The scientific research materials shown below formed the basis for what is discussed in the exhibition.
Outsmarting Human Minds
A Project at Harvard University (OHM) is a media series that explores the quirks and blindspots of the mind using insights from psychological science
Gender in Science, Technology, Engineering, and Mathematics: Issues, Causes, Solutions
Tessa E.S. Charlesworth and Mahzarin R. Banaji | Journal of Neuroscience 11 September 2019
Ambient Belonging: How Stereotypical Cues Impact Gender Participation in Computer Science
Sapna Cheryan, University of Washington; Victoria C. Plaut, University of Georgia; Paul G. Davies, University of British Columbia, Okanagan; Claude M. Steele, Stanford University | Journal of Personality and Social Psychology © 2009 American Psychological Association 2009, Vol. 97, No. 6, 1045–1060
National differences in gender-science stereotypes predict national sex differences in science and math achievement
Nosek et al., 2009, PNAS
Racial disparities in school-based disciplinary actions are associated with county-level rates of racial bias
Travis Riddle and Stacey Sinclair | PNAS April 23, 2019 116 (17) 8255-8260; first published April 2, 2019
The School-to-Prison Pipeline: Policies and practices that favor incarceration over education do us all a grave injustice
Marilyn Elias | Teaching Tolerance Magazine ISSUE 43, SPRING 2013
Understanding Implicit Bias: What Educators Should Know
Cheryl Staats | American Educator, Vol. 39, No. 4, Winter 20
Accessible overview of social categories
Liberman, Z., Woodward, A. L., & Kinzler, K. D. | (2017) The Origins of Social Categorization. Trends in Cognitive Sciences, 21(7), 556–568
Kinzler, K. D., Shutts, K., DeJesus, J., & Spelke, E. S. | (2009) Accent Trumps Race in Guiding Children’s Social Preferences. Social Cognition, 27(4), 623–634
The native language of social cognition. Proceedings of the National Academy of Sciences of the United States of America
Kinzler, K. D., Dupoux, E., & Spelke, E. S. | (2007) 104(30), 12577–12580
Out-group "hate" arrives around age 6
Buttelmann, D., & Böhm, R. | (2014) The Ontogeny of the Motivation That Underlies In-Group Bias. Psychological Science, 25(4), 921–927
Additional research about bias that are not represented in the exhibition
Courtesy of Harvard University Department of Psychology
Negative perceptions of aging are widespread: Levy, B. R., & Banaji, M. R. (2002). Implicit Ageism. In T. D. Nelson (Ed.), Ageism: Stereotyping and Prejudice against Older Persons. Cambridge, MA: The MIT Press. Retrieved from
Negative perceptions of aging have profound personal consequences. People who have positive perceptions of aging live 7.5 years longer than those with negative perceptions of aging, revealing how powerful the internalized stigmas can be! Levy, B. R., Slade, M. D., Kunkel, S. R., & Kasl, S. V. (2002). Longevity Increased by Positive Self- Perceptions of Aging. Journal of Personality and Social Psychology, 83(2), 261–270.
Persons with physical disabilities
Negative implicit bias against physical disability: Dovidio, J. F., Pagotto, L., & Hebl, M. R. (2011). Implicit attitudes and discrimination against people with physical disabilities. In Disability and Aging Discrimination: Perspectives in Law and Psychology (pp. 157–183).
Stereotypes typically focus on incompetence: Rohmer, O., & Louvet, E. (2016). Implicit stereotyping against people with disability. Group Processes & Intergroup Relations, 21(1), 127–140.
Typically, people in poverty are seen with "mixed" stereotypes of being "warm" but also incompetent/weak: Fiske, S. T. (2018). Stereotype Content: Warmth and Competence Endure. Current Directions in Psychological Science, 1–7.
Children from 3 years of age associate White with wealth (and Black people with poverty), indicating an early understanding of the racial stereotypes of wealth: Olson, K. R., Shutts, K., Kinzler, K. D., & Weisman, K. G. (2012). Children Associate Racial Groups With Wealth: Evidence From South Africa. Child Development, 83(6), 1884–1899.
Black children at 7-11 years of age who show a preference for wealth also show an implicit preference for White (i.e., for their outgroup): Newheiser, A. K., & Olson, K. R. (2012). White and Black American children’s implicit intergroup bias. Journal of Experimental Social Psychology, 48(1), 264–270.
There is also a strong implicit rich-good/poor-bad attitude throughout the US (in fact, it's stronger than biases about ability, body weight, age, race, etc.): Nosek, B. A. (2005). Moderators of the relationship between implicit and explicit evaluation. Journal of Experimental Psychology: General, 134(4), 565–584.