1. Implicit Bias and Diversity in Higher Education Stephen Benard Indiana University sbenard@indiana.edu

2. Overview  Aggregate data  Evidence of cognitive biases  How cognitive biases work  Stereotype content  How to reduce cognitive biases

3. Distribution of Faculty by Race/Ethnicity Source: US Department of Education, 2007

4. Percent Female by Rank Source: US Department of Education, 2007

5. Salaries Source: US Department of Education, 1998

6. Contributing Factors  Supply side/pipeline  Factors resulting in a smaller pool of applicants  Demand side/bias  Factors resulting in a lower preference for women or minority candidates

7. Contributing Factors  Supply side/pipeline  Factors resulting in a smaller pool of applicants  Demand side/bias  Factors resulting in a lower preference for women or minority candidates

8. Perceptions  Among scientists and engineers, men rated more positively by managers  Among fellowship winners, 72.8% of women and 12.9% of male scientists report discrimination Sources: DiTomaso et al 2007; Heilman et al 1989; Sonnert and Holton 1996

9. A Curriculum Vita Experiment  Identical CVs sent to random, national sample of faculty  Manipulate applicant sex (first name)  Applicant experience (assistant/associate CV) Source: Steinpreis, Anders, and Ritzke 1999

10. A Curriculum Vita Experiment  In addition to hiring, male CV advantaged on  Salary  Tenure recommendations  Research, teaching, and service evaluations  No differences in ratings of more experienced CVs  Four times as many “cautionary statements” on experienced female CV Source: Steinpreis, Anders, and Ritzke 1999

11. Race in Hiring  Researchers sent ~5,000 resumes to a wide range of jobs in Chicago and Boston  Systematically varied common white/African American names Source: Bertrand and Mullainathan 2003

12. Stereotypes  Cognitive association between a group and a trait or a set of traits  E.g. women and dependence, men and competence, African American males and aggression

13. Stereotypes Can Be Implicit  We may not be aware we hold particular associations  Can develop early in life  Exposure to a stimulus activates related concepts (also implicitly)  More accessible in memory  More likely to be applied in information processing, behavior Sources: Bargh, Chen and Burrows 1996; Bargh and Ferguson 2001; Devine 1989; Greenwald and Banaji 1995; Kunda et al. 2002; Srull and Weyer 1979; Wilson and Brekke 1994

14. Implicit Associations  Can exist and affect behavior outside of awareness, even when we disapprove of a stereotype  Implicit associations are measurable  Predict a wide range of behavior Source: Greenwald and Krieger 2001; Jost et al 2009

15. Stereotypes about Competence  Women and minorities stereotyped as less competent than men and whites  In task groups, viewed as less likely to make valuable contributions  Fewer opportunities to speak  Less influence  Performances evaluated less positively Source: Berger, Cohen, & Zelditch 1972; Pugh and Wahrman 1983; Ridgeway 1982; Smith-Lovin & Brody 1989

16. Double Standards for Competence  Lower expectations for competence produces greater skepticism of good performances  Need to perform at higher levels to be seen as equally talented Source: Foschi 1996, 2000; Foschi, Lai & Sigerson 1994

17. Double Standards for Competence  Varying overall qualifications  Male applications preferred (by men) when men more qualified  But no difference in M/F preference when women more qualified  Education vs. Experience  Male applicants shown preference  Raters cited whichever qualification favored males as most important Source: Foschi, Lai & Sigerson 1994; Norton, Vandello, & Darley 2004

18. Prescriptive Biases  Penalties for women who behave in stereotypically male manner  Assertive women disliked, seen as pushy, selfish, less hireable  Similarly-behaving men not penalized  Grades given predict teaching evaluations for women, not men Source: Heilman et al 2004; Ridgeway 1982; Rudman 1998; Rudman & Glick 1999; Sinclair and Kunda 2000

19. Reducing the Influence of Implicit Bias: General Principles  Implicit bias can be difficult to address because stereotypes can be activated and applied unconsciously  But it is possible, with conscious effort  This requires both motivation and cognitive resources

20. Reducing the Influence of Implicit Bias  Support from Leaders  Training  Accountability  Transparency  Creating Effective Searches

21. Training  Educate decision makers about research, mechanisms of unconscious bias  vs. other forms of “diversity training”  Requires motivation to reduce bias Source: Devine et al 2002; McCracken 2000; Rudman et al. 2001; Wilson and Brekke 1994

22. Accountability  Definition: the implicit or explicit expectation that one may be called on to justify one's beliefs, feelings, and actions to others Lerner and Tetlock 1999; Tetlock 1983a, 1983b, 1985; and Tetlock and Kim 1987

23. Why Accountability Works  Requires us to think through our decisions  Use more effort to process information  Less likely to make snap decisions  Increases motivation and effort to avoid stereotyping Lerner and Tetlock 1999; Tetlock 1983a, 1983b, 1985; and Tetlock and Kim 1987

24. When Does Accountability Work Best?  Accountable to higher, impartial authority  Before the final decision has been made  When authority is seen as legitimate

25. Transparency  Agree on standards of evaluation before evaluating candidates  Education vs. experience  Performance vs. potential

26. Creating Effective Searches  Defining the search  Creating the search committee  Allow sufficient time  Structuring group discussions  Critically analyze supporting materials

27. Thank you! Stephen Benard Indiana University sbenard@indiana.edu