Implicit Bias in Science: The Power of Automatic, Unintended Mindsets
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1 Implicit Bias in Science: The Power of Automatic, Unintended Mindsets Frederick Smyth Department of Psychology University of Virginia OXIDE National Diversity Equity Workshop January 25, 2011
2 full potential initiative Brian Nosek & Fred Smyth Funded by the National Science Foundation REC fullpotentialinitiative.org
3 Take Home about Implicit Associations 1) Humility: Implicit associations pervasive 2) Changeable 3) Measurable 4) Related to STEM outcomes 5) Mindfulness matters
4 Who will win? A B
5 Competitor A wins IF he s wearing red Hagemann, Strauss & Leiing, 2008 Mean Points A B A B
6 Implicit Bias Taekwondo referees unaware 1977 early demonstrations: Nisbett& Wilson 2009 pervasive influence: Barghet al. Livelihoods and lives Payne, 2006 Goldin & Rouse, 2000
7 Implicit Stereotypes Debbie Danny Afraid Angry Condry & Condry, 1976
8 Proportion recommending higher math Teachers math placement decisions Recommendation for a precocious 6th grader 0.24 Sex*condition interaction (p=.01) 0.19 Female Participant teachers n=636 Boy Student Girl Student Participant Sex 0.13 Participant Sex 0.26 Male Male teachers Participant n=230 Smyth, Hawkins & Nosek, 2009
9 Measuring Implicit Associations
10 Implicit Association Test (IAT) Greenwald, McGhee & Schwarz, 1998 Green Bay or Pittsburgh?
11 Steelers Packers Left Right
12 Steelers Packers Left Right
13 Good Bad Left Right
14 Good Bad Left Right
15 Steelers Good Packers Bad Left Right
16 Steelers Good Packers Bad Left Right
17 Steelers Packers Good Packers Steelers Bad Left Right
18 Which sorting is easier? Steelers Steelers fans Packers Good Bad Packers Packers fans Steelers Good Bad
19 implicit.harvard.edu/implicit/
20 Group Demonstration of Implicit Gender-Science Bias 2 Counter-balanced Conditions IAT Then
21 Gender-Science on Project Implicit Number of Participants Number of Respondents % 70% 0 Counter-Stereotype Science=male Stereotype Implicit Science=Male / Arts=Female Stereotyping
22 Same for Men and Women? Male Respondents Female Respondents % 71% Number of Respondents % Number of Respondents % Im plicit Science=Male / Arts=Female Stereotyping Im plicit Science=Male / Arts=Fem ale Stereotyping
23 Not the same if academic identity is taken into account.
24 Implicit Science=Male IAT d Score IAT d Women (N=72,938) Men (N=31,358) Female-Male Cohen s d Visual/Perform Arts Humanities Law-Legal Studies Communication Education Social Sci-History Business Psychology Health Sci Biology-Life Sci Computer-Info Sci Major Field of Highest Degree Engin-Math-Phy Sci Smyth, Greenwald & Nosek, 2010
25 Environment Matters
26 International Variation Nosek, Smyth, et al., 2009, PNAS
27 Male Advantage TIMSS Science 8th-grade TIMSS Gender Gap 30 and Citizens Implicit Bias, r =.60* Nosek, Smyth, et al., 2009, PNAS Science = Male IAT
28 Effect of Professor s Gender on Calculus Students Implicit Math Self-Concept Implicit Math Identity Female Students Male Students Female Professors Male Professors Stout, Dasgupta et al., 2010
29 Stereotype Inoculation Model Even when a distinct minority, inoculation by contact with successful female role models bolsters STEM selfconcept, attitude, self-efficacy and goals. Stout, Dasgupta et al., 2010
30 Costs of Implicit Bias? Logel et al., 2009 Jenny went home to cook dinner 1-Egalitarian to 5-Sexist for her husband. naked. because Tim cooked dinner last night. after work. Female engineering students scored significantly worse on an engineering test after interacting with men who scored highly on this implicit sexism test.
31 What to do? More research! Re-doing more than undoing Articulate explicit values Education and self monitoring Promote malleability mindset about ability
32 Restructure decision-making process Goldin & Rouse, 2000
33 Protect against known biases Hagemann, Strauss & Leiing, 2008
34 Thank you. full potential initiative Funded by the National Science Foundation REC fullpotentialinitiative.org
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