RECOGNIZING THE BEST AND THE BRIGHTEST

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RECOGNIZING THE BEST AND THE BRIGHTEST

• Overcoming Hidden Bias

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Who are we? Why are we here?
Prof. Thomas DeFrantz Professor of Music and
Theater Arts Director, Womens and Gender
Studies Prof. Sally Haslanger Professor of
Linguistics and Philosophy
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Outline

• Why might we care about diversity?
• Some data
• Schemas and implicit bias
• Stereotype threat and solo status
• Feedback loops
• Discussion
• An annotated bibliography and copies of research
  we are relying on can be found on Stellar at
• http//stellar.mit.edu/S/project/equityissues/inde
  x.html

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• MITs mission statement
• The Institute is committed to generating,
  disseminating, and preserving knowledge, and to
  working with others to bring this knowledge to
  bear on the world's great challenges. MIT is
  dedicated to providing its students with an
  education that combines rigorous academic study
  and the excitement of discovery with the support
  and intellectual stimulation of a diverse campus
  community. We seek to develop in each member of
  the MIT community the ability and passion to work
  wisely, creatively, and effectively for the
  betterment of humankind.

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Why do we care?

• We want the highest quality faculty we can get to
  respond to the conditions of the world today.
• For excellence in research, competitiveness in
  our disciplines.
• To respond to the growing diversity of our
  student body.
• Fairness is crucial in a genuine meritocracy.
• Women and minorities are underrepresented in high
  status occupations relative to their quality.
• The composition of the candidate pool only
  accounts for part of the problem.
• Research shows that we all regardless of gender
  or race treat people differently based on their
  perceived social group.
• All else being equal, diversity is valuable.

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School of Science Tenure Data
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Numbers in Math
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Numbers in EAPS
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Numbers in Biology
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Numbers in BCS
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What are the numbers in Physics?

• 75 faculty total including 5 women (6) and 1
  underrepresented minority     
• 242 graduate students total including 37 (15)
  women and 13 (5) underrepresented
  minorities       
• 2008 SB degrees 88 total including 26 (29)
  women and 14 (15) underrepresented minorities.

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Numbers in Chemistry?
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Schemas and Discrimination

• Explicit Discrimination conscious actions
  directed against members of a group.
• Schemas Non-conscious expectations or
  stereotypes associated with members of a group
  that guide perceptions and behaviors.
• Action based on schemas is pervasive and
  inevitable. But schemas can be distorting and
  result in poor judgment.

Valian (1998) Why So Slow? The Advancement of
Women. Cambridge MIT Press, p. 280
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Schemas are widely shared

• Research shows that we all regardless of gender
  or race perceive and treat people based on
  schemas associated with their race/gender/social
  group.
• Both men and women hold them about gender
• Both whites and people of color hold them about
  race
• People are typically not aware of them, but with
  effort can become aware of them and change them.
• Implicit association test
• https//implicit.harvard.edu/implicit/

Fiske (2002). Current Directions in Psychological
Science, 11, 123-128.
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Schemas play a significant role when there is

• Ambiguity (including lack of information)
• Stress from competing tasks
• Time pressure
• Under-representation of the group in question
  (when the group does not reach critical mass)

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Schemas and Evaluation

• Applicants with African American-sounding names
  had to send 15 resumes to get a callback,
  compared to 10 for applicants with white-sounding
  names.

Jamal

• White names counted as an additional 8 years of
  experience.
• The higher the resume quality, the greater the
  gap in callback rate.

Greg
Bertrand Mullainathan (2004) Poverty Action
Lab, 3, 1-27.

• When evaluating identical application packages,
  male and female university psychology professors
  preferred 21 to hire Brian (or Barack?) over
  Karen.

Steinpreis, Anders, Ritzke (1999) Sex Roles,
41, 509.
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Schemas and Evaluation

• Applicants with African American-sounding names
  had to send 15 resumes to get a callback,
  compared to 10 for applicants with white-sounding
  names.

Jamal

• White names counted as an additional 8 years of
  experience.
• The higher the resume quality, the greater the
  gap in callback rate.

Greg
Bertrand Mullainathan (2004) Poverty Action
Lab, 3, 1-27.

• When auditioners were placed behind a screen,
  the percentage of female new hires for orchestral
  jobs increased 25 46.

Goldin Rouse (2000) The American Economic
Review, 90, 4, 715-741
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Evaluation of Fellowship Applications

• the success rate of female scientists applying
  for postdoctoral fellowships at the Swedish
  Medical Research Council during the 1990s has
  been less than half that of male applicants.

Results of study Women applying for a post-
doctoral fellowship had to be 2.5 times more
productive to receive the same reviewer rating as
the average male applicant.

• Similar findings
• USA/GAO report on Peer Review in Federal Agency
  Grant Selection (1994)
• European Molecular Biology Organization Reports
  (2001)
• NIH Pioneer Awards Journal of Womens Health
  (2005) Nature (August 2006)

Wenneras Wold (1997) Nature, 387, 341.
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Gender Schemas in Recommendations for Successful
Medical School Faculty Applicants

• Letters for men
• Longer
• More references to CV, Publications, Patients,
  Colleagues

• Letters for women
• Shorter
• More references to personal life
• More doubt raisers, including hedges, faint
  praise, and irrelevancies (e.g., Its amazing
  how much shes accomplished. It appears her
  health is stable. She is close to my wife.)

Trix Psenka (2003) Discourse Society, 14(2)
191-220, 2003.
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More evidence of evaluation bias

• Race stereotypes often lead to different
  standards of assessment.
• Women and minorities are more easily judged
  competent,
• But standards for excellence are set higher than
  for men and whites.

Biernat Kobrynowicz, 1997
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Stereotype Threat

• Stereotype threat occurs when your group is
  stereotyped as performing poorly in a domain and
  your performance may appear to confirm the
  negative stereotype.
• Performance decreases on computational and recall
  tests.
• Conscious awareness of the threat is not
  necessary for the effects.
• Stereotype threat is situational performance
  decreases only in settings where the stereotype
  is activated.

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Solo Status

• Solo status occurs when one is the only member of
  ones social group in a setting.
• Solo status increases the risk of stereotype
  threat public settings also exacerbate the
  effects.
• Explanation of stereotype threat is contested,
  but addressing solo status can reduce stereotype
  threat.

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Accumulation of advantage disadvantage

• Like interest on capital, advantages accrue.
• Like interest on debt, disadvantages accrue.
• Small differences in treatment can accumulate to
  cause major consequences in salary, promotion,
  prestige.

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Accumulation of disadvantage feedback loop
LOWERED CAREER SUCCESS RATE
Affects educational opportunities, publication
rate, funding, climate of support, etc.
Lack of critical mass
Confirms schema
Performance is underestimated
Evaluation Bias
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Brainstorming

• How do we account for the numbers in your
  department?
• What is your explanation?

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Brainstorming

• What actions, strategies, solutions do you have
  to offer?

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Accumulation of disadvantage feedback loop
LOWERED CAREER SUCCESS RATE
Affects educational opportunities, publication
rate, funding, climate of support, etc.
Lack of critical mass
Confirms schema
Performance is underestimated
Evaluation Bias
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Accumulation of disadvantage feedback loop
Improved
LOWERED CAREER SUCCESS RATE
Affects educational opportunities, publication
rate, funding, climate of support, etc.
Lack of critical mass
Creates
Confirms schema
Disconfirms
Valued appropriately
Performance is underestimated
Evaluation Bias
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Next steps

• Challenge the myth of non-bias
• Even individuals who are strongly egalitarian may
  still rely on problematic schemas.
• Confidence in your own fairness may prevent you
  from being as fair as you aim to be. E.g., If
  you are always fair, then others weaknesses must
  be their own fault.
• Search not (just) sort
• Distributed leadership

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Next steps

• Mentorship
• Cultivating talent
• Making a difference in someones life

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MIT Diversity CongressProf. Michael Summers, UMBC