Skip to main content
Log in

Disentangling the Effects of Racial Self-identification and Classification by Others: The Case of Arrest

  • Published:
Demography

Abstract

Scholars of race have stressed the importance of thinking about race as a multidimensional construct, yet research on racial inequality does not routinely take this multidimensionality into account. We draw on data from the U.S. National Longitudinal Study of Adolescent Health to disentangle the effects of self-identifying as black and being classified by others as black on subsequently being arrested. Results reveal that the odds of arrest are nearly three times higher for people who were classified by others as black, even if they did not identify themselves as black. By contrast, we find no effect of self-identifying as black among people who were not seen by others as black. These results suggest that racial perceptions play an important role in racial disparities in arrest rates and provide a useful analytical approach for disentangling the effects of race on other outcomes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Notes

  1. Given the relatively small numbers of respondents who were racially classified and identified differently, we report additional analyses in Online Resource 1 using a variety of alternative estimation strategies for our standard errors (all of which yield substantively similar results).

  2. We obtained similar results from a model comparing respondents who were neither classified nor identified as black with those who (1) were both classified and identified as black, (2) were classified as black but did not identify as black, and (3) were not classified as black but identified as black.

  3. We add these controls to account for concerns about survey design effects and the consistency of self-identification across waves (see Cheng and Powell 2011).

  4. Models with and without controls yield similar results. We prefer the model without controls out of concern for data sparseness. We do not constrain our sample sizes to be equal across models because of the number of respondents who have missing data on control variables.

  5. Our models do not account for other situational factors that also predict arrest because Add Health does not record detailed information about the circumstances surrounding the arrest (e.g., the evidence on which the arrest was based, the arrestee’s demeanor, and whether the arrestee complied with police commands). Future work examining the relationship between these characteristics and racial perceptions would be of great value for understanding the relationship between race and arrest (cf. Goff and Richardson 2012; Kochel et al. 2011).

References

  • Bailey, S. R., Saperstein, A., & Penner, A. M. (2014). Race, color, and income inequality across the Americas. Demographic Research, 31(article 24), 735–756. doi:10.4054/DemRes.2014.31.24

    Article  Google Scholar 

  • Bonilla-Silva, E. (2010). Racism without racists: Color-blind racism and the persistence of racial inequality in the United States. Lanham, MD: Rowman & Littlefield.

    Google Scholar 

  • Brubaker, R., Loveman, M., & Stamatov, P. (2004). Ethnicity as cognition. Theory and Society, 33, 31–64.

    Article  Google Scholar 

  • Cheng, S., & Powell, B. (2011). Misclassification by whom? A comment on Campbell and Troyer (2007). American Sociological Review, 76, 347–355.

    Article  Google Scholar 

  • Fordham, S. (2008). Beyond Capital High: On dual citizenship and the strange career of “acting white.” Anthropology & Education Quarterly, 39, 227–246.

  • Goff, P. A., & Richardson, L. S. (2012). No bigots required: What the science of racial bias reveals in the wake of Trayvon Martin. In G. Yancy & J. Jones (Eds.), Pursuing Trayvon Martin: Historical contexts and contemporary manifestations of racial dynamics (pp. 59–72). New York, NY: Rowman & Littlefield.

  • Goldstein, J. R., & Morning, A. J. (2000). The multiple-race population of the United States: Issues and estimates. Proceedings of the National Academy of Sciences, 97, 6230–6235.

    Article  Google Scholar 

  • Greenwald, A. G., McGhee, D. E., & Schwartz, L. K. (1998). Measuring individual differences in implicit cognition: The Implicit Association Test. Journal of Personality and Social Psychology, 74, 1464–1480.

    Article  Google Scholar 

  • Harris, K. M. (2009). The National Longitudinal Study of Adolescent Health (Add Health), Waves I & II, 1994–1996; Wave III, 2001–2002; Wave IV, 2007–2009 [machine-readable data file and documentation]. Chapel Hill, NC: Carolina Population Center, University of North Carolina at Chapel Hill.

  • Kirk, D. S. (2008). The neighborhood context of racial and ethnic disparities in arrest. Demography, 45, 55–77.

    Article  Google Scholar 

  • Kochel, T. R., Wilson, D. B., & Mastrofski, S. D. (2011). Effect of suspect race on officers’ arrest decisions. Criminology, 49, 473–512.

    Article  Google Scholar 

  • Pager, D. (2003). The mark of a criminal record. American Journal of Sociology, 108, 937–975.

    Article  Google Scholar 

  • Roth, W. (2010). Racial mismatch: The divergence between form and function in data for monitoring racial discrimination of Hispanics. Social Science Quarterly, 91, 1288–1311.

    Article  Google Scholar 

  • Saperstein, A. (2012). Capturing complexity in the United States: Which aspects of race matter and when? Ethnic and Racial Studies, 35, 1484–1502.

    Article  Google Scholar 

  • Saperstein, A., & Penner, A. M. (2010). The race of a criminal record: How incarceration colors racial perception. Social Problems, 57, 92–113.

    Article  Google Scholar 

  • Saperstein, A., Penner, A. M., & Kizer, J. (2014). The criminal justice system and the racialization of perceptions. Annals of the American Academy of Political and Social Science, 651, 104–121.

    Article  Google Scholar 

  • Snipp, C. M. (2003). Racial measurement in the American census: Past practices and implications for the future. Annual Review of Sociology, 29, 563–588.

    Article  Google Scholar 

  • Takaki, R. (1994). From different shores: Perspectives on race and ethnicity in America. New York, NY: Oxford University Press.

    Google Scholar 

  • Telles, E. E., & Lim, N. (1998). Does it matter who answers the race question? Racial classification and income inequality in Brazil. Demography, 35, 465–474.

    Article  Google Scholar 

Download references

Acknowledgments

The authors are grateful to the Russell Sage Foundation, the UC Center for New Racial Studies, and Stanford's Institute for Research in the Social Sciences for support, to Jessica Kizer for research assistance and to Sara Wakefield for useful comments and discussions. A previous version of this article was presented at the annual meeting of the Population Association of America, San Francisco, May 2012.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrew M. Penner.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(PDF 35 kb)

Appendix

Appendix

Table 2 Odds ratios predicting a reported arrest in Wave 4 among Wave 3 self-identified nonblacks
Table 3 Odds ratios predicting a reported arrest in Wave 4 among Wave 3 interviewer-classified nonblacks

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Penner, A.M., Saperstein, A. Disentangling the Effects of Racial Self-identification and Classification by Others: The Case of Arrest. Demography 52, 1017–1024 (2015). https://doi.org/10.1007/s13524-015-0394-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13524-015-0394-1

Keywords

Navigation