Sharon Broude Geva discusses the persistent issues of gender bias in the workplace, particularly in performance evaluations which negatively affect retention rates among women. Evidence suggests that women receive feedback that includes personal criticism while men receive constructive suggestions for skill development, leading to unequal career advancement opportunities. To improve retention and address these biases, recommendations include educating managers on unconscious biases, using objective language in reviews, and facilitating anonymous feedback.

1. Sharon Broude Geva
Director of Advanced Research Computing (ARC)
University of Michigan
sgeva@umich.edu
http://arc.umich.edu
We’re Done with Hiring.
We Now Have a Diverse Team.
Biases are a Thing of the Past!*
(*Spoiler alert – no, they really aren’t)
PEARC17 – New Orleans, July 11, 2017

2. Sharon Broude Geva
Director of Advanced Research Computing (ARC)
University of Michigan
sgeva@umich.edu
http://arc.umich.edu
Biases Hurt Retention,
Not Just Hiring and
Recruitment
PEARC17 – New Orleans, July 11, 2017

3. Have you ever heard that “men stay in a
job because they like the work, women
stay because they like their boss/co-
workers”?
Turns out, this may be a result of
culture, rather than a chromosomal
tendency …

4. Biases don’t go away just because we managed to overcome
them during the hiring process.
Underrepresented groups talk about ”death by a thousand
paper cuts” which led them to leave a job or even a career.
Can you think of any part of a job that has the propensity to
inflict paper cuts, or even more serious damage?

5. How about performance evaluation?
Whether it’s annual, bi-annual, or daily, it has huge impact on
• morale
• promotion
• relationships inside the office
• and ultimately – on retention

7. Basically:
“The language used for both genders conforms to stereotypes
of women being more adept in supporting roles and men being
more independent. While women were given constructive
feedback for using communication perceived as aggressive,
they were also found to be “supportive,” “collaborative” and
“helpful” more often than men. Meanwhile, men were twice as
likely to receive feedback based on their technical expertise.
These assumptions result in women and men being put on
different career paths, with men being favored for leadership
positions. “ (Source: Wall Street Journal)

8. 2014 study by
Kieran Snyder, PhD in
Linguistics and Cognitive
Science

9. “The critical feedback men receive is heavily geared towards
suggestions for additional skills to develop. A few examples:
• “Constructive feedback on your performance as a feature crew
tester can be summed up by saying that you still have some
skills to continue to develop.”
• “Hone your strategies for guiding your team and developing
their skills. It is important to set proper guidance around
priorities and to help as needed in designs and product
decisions.”
• “There were a few cases where it would have been extremely
helpful if you had gone deeper into the details to help move an
area forward.”
• “Take time to slow down and listen. You would achieve even
more.”
”
(Source: Kieran Snyder, http://fortune.com/2014/08/26/performance-review-
gender-bias/)

10. “
Women receive this kind of constructive feedback too. But the
women’s reviews include another, sharper element that is absent
from the men’s:
• “You can come across as abrasive sometimes. I know you don’t
mean to, but you need to pay attention to your tone.”
• “Your peers sometimes feel that you don’t leave them enough
room. Sometimes you need to step back to let others shine.”
• “The presentation ultimately went well. But along the way, we
discovered many areas for improvement. You would have had
an easier time if you had been less judgmental about R---‘s
contributions from the beginning.”
“
(Source: Kieran Snyder, http://fortune.com/2014/08/26/performance-review-
gender-bias/)

11. “This kind of negative personality criticism—watch
your tone! step back! stop being so judgmental!—
shows up twice in the 83 critical reviews received by
men. It shows up in 71 of the 94 critical reviews
received by women.”
(Source: Kieran Snyder,
http://fortune.com/2014/08/26/performance-review-gender-
bias/)

12. It’s not just about gender bias. Some food for
thought:
• Stellar employees are Morning People
• Woman just can’t get along with each other
• People with a degree in XXXX just aren’t that good
• People who don’t make eye contact can’t communicate well
• …

13. So what can be done to alleviate the unconscious biases
everyone has?
1. Help managers understand and confront unconscious biases.
Again – we all have them!
2. Be conscious of language. Ask yourself: Is this a judgement or
a fact? Is this perception of personality or “optimal personality”
subjective? Use verbs rather than adjectives when reviewing!
3. Move to 360-degree reviews. A large group of reviewers might
mean less bias.
4. Facilitate anonymous employee feedback to managers. It
could make them more aware of their biases.
5. Help employees track feedback. It holds managers
accountable and allows transparency in the process.

14. Bottom Line:
It takes awareness, thought, and work to retain a
diverse workforce.
(but we’ve been learning about the recruitment and
hiring of a diverse workforce, and we have some
tools that transfer to retention)

15. U-M Research Computing Modular
Data Center
Image courtesy of Russell Dekema and
James Bergman

16. The University of Michigan (U-M)

17. Questions?
sgeva@umich.edu
arc.umich.edu

18. Coalition for Academic Scientific Computation (CASC)
❖ Founded in 1989
❖ an educational nonprofit 501(c)(3) organization
❖ 86 member institutions representing many of the
nation’s most forward thinking universities and
computing centers
❖ CASC is dedicated to advocating the use of the most
advanced computing technology to accelerate
scientific discovery for national competitiveness,
global security, and economic success, as well as
develop a diverse and well-prepared 21st century
workforce.

19. CASC’s mission:
❖ disseminate information about the value of high
performance computing and advanced
communications technologies;
❖ provide an ‘expert resource’ for the Executive
Office of the President, the Congress, and
government agencies; and
❖ facilitate information exchange within the
academic scientific computation and
communication community.

21. Advanced Research Computing at U-M (ARC)