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February 11, 2014

Mentoring Relationships Across Difference A Workshop for Mentors. February 11, 2014. Learning Objectives. Learn about faculty diversity at UCSF Understand the concept of “ implicit/unconscious bias ” and its potential impact on mentor-mentee relationships

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February 11, 2014

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  1. Mentoring Relationships Across Difference A Workshop for Mentors February 11, 2014

  2. Learning Objectives Learn about faculty diversity at UCSF Understand the concept of “implicit/unconscious bias” and its potential impact on mentor-mentee relationships Learn 3 strategies for how to work more effectively with diverse mentors or mentees

  3. Diversity At UCSF Diversity refers to the variety of personal experiences, values, and worldviews that arise from differences of culture and circumstance. Such differences include race, ethnicity, gender, age, religion, language, abilities/disabilities, sexual orientation, gender identity, socioeconomic status, geographic region, and more. http://www.universityofcalifornia.edu/diversity/diversity.html Office of Diversity and Outreach established 2010

  4. Black, Native American, and Hispanic Medical School Faculty: <10% Percentage of U.S. Medical School Faculty by Race and Ethnicity, 2012 AAMC Women in US Academic Medicine Statistics and Benchmarking Report, 2011-2012

  5. Representation of Women in Academic Medicine, 2011-2012 Representation of Women (%) AAMC Women in US Academic Medicine Statistics and Benchmarking Report, 2011-2012

  6. Distribution of Women Faculty by Rank, 2012 AAMC Women in US Academic Medicine Statistics and Benchmarking Report, 2011-2012

  7. Distribution of Men Faculty by Rank, 2012 AAMC Women in US Academic Medicine Statistics and Benchmarking Report, 2011-2012

  8. UCSF Faculty Trends n = 2325 / 2397 / 2475

  9. UCSF Faculty Gender by Series,December 2012 n = 2475

  10. School of Dentistry

  11. School of Medicine

  12. School of Nursing

  13. School of Pharmacy

  14. Fall 2012 Students/Trainees by Racial/Ethnic

  15. 2012 UCSF Students and Trainees by Gender

  16. Barriers to Diversity Pipeline Support Systems Professional Role Models Disparity in scientific identity and values Mentoring Unconscious Bias

  17. Unconscious Bias • National Academy of Science (2006) • Greatest barrier to achieving gender equity in STEMM is systematic bias, frequently unconscious • NSF (2007), Office of Research on Women’s Health (2007), NIH (2008) • Institutional transformation -- changing attitudes and behaviors -- required to ensure equal opportunities

  18. Unconscious Bias AAAS (2007) – “bias literacy” is prerequisite to action Institutional change requires making explicit what may be implicit (unconscious) through addressing the bias process (Carnes et al., 2012)

  19. What is Unconscious Bias? Social stereotypes about certain groups of people that individuals form outside their own consciousness Patterns based on small bits of information Often incompatible with our conscious values

  20. What is Unconscious Bias? • Implicit Association Test (IAT) http://implicit.harvard.edu/ • Biases and associations exist in most people (over 75%) – 15 years of research, more than 10 million taken IAT • Maps to existing social hierarchies and stereotypes (Nosek, 2009) • Favor men, Whites, youth, heterosexuals, and physically able • Males = Science; Females = Liberal Arts

  21. Unconscious BiasInstitutional Diversity Data we receive from others may be biased Regardless of gender or ethnicity, we also have biases Affects hiring, evaluation, selection of leaders (Wright, AAMC, 2010)

  22. EvaluationEthnic/Racial • Race and resume (King et al., 2006) • Whites & Hispanics benefit from quality resume • Blacks evaluated negatively with quality resume • Occupational Stereotypes – Black & Hispanics more suited for lower status; Asians high status regardless of resume

  23. EvaluationEthnic/Racial • NIH Review Panels (Ginther et al., 2011) • Black applicants 10% less likely than Whites to receive NIH investigator initiated research grants • Taking into account education, country of origin, training, previous research awards, publications & employer

  24. Probability of NIH R01 Award by Race and Ethnicity, FY 2000 to FY 2006 (N = 83,188) R01 Award Probability (%) Ginther DK et al, Science 2011

  25. EvaluationWomen • Symphony orchestras • Switched to “blind” auditions – increased hiring of women by 25% (Goldin & Rouse, 2000) • Recommendation Letters for Faculty • Similarities but more “standout” adjectives for males (Schmader et al., 2007) • Female letters shorter, contained more “doubt raisers” & focus on teaching; males as researchers (Trix & Psenka, 2003)

  26. EvaluationWomen • Research Science Faculty Ratings of Students • Randomized national study – faculty rated identical applicants identified as male or female for lab manager (Moss-Racusin et al, 2012) • Male student more competent and hireable than female • Hiring starting salary and more mentoring for males as compared to females

  27. Motherhood Penalty • Mothers • Lower perceived competence & starting salaries. (Correll et al., 2007; Heilman & Okimoto, 2008) • Less interest in hiring & promoting mothers compared to fathers & childless employees. (Cuddy et al., 2004) • Fathers • Not penalized & sometimes benefit from fatherhood. (Correll et al., 2007)

  28. DISCUSSION AND STRATEGIES Burgess et al. 2007

  29. What Works?: Individual • Enhance internal motivation to reduce bias • Recognize unconscious bias (IAT) • Self-discovery within a non-threatening, private context • Increase the understanding about the psychological basis of bias • Normal aspect of human cognition • Improve ability to build partnerships with others • Finding a common ground • Enhanced empathy • Perspective taking • Role play-team discussions Burgess et al. 2007

  30. What Works?: Institutional Concrete, objective indicators & outcomes reduce standard stereotypes (Fiske & Taylor, 1991; Heilman, 2001; Bernat & Manis, 1994) Decreasing ambiguity about individual contributions to joint outcome reduces bias in performance evaluation (Heilman & Haynes, 2005) Use structured interviews and objective evaluation criteria (Martell & Guzzo, 1991; Heilman, 2001)

  31. What Works?: Institutional Commit to specific credentials before reviewing applications (Uhlmann & Cohen, 2005) Allow sufficient time as bias stronger when under time pressure(Martell,1991; Blair & Banaji,1996) Provide training workshops (Blair & Banji, 1996) Accountability for decision makers (Foschi, 1996;2000; Foschi et al., 1994) AAMC webinar: Science of Unconscious Bias

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