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Building a more inclusive environment

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References

Reading List For Becoming a BiasBusters Trainer:

This list is inspired from the reading list suggested by Google’s Unbiasing at Work reading list.

  1. (2007) The Bottom Line: Corporate Performance and Women’s Representation on Boards. Catalyst.org.
  2. Phillips, K. W., Kim-Jun, S. Y., Shim, S. (2010). The Value of Diversity in Organizations: A Social Psychological Perspective. Social Psychology and Organizations. 253–272.
  3. Martell, R.F., Lane, D.M., Emrich, C. (1996). Male-female differences: a computer simulation. American Psychologist. 157–158.
  4. Bertrand, M., Mullainathan, S. (2004). Are Emily and Greg More Employable than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination. The American Economic Review. (94) 4, 991–1013.
  5. Moss-Racusin, C.A., Dovidio, J.F., Brescoll, V.L., Graham, M.J. Handelsman, J. (2012). Science faculty’s subtle gender biases favor male students. Proceedings of the National Academy of Sciences. (109) 41, 16,474–16479.
  6. Brooks, A. W., Huang, L., Kearney, S. W., & Murray, F. E. (2014). Investors prefer entrepreneurial ventures pitched by attractive men.
  7. Heilman, M.E, Block, C.J., Martell, R.F., Simon, M.C. (1989). Has Anything Changed? Current Characterizations of Men, Women, and Managers. Journal of Applied Psychology. (74) 6, 935–942.
  8. Heilman, M.E., Haynes M.C. (2005). No credit where credit is due: Attributional rationalization of women’s success in male-female teams. Journal of Applied Psychology. (90) 5, 905–916.
  9. Hebl, M.R., Bigazzi Foster, J., Mannix, L.M., Dovidio, J.F. (2002). Formal and Interpersonal Discrimination: A Field Study of Bias Toward Homosexual Applicants. Personality & Social Psychology Bulletin. 28; 815.
  10. Cheryan, S., Davies, P.G., Plaut, V.C., Steele, C.M. (2009) Ambient Belonging: How Stereotypical Cues Impact Gender Participation in Computer Science. Journal of Personality and Social Psychology. (97) 6, 1045–1060.
  11. Banaji, M. R. & Greenwald, A. G. (2013). Blindspot: Hidden Biases of Good People. New York, NY: Random House, Inc.
  12. Uhlmann, E. L., & Cohen, G. L. (2005). Constructed criteria: Redefining merit to justify discrimination. Psychological Science, 16(6), pp. 474–480.
  13. Martin, Ann M., Gender Distribution in Google Doodles: 2013 Year in Review, Speaking Up, Feb 4, 2014.
  14. Banaji, M. R., Caruso, E. M. & Rahnev, D. A. (2009). Using Conjoint Analysis to Detect Discrimination: Revealing Covert Preferences from Overt Choices.
  15. Bongiorno, R., Haslam, A. S., Hersby, M. D., & Ryan, M. K. (2011). Think Crisis–Think Female: The Glass Cliff and Contextual Variation in the Think Manager–Think Male Stereotype.
  16. Jones, K. P., Peddie, C. I., Gilrane, V. L., King, E. B., & Gray, A. L. (2013). Not So Subtle: A Meta-Analytic Investigation of the Correlates of Subtle and Overt Discrimination.
  17. Murphy, M. C., Steele, C. M., & Gross, J. J. (2007). Signaling Threat: How Situational Cues Affect Women in Math, Science & Engineering Settings.
  18. Rudman, L. A., Ashmore, R. D., & Gary, M. L. (2001). “Unlearning” Automatic Biases: The Malleability of Implicit Prejudice and Stereotypes.
  19. Welle, B., & Heilman, M. E. (2007). Formal and Informal Discrimination against Women at Work: The Role of Gender Stereotypes.
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