cies and procedures that minimize the influence of bias and assumptions on the recruitment and admission of students, as well as on the recruitment, hiring, promotion, and retention of faculty. Awareness of our own propensity to rely on biases and assumptions when interacting with and evaluating individuals is another key strategy for ensuring admitted students and newly hired faculty experience positive and welcoming climates, students complete their degrees and continue their education, and faculty advance professionally through tenure and promotion. Research on overcoming the influence of bias and assumptions demonstrates that in order to do so successfully, individuals must be motivated, must believe they have the capacity to do so, and must learn and practice specific techniques demonstrated to be effective [ 24]. These techniques include:

˲ Recognizing when you have, hear, or see a stereotyped or biased viewpoint (e.g., women aren’t good at math) and replacing it with a non-stereotypi-cal response (e.g., gender differences in math performance disappear when we control for math courses taken).

˲ Practicing counter-stereotype imaging (e.g., think about successful women computer scientists and their contributions to the field).

˲ Practicing individuation by focusing on an individual’s unique personal qualities, strengths, and weaknesses, rather than on characteristics of the group to which the individual belongs.

˲ Engaging in perspective-taking, such as imagining how it would feel to be the only woman in a workgroup or classroom, to have colleagues assume you were only admitted to a program or hired because of your race or gender rather than because of your ability, and to have to prove your worthiness constantly.

˲Seeking out opportunities to interact professionally with women students and colleagues and learning more about their strengths and contributions and the challenges they face [ 25].

Unfortunately, reading about such
strategies—especially in a short ar-
ticle—will not help you to overcome
bias and stereotypes; nor will reading
a longer article, viewing a webcast,
or watching a video. Research on ef-
fective strategies for minimizing the
influence of unintentional bias dem-
onstrates that actively engaging in ed-
ucational activities and discussions is
essential [ 26]. Universities are increas-
ingly offering workshops and educa-
tional activities centered around re-
search on unconscious or implicit bias
and how to minimize the role it plays.
Watch for or request such offerings on
your campus and participate in them.
Use these opportunities to learn and
practice the strategies needed to de-
velop and sustain a diverse and inclu-
sive scientific workforce that takes full
advantage of the human capacity for
knowledge and innovation.

REFERENCES

[ 1] National Institutes of Health, Office of Research on Women’s Health. National Leadership Workshop on Mentoring Women in Biomedical Careers. NIH, Bethesda, MD, 2008.

[ 2] Yoder, B. L. Engineering by the Numbers. American Society for Engineering Education. http://www.asee. org/papers-and-publications/publications/11-47. pdf.

[ 3] Misra, T. J., ed. Gender Codes: Why women are leaving computing. Wiley and IEEE Computer Society, Hoboken, NJ, 2010.

[ 4] Abbate, J. Recoding Gender: Women’s changing participation in computing. MI T Press, Cambridge, MA, 2012.

[ 5] Margolis, J. and Fisher, A. Unlocking the Clubhouse: Women in computing. MI T Press, Cambridge, MA,

2002.

[ 6] Nelson, D. J. and Brammer, C. N. A National Analysis of Minorities in Science and Engineering Faculties at Research Universities. Diversity in Science Association and University of Oklahoma, Norman, OK, October 31, 2007. http://faculty-staff.ou.edu/N/ Donna. J.Nelson-1/diversity/Faculty_Tables_FY07/ FinalReport07.html.

[ 7] Valian, V. Interests, Gender, and Science. Perspectives on Psychological Science 9, 2 (2014), 225-230.

[ 8] Hyde, J. S. and Linn, M. C. Gender Similarities in Mathematics and Science. Science 314, 5799

(2006), 599-600.

[ 9] Ceci, S. J. and Williams, W. M. Understanding Current Causes of Women’s Underrepresentation in Science.

PNAS 108, 8 (2011), 3157-3162.

[ 10] Weinberger, C. J. Is the Science and Engineering
Workforce Drawn from the Far Upper Tail of the
Math Ability Distribution? http://econ.ucsb.
edu/~weinberg/uppertail.pdf
[ 11] Hyde, J. S. and Mertz, J. E. Gender, Culture, and
Mathematics Performance. PNAS 106, 22 (2009),
8801-8807.

[ 12] Handelsman, J., et al. More Women in Science.

Science 309, 5738 (2005), 1190–1191.

[ 13] Heilman, M. E. Description and Prescription: How gender stereotypes prevent women’s ascent up the organizational ladder. Journal of Social Issues 57, 4 (2001), 657–674.

[ 14] Eagly, A. H. and Karau, S. J. Role Congruity Theory of Prejudice Toward Female Leaders. Psychological Review 109, 3 (2002), 573–598.

[ 15] Mead, M. and Métraux, R. Image of the Scientist Among High-School Students: A pilot study. Science

126, 3270 (1957), 384-390.

[ 16] Finson, K. D. Drawing a Scientist: What we do and do not know after fifty years of drawings. School Science and Mathematics 102, 7 (2002), 335-345.

[ 17] Nosek, B. A., et al. National Differences in Gender-Science Stereotypes Predict National Sex Differences in Science and Math Achievement. PNAS 106, 26 (2009), 10593–10597.

[ 18] Good, J. J., Woodzicka, J. A. and Wingfield, L. C. The Effects of Gender Stereotypic and Counter-Stereotypic Textbook Images on Science Performance. Journal of Social Psychology 150, 2 (2010), 132-147.

[ 19] Cheryan, S., Plaut, V. D., Davies, P. and C. M. Steele. Ambient Belonging: How stereotypical cues impact gender participation in computer science. Journal of Personality and Social Psychology 97, 6 (2009), 1045-1060.

[ 20] Moss-Racusin, C. A., Dovidio, J. F., Brescoll, V. L., Graham, M. J. and Handelsman, J. Science Faculty’s Subtle Gender Biases Favor Male Students. PNAS 109, 41 (2012), 16474–16479.

[ 21] Steinpreis, R. E., Anders, K. A. and Ritzke, D. The Impact of Gender on the Revie w of the Curricula Vitae of Job Applicants and Tenure Candidates: A national empirical study. Sex Roles 41, 7 (1999), 509–528.

[ 22] Allan, E. J. and Madden, M. Chilly Classrooms for Female Undergraduate Students: A question of method? Journal of Higher Education 77, 4 (2006), 684-711.

[ 23] Savoy, J. N. and Sheridan, J. Results from the 2012 Study of Faculty Worklife at U W-Madison: Tenured & Tenure-Track Faculty. Women in Science and Engineering Leadership Institute, University of Wisconsin-Madison, Madison, WI, 2013.

[ 24] Devine, P. G., Forscher, P. S., Austin, A. J. and Cox, W. T. L. Long-Term Reduction in Implicit Race Bias: A prejudice habit-breaking intervention. Journal of Experimental Social Psychology 48, 6 (2012), 1267–1278.

[ 25] Carnes, M., Devine, P. G., Isaac, C., Manwell, L. B., Ford, C., Byars- Winston, A., Fine, E. and Sheridan, J. Promoting Institutional Change Through Bias Literacy. Journal of Diversity in Higher Education 5, 2 (2012), 63-77.

[ 26] Moss-Racusin, C. A., van der Toorn, J., Dovidio, J. F., Brescoll, V. L., Graham, M. J. and Handelsman, J. Scientific Diversity Interventions. Science 343, 6171 (2014), 615–616.

 

Biographies

Eve Fine, Ph.D., is a researcher at WISELI: the Women in Science and Engineering Leadership Institute at the University of Wisconsin-Madison. Dr. Fine relies on her Ph.D. in the history of science and medicine to understand and address contemporary issues facing women faculty in S TEM fields.

Amy Wendt, Ph. D., is a professor of electrical and computer engineering, and is co-director of WISELI, University of Wisconsin-Madison. Prof. Wendt received graduate degrees in electrical engineering and computer science from UC Berkeley, and no w runs an experimental research program investigating “low-temperature” plasmas for materials processing applications including the fabrication of integrated circuits. She also works to enhance the representation of women in academic departments through WISELI initiatives, and by developing a hands-on engineering curriculum for middle school math and science classes that sho wcases engineering as a means to meet societal needs.

Molly Carnes, M. D., M. S., is a professor of medicine, psychiatry, and industrial and systems engineering, and is director of the Center for Women’s Health Research and co-director of WISELI, University of Wisconsin-Madison. Dr. Carnes studies how gender and race stereotypes negatively impact career development in academic medicine, science, and engineering with the goal of developing and implementing effective interventions.

Copyright held by Owner(s)/Author(s). Publication rights licensed to ACM $15.00.