juvenile offenders. A promax-rotated exploratory factor analysis of the three indicators in the dependent variable and the two indicators in the Adult Criminal Intent mediator confirmed that there are two separate factors, a policy support measure and a perceptual measure.

  7. Although this measure is not as reliable as the former measure (i.e., Adult Criminal Intent), we chose to retain the measure in the analyses based on the results of the factor analysis. However, we re-analyzed the models without the Childhood Naivety mediator and obtained substantively similar results. As noted in footnote 5, it may be that the findings reported below involving Childhood Naivety are underestimated due to the lower reliability of the measure (Iacobucci and Duhachek 2003). The lower alpha value could also be a result of having only two indicators in the index (Cortina 1993).

  8. As seen in “Appendix 2”, we also considered the mediating influences of Childhood Naivety, but the results are not discussed in detail since the effect of Racial Typification on Childhood Naivety is not significant, similar to the model reported in the text.

  9. Significant differences between the coefficients of interest were determined based on a two-tailed test for statistical significance. When relying on a one-tailed test for statistical significance, one of the differences between the coefficients of interest for the two groups emerged as significant: the direct association between Racial Typification and Punitive Attitudes (p = .040).

  10. The path analyses for the two age groups still include the age of the respondents as a control variable, since there is variation in age within the two groups. The models were also reanalyzed without controlling for age. The results were substantively similar to those reported in “Appendix 3”. There were no significant differences between the coefficients of interest using a two-tailed test for statistical significance. However, three differences between the coefficients of interest for the two groups emerged as significant using a one-tailed test: (1) the direct association between Racial Typification and Adult Criminal Intent (p = .046), (2) the direct association between Racial Typification and Punitive Attitudes (p = .028), and (3) the total association between Racial Typification and Punitive Attitudes (p = .048).

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Author information

Authors and Affiliations

  1. Department of Criminology and Criminal Justice, Currell College, University of South Carolina, 1305 Greene Street, Columbia, SC, 29208, USA

    Christi Metcalfe

  2. School of Criminal Justice, University at Albany State University of New York, 1400 Washington Avenue, Albany, NY, 12222, USA

    Justin T. Pickett

  3. L. Douglas Wilder School of Government and Public Affairs, Virginia Commonwealth University, 923 West Franklin Street, PO Box 842028, Richmond, VA, 23284, USA

    Christina Mancini

Authors
  1. Christi Metcalfe
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  2. Justin T. Pickett
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  3. Christina Mancini
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Correspondence to Christi Metcalfe.

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Supplementary material 1 (DOC 165 kb)

Appendices

Appendix 1: Path Analysis Examining Punitive Attitudes Without Rehabilitable

See Tables 6 and 7.

Table 6 Results of the path analysis examining punitive attitudes: direct associations
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Table 7 Results of the path analysis examining punitive attitudes: indirect and total associations
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Appendix 2: Alternate Specifications of the Path Analysis Examining Punitive Attitudes

See Fig. 2 and Tables 8 and 9.

Fig. 2
figure 2

Full path analysis examining punitive attitudes. Notes: The model accounted for all control variables; paths are only shown for the variables and relationships of interest. Standardized path coefficients are presented. *p ≤ .05; **p ≤ .01; ***p ≤ .001

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Table 8 Results of the path analysis examining punitive attitudes: direct associations
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Table 9 Results of the path analysis examining punitive attitudes: indirect and total associations
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Appendix 3: Path Analyses Examining Punitive Attitudes by Age

See Tables 10, 11 and 12.

Table 10 Results of the path analysis examining punitive attitudes for respondents 21 and over: direct associations
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Table 11 Results of the path analysis examining punitive attitudes for respondents 18–20: direct associations
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Table 12 Results of the path analysis examining punitive attitudes: indirect and total associations
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Metcalfe, C., Pickett, J.T. & Mancini, C. Using Path Analysis to Explain Racialized Support for Punitive Delinquency Policies. J Quant Criminol 31, 699–725 (2015). https://doi.org/10.1007/s10940-015-9249-6

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