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Implicit Bias and Diversity in Higher Education. Stephen Benard Indiana University sbenard@indiana.edu. Overview. Aggregate data Evidence of cognitive biases How cognitive biases work Stereotype content How to reduce cognitive biases. Distribution of Faculty by Race/Ethnicity.

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Implicit Bias and Diversity in Higher Education


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    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 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 • 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

    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 Source: Berger, Cohen, & Zelditch 1972; Pugh and Wahrman 1983; Ridgeway 1982; Smith-Lovin & Brody 1989 • 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

    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 Source: Heilman et al 2004; Ridgeway 1982; Rudman 1998; Rudman & Glick 1999; Sinclair and Kunda 2000 • 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

    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