This document discusses implicit biases and stereotype threat that can negatively impact women and other underrepresented groups in fields like science and academia. It notes that while explicit sexism has decreased, unconscious biases still exist and influence perceptions and evaluations. These unconscious biases can result in unfair outcomes like lower marks, unequal hiring, and impediments to women's career progress. The document also describes how stereotype threat can cause members of these groups to underperform on tasks when their social identity is emphasized. It provides suggestions for addressing these issues, such as anonymizing processes, focusing on merit-based criteria, increasing diversity among role models, and reflecting on one's own biases.

1. Jennifer Saul
j.saul@sheffield.ac.uk

2. Low numbers of women in Science, Engineering,
Mathematics
Also other fields, e.g Philosophy (16-25%
worldwide).
Low numbers of women at the top in almost
every field

3.  Innate, unchangeable psychological differences?
 Difficulty combining work and childcare?
 Conscious, old-fashioned sexism?
 Sexual harassment?
 But there’s very good reason to believe that unconscious
psychological phenomena are playing a role (also with other
groups).

4.  Implicit Biases: those that we will be concerned
with here are unconscious biases that affect the way
we perceive, evaluate, or interact with people from
groups that are stigmatised in our society.
 Stereotype Threat: people’s awareness of their
group membership may (often unconsciously) have
a negative impact on their performance.

5.  Arises from our very useful tendency to make fast associations.
 Our tendency to make automatic unconscious associations leads to problems when it
comes to social groups.
 Most of us have unconscious, automatic biases based on the ways that social groups
are stereotyped in our societies.

6. These are often contrary to genuinely held
commitments.
They are held even by members of the target
group.

7. Anonymous marking leads to higher marks
for women (Bradley 1984, 1993)

8. Man:
• “brilliant”
• “outstanding”;
• “original”
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9. Woman:
• “works hard”
• “friendly”
• “surprisingly successful
• “friends with my wife”
• “very attractive”
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10. More likely to call on male students, more
likely to charitably interpret their
inchoate contributions.
More likely to take point raised by a
woman seriously if re-stated by a man.
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11. CVs: Same CV, with different names
•John more employable than Jane.
•John more employable than Yasser.
•Parenthood harms women.
Dying out? No: 2012
Strong for men and women,
of all ages.

12. 2013 study, in International Relations
• Of faculty members at research universities: The
average paper by an untenured male is cited 26.7
times, while the average paper by a female colleague
at same level would be cited only 2.15 times.

15. Examples:
People not receiving the marks that they
should
Hiring not based on merit
Women’s career progress impeded

16. Underperformance on particular tasks by
members of groups stigmatised as less good
at these tasks, when
• They really care about doing well
• Stakes are high
• They are reminded of their group membership

17. Women who are reminded of their gender
(by ticking a gender box, or by being
surrounded by men), taking a high-stakes
math test, will underperform.

18. Black men taking tests “of academic ability”
will underperform.

19. White men at Ivy League universities doing
tests of athletic ability will underperform if
reminded of their race.

20. 5-7 year old girls will do worse on a math test if
they take it after colouring in a picture of a girl
with a doll.

21. With exactly the same talent and dedication, it
will be harder for members of some social
groups to perform well: UNJUST.
Many people will fail to perform as well as they
otherwise might.
Society will not have the benefit of the full
contributions that some groups might make.

22. First, Implicit Bias.
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23. Don’t just tell yourself “ don’t be biased”.
Don’t just tell yourself not to see gender or
race.
Don’t just tell yourself to be objective.

24. Putting women on hiring committees in
order ensure gender fairness.
•Women, like men, are very likely to hold negative
implicit biases against women. So won’t help with
implicit bias.
•However: can help candidates not to suffer from
such serious stereotype threat while being
interviewed.
 But note: One woman probably won’t be enough.

25. Anonymise– when possible. (Think about
parts of process to anonymise.)

26. Spend some time thinking about
counterstereotypical exemplar….

27. Get more counterstereotypical exemplars in.
•As students, as lecturers, as researchers, as visiting
speakers, at conferences, on reading lists.
•This both reduces the influence of biases and helps
to change the regularities in the world that
perpetuate the biases.

28. But that means basing one’s judgments (in
part) on something other than merit!
•Our judgments are already (in part) based on
something other than merit: they are based partly on
social prejudices.
•These prejudices prevent us from properly discerning
merit.
•The only way we will ever be able to properly judge
merit is if we first break down our bad, biased habits.

29. Being hungry, tired and rushed increases
manifestation of implicit bias. Glucose
decreases it.

30. Agree on criteria in advance.
Get feedback on each element as you go,
to avoid overall gestalt evaluation.

31. Spend some time thinking about past
instances where you were biased.

32. Try harder to notice when a woman
student wants to speak.
If a woman’s comment is being ignored,
or attributed to someone else, speak up.
Perhaps: adopt an affirmative action
policy in chairing discussions.
Re-examine your letters of reference for
gendered content.

33. Stereotype threat: alternative identity

34. Reflecting on counterstereotypical
exemplars.
Sharing stories of those who have succeeded
despite it.
Talk about it as a possible source of anxiety.
Values affirmation.

35. Tackling phenomena like these requires
reshaping the way that we think about
bias…
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38. Chris Hookway argues that to be
responsible inquirers we need to know
that we can trust our cognitive
instruments.
The implicit bias literature shows us that
we have faulty cognitive instruments.
It’s also starting to show us how to fix
them.
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39. • Being biased is not always blameworthy: the
tendency to implicit bias is part of the human
condition.
 Many people are totally unaware of their implicit biases
and the effects that they have.
 Even after becoming aware, people are likely to not know
how to combat them.
So blame is not appropriate just for having implicit biases.

40. Bias becomes blameworthy if people
learn about implicit bias and don’t try to
do anything to change.

41. We need, collectively and individually, to
fix our cognitive instruments.
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