, Volume 45, Issue 3, pp 1299–1311 | Cite as

Uncertainty in Hiring Does Not Justify Affirmative Action

  • Thomas MulliganEmail author


Luc Bovens has recently advanced a novel argument for affirmative action, grounded in the plausible idea that it is hard for an employer to evaluate the qualifications of candidates from underrepresented groups. Bovens claims that this provides a profit-maximizing employer with reason to shortlist prima facie less-qualified candidates from underrepresented groups. In this paper, I illuminate three flaws in Bovens’s argument. First, it suffers from model error: A rational employer does not incur costs to scrutinize candidates when it knows their qualifications with perfect certainty, nor does it refuse to hire better-qualified candidates just because they did not require extra scrutiny. Second, Bovens’s core premise--that there is greater variance in the evaluation of underrepresented candidates than there is the evaluation of other candidates--hurts underrepresented candidates rather than helps them. Third, candidates who are not shortlisted for the reasons Bovens gives have a plausible complaint about unfairness in the hiring process.


Affirmative action Statistical discrimination Hiring Distributive justice Meritocracy 



I thank two anonymous referees for their many helpful suggestions on this article.


  1. Aigner, D. J., & Cain, G. C. (1977). Statistical theories of discrimination in labor markets. Industrial and Labor Relations Review, 30, 175–187.CrossRefGoogle Scholar
  2. Allen-Hermanson, S. (2017). Leaky pipeline myths: in search of gender effects on the job market and early career publishing in philosophy. Frontiers in Psychology, 8, 1–10.CrossRefGoogle Scholar
  3. Arkes, H., & Tetlock, P. E. (2004). Attributions of implicit prejudice, or “Would Jesse Jackson ‘fail’ the Implicit Association Test?”. Psychological Inquiry, 15, 257–278.CrossRefGoogle Scholar
  4. Arrow, K. J. (1973). The theory of discrimination. In O. Ashenfelter & A. Rees (Eds.), Discrimination in Labor Markets (pp. 3–33). Princeton: Princeton University Press.Google Scholar
  5. Baldi, S. (1995). Prestige determinants of first academic job for new sociology Ph.D.s 1985–1992. Sociological Quarterly, 36, 777–789.CrossRefGoogle Scholar
  6. Becker, G. (1957). The Economics of Discrimination. Chicago: University of Chicago Press.Google Scholar
  7. Blanton, H., Jaccard, J., Klick, J., Mellers, B., Mitchell, G., & Tetlock, P. E. (2009). Strong claims and weak evidence: reassessing the predictive validity of the IAT. Journal of Applied Psychology, 94, 567–582.CrossRefGoogle Scholar
  8. Bovens, L. (2016). Selection under uncertainty: affirmative action at shortlisting stage. Mind, 125, 421–437.CrossRefGoogle Scholar
  9. Burris, V. (2004). The academic caste system: prestige hierarchies in PhD exchange networks. American Sociological Review, 69, 239–264.CrossRefGoogle Scholar
  10. Ceci, S. J., & Williams, W. M. (2015). Women have substantial advantage in STEM faculty hiring, except when competing against more-accomplished men. Frontiers in Psychology, 6, 1–10.CrossRefGoogle Scholar
  11. Clauset, A., Arbesman, S., & Larremore, D. B. (2015). Systematic inequality and hierarchy in faculty hiring networks. Science Advances, 1.Google Scholar
  12. Connolly, M. R., Lee, Y.-G., and Savoy, J. N. 2015. Faculty hiring and tenure by sex and race: new evidence from a national survey. Paper presented at the Annual Meeting of the American Educational Research Association, 16-20 April 2015.Google Scholar
  13. Dicey Jennings, C., Kyrilov, A., Cobb, P., Vlasits, J., Vinson, D. W., Montes, E., & Franco, C. (2015). Academic placement data and analysis: 2015 final report. At
  14. Ewens, M., Tomlin, B., & Choon Wang, L. (2014). Statistical discrimination or prejudice? A large sample field experiment. Review of Economics and Statistics, 96, 119–134.CrossRefGoogle Scholar
  15. Finnigan, K. M., & Corker, K. S. (2016). Do performance avoidance goals moderate the effect of different types of stereotype threat on women’s math performance? Journal of Research in Personality, 63, 36–43.CrossRefGoogle Scholar
  16. Flore, P. C., & Wicherts, J. M. (2015). Does stereotype threat influence performance of girls in stereotyped domain? A meta-analysis. Journal of School Psychology, 53, 25–44.CrossRefGoogle Scholar
  17. Forscher, P. S., Lai, C. K., Axt, J. R., Ebersole, C. R., Herman, M., Devine, P. G., Nosek, B. A. (2017). A meta-analysis of change in implicit bias. Accessed 22 July 2017.
  18. Ganley, C. M., Mingle, L. A., Ryan, A. M., Ryan, K., Vasilyeva, M., & Perry, M. (2013). An examination of stereotype effects on girls’ mathematics performance. Developmental Psychology, 49, 1886–1897.CrossRefGoogle Scholar
  19. Hedges, L. V., & Nowell, A. (1995). Sex differences in mental test scores, variability, and numbers of high-scoring individuals. Science, 269, 41–45.CrossRefGoogle Scholar
  20. Hyde, J. S., Lindberg, S. M., Linn, M. C., Ellis, A. B., & Williams, C. C. (2008). Gender similarities characterize math performance. Science, 321, 494–495.CrossRefGoogle Scholar
  21. Jacobs, D. (1999). Ascription or productivity? The determinants of departmental success in the NRC quality rankings. Social Science Research, 28, 228–239.CrossRefGoogle Scholar
  22. Jacobs, D. (2004). Ascription and departmental rankings revisited: A correction and a reanalysis. Social Science Research, 33, 183–186.CrossRefGoogle Scholar
  23. Keith, B., & Babchuk, N. (1998). The quest for institutional recognition: A longitudinal analysis of scholarly productivity and academic prestige among sociology departments. Social Forces, 76, 1495–1533.CrossRefGoogle Scholar
  24. List, J. A. (2004). The nature and extent of discrimination in the marketplace: evidence from the field. Quarterly Journal of Economics, 119, 49–89.CrossRefGoogle Scholar
  25. Marinoff, L. 2009. Inside a search. Inside Higher Ed, <>, retrieved 3 July 2017.
  26. McGinnis, R., & Long, J. S. (1997). Entry into academia: Effects of stratification, geography and ecology. In M. J. Finkelstein & P. G. Altbach (Eds.), The Academic Profession: The Professorate in Crisis (pp. 342–366). New York: Routledge.Google Scholar
  27. Mulligan, T. (2017). Justice and the Meritocratic State. New York: Routledge.Google Scholar
  28. Narveson, J. (1993). Moral Matters. Peterborough, Canada: Broadview Press.Google Scholar
  29. Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J., & Tetlock, P. E. (2013). Predicting ethnic and racial discrimination: a meta-analysis of IAT criterion studies. Journal of Personality and Social Psychology, 105, 171–192.CrossRefGoogle Scholar
  30. Oprisko, R. L., Dobbs, K. L., and DiGrazia, J. 2013. Honor, prestige, and the academy: A portrait of political science tenured and tenure-track faculty in Ph.D.-granting institutions (2012-2013). Paper presented at the 2013 annual meeting of the American Political Science Association.Google Scholar
  31. Phelps, E. S. (1972). The statistical theory of racism and sexism. American Economic Review, 62, 659–661.Google Scholar
  32. Sackett, P. R., Hardison, C. M., & Cullen, M. J. (2004). On interpreting stereotype threat as accounting for African American-White differences on cognitive tests. American Psychologist, 59, 7–13.CrossRefGoogle Scholar
  33. Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69, 797–811.CrossRefGoogle Scholar
  34. Steinpreis, R. E., Anders, K. A., & Ritzke, D. (1999). The impact of gender on the review of the curricula vitae of job applicants and tenure candidates: a national empirical study. Sex Roles, 41, 509–528.CrossRefGoogle Scholar
  35. Williams, W. M., & Ceci, S. J. (2015). National hiring experiments reveal 2:1 faculty preference for women on STEM tenure track. Proceedings of the National Academy of Sciences, 112, 5360–5365.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.McDonough School of BusinessGeorgetown UniversityWashingtonUSA

Personalised recommendations