Transcript What is ALTERR? - Ecology & Evolutionary Biology | UConn

What is ALTERR?

Academic Leadership Team to Enhance Recruitment and Retention
The ALTERR team is charged with:
1. developing expertise on techniques for effectively recruiting
the strongest and most diverse faculty possible
2. disseminating their expertise through a series of
presentations to faculty search committees
Angel De Blas, Physiology and Neurobiology
Sharon Harris, English and the Humanities Institute
Donald Les, Ecology and Evolutionary Biology
Felicia Pratto, Psychology
Stephen Ross, Economics
Carolyn Teschke, Molecular and Cell Biology, and Chemistry
Why is diversity important?
The fabric of diversity at our University must be woven in thought and in
experience, within a climate in which diverse views are welcomed and
respected and in which there is a commonality that comes from working
together to effect constructive change.
www.ode.uconn.edu/2009DT.pdf
Overview:
 The problem – disproportionality in hiring
 Studies on bias – a couple of examples
 Solutions
 UConn Resources
What is diversity?
 Encompasses the presence and participation of
people who differ by age, color, ethnicity, gender,
national origin, race, religion, and sexual
orientation.
 Includes those with disabilities and from various
socio-economic backgrounds.
 Encompasses not only individuals and groups, but
also thoughts and attitudes
www.ode.uconn.edu/2009DT.pdf
UConn’s definition of diversity includes:

Age

National Origin

Color Race Ethnicity

Religion

Disabilities

Socio-Economic Background

Gender

Thoughts and Attitudes
These categories are included in the University’s definition of
diversity and were approved by the University of Connecticut
Board of Trustees in August 2002.
www.ode.uconn.edu/Executive%20Summary.pdf
Our student body is diverse,
shouldn’t we be?
“Female student attrition in science and
engineering has been attributed, in part, to a
lack of female mentors and role models.”
Nelson & Rodgers (2006). A National Analysis of Diversity in
Science and Engineering Faculties at Research Universities.
Our student body is diverse,
shouldn’t we be?
Table 1. Gender Distribution of BS Recipients vs. Role Models
% Females
% Males
Students
Faculty
S/F ratio
Students
Faculty
S/F ratio
Math
48.2
8.3
5.8
51.8
91.7
0.6
Chemistry
47.3
12.1
3.9
52.7
87.9
0.6
Physics
21.4
6.6
3.2
78.6
93.4
0.8
Biological Sciences
58.4
20.2
2.9
41.6
79.8
0.5
Economics
32.3
11.5
2.8
67.7
88.5
0.8
Computer Science
27.7
10.6
2.6
72.3
89.4
0.8
Astronomy
32.7
12.6
2.6
67.3
87.4
0.8
Psychology
76.5
33.5
2.3
23.5
66.5
0.4
Political Science
50.1
23.5
2.1
49.9
76.5
0.7
Sociology
70.2
35.8
2.0
29.8
64.2
0.5
= biased beneficially
= biased negatively
BS degree data are for 2000, from NSF; faculty data are FY2002
except chemistry (FY2003) and astronomy (FY2004)
Our student body is diverse,
shouldn’t we be?

~50% of all doctorate degrees in the USA are earned by women;
however, women constitute only 39% of full-time faculty nationally
(women earn 40% of doctorate degrees in science & engineering but
make up only 28% of full-time faculty)
 The most prestigious academic positions are occupied by even fewer
women
 Only 24% of academic full professor positions are held by women
nationwide (19% in science and engineering fields)
:
Huang (n.d.). Gender Bias in Academia: Findings from Focus Groups
Table 2. Assistant Professors and PhD Attainment (1993–2002) in Science Disciplines
(% indicated; ratio is % Asst Professorships/PhDs; URM = underrepresented minority)
Discipline
Males (white)
Males (Asian)
Females (all)
Males (URM)
Asst
PhDs
ratio
Asst
PhDs
ratio
Asst
PhDs
ratio
Asst
PhDs
ratio
Chemistry
65.4
54.8
1.2
11.5
9.6
1.2
21.5
31.3
0.7
1.6
4.2
0.4
Computer Science
62.9
60.6
1.0
24.3
15.1
1.6
10.8
20.5
0.5
2.0
3.5
0.6
Math
60.5
58.1
1.0
15.0
11.3
1.3
19.6
27.2
0.7
5.0
3.3
1.5
Astronomy
62.6
69.8
0.9
9.9
6.6
1.5
22.0
20.6
1.1
5.5
2.6
2.1
Physics
70.6
68.9
1.0
14.9
13.9
1.1
11.2
13.3
0.8
3.3
3.8
0.9
Economics
59.8
54.9
1.1
16.1
9.6
1.7
19.0
29.3
0.6
5.1
6.0
0.9
Political Science
54.2
52.4
1.0
4.5
3.6
1.3
36.5
36.6
1.0
4.8
7.0
0.7
Sociology
37.2
31.5
1.2
3.5
3.0
1.2
52.3
58.9
0.9
7.0
6.5
1.1
Psychology
46.0
29.5
1.6
4.6
1.1
4.2
45.4
66.1
0.7
4.0
3.3
1.2
Biological Sciences
55.4
43.2
1.3
10.7
8.7
1.2
30.2
44.7
0.7
3.7
3.3
1.1
= biased beneficially
= biased negatively
Nelson & Rodgers (2006)
Table 3. Biased hiring results in other biases, e.g., membership in the National Academy
of Sciences (compiled 6-15-2010, NAS data):
Males
Females
M/F Ratio
Psychology
56
16
3.5:1
Evolutionary Biology
36
9
4
Ecology
48
8
6
Plant Biology
50
8
6
Social & Political Sciences
44
3
15
Mathematics
109
5
22
Engineering
79
3
26
Economics
60
2
30
Chemistry
192
6
32
Physics
183
4
46
Additionally:
► Only 40 of the 802 Nobel Laureates (5%) have been women (all fields).
► The first woman to win a Nobel Prize was Marie Curie (Physics, 1903);
there have been no female members added in Physics since.
Racial bias in hiring

non-academic positions:
Researchers sent fictitious resumes in response to 1,300 help-wanted ads listed in the
Boston Globe and the Chicago Tribune.
Each resume was randomly assigned either a very white-sounding name (Emily Walsh,
Brendan Baker) or a very African-American-sounding name (Lakisha Washington, Jamal
Jones).
Results:
 applicants with white-sounding names are 50% more likely to get called for
an initial interview than applicants with African-American-sounding names.
 white job applicants with higher-quality resumes received 30% more
callbacks than whites with lower-quality resumes. African-American
applicants received only 9% more callbacks for the same improvement in
their credentials
Bertrand & Mullainathan (2004) Amer. Economic Review 94: 991.
Letters of recommendation:
common pitfalls
 Letters for men tend to be
longer than those for
women.
 Letters for women tend to
highlight teaching and
training over research.
 Letters for women tend to
discuss their personal
details more that those for
men.
Trix & Psenka (2003) Discourse & Society 14: 191
Picking the short list:
 Having more than one female or minority candidate
de-emphasizes their ‘uniqueness’.
 Be open to the idea that there is more than one
way to measure excellence.
 Look for inconsistencies between letters and CV to
check for biases.
The Interview
 Questions not to ask?
http://ode.uconn.edu/Interview%20Questions.pdf
 A packet of general information will be provided to
send to short list candidates that covers child care,
partner benefits, and other information regarding
the region, etc.
 You are allowed to answer any question from a
candidate.
 Reach outside your department to find faculty to meet
with diverse candidates at a social event.
Financial resources at UConn:
 Faculty Excellence & Diversity Program (FEDP)
Office of the President and Provost

Deans may apply to FEDP for full funding of salary
and benefits of eligible, qualified candidates for the
life of the appointment.

Provides assistance in the recruitment of qualified
tenure-track candidates who possess a strong record
of scholarly accomplishments and other talents
which demonstrate that the candidate would
enhance the diversity of the School/College.
To qualify for FEDP money:
 Job description and ads must include at least one of the
following statements:




1. Contribute through research, teaching, and/or public
engagement to the diversity and excellence of the learning
experience.
2. Integrate multicultural experiences into instructional
methods and research tools.
3. Apply understanding of issues such as diversity and
multiculturalism to scholarship.
4. Provide leadership in developing pedagogical techniques
designed to meet the needs of diverse learning styles.
 The candidate must then demonstrate an ability to work
effectively in the context of diversity through unique
skills and talents.
 Remember to ask all candidates about their diversity
ODE.uconn.edu
qualifications.
Language for announcing positions
 In addition, proactive language can be included in job
descriptions to further indicate a department’s
commitment to diversity. This addition could make the
position more attractive to female and minority
candidates.
 Examples include:

The college is especially interested in qualified candidates who
can contribute, through their research, teaching, and/or
service, to the diversity and excellence of the academic
community.

The University is responsive to the needs of dual career
couples.

Women, minorities, individuals with disabilities, and veterans
are encouraged to apply.
‘Advance’ Handbook (University of Michigan)
Recent job ad with FEDP language
Where to send ads?
 Cast a broad net to have many candidates.
 Ads sent to specialized organizations (i.e., Journal
of Blacks in Higher Education) – can give an
impression of openness, even if the main ad is in
the most read journal for your field.

http://ode.uconn.edu/recruit.html
 Be open to other opportunities to find candidates –
i.e., networking through conferences. Phone
contact is an excellent method.
Advertising positions broadly can reduce net cumulative
employment discrimination.
Discrimination level

Bendick (1996). Discrimination against racial/ethnic minorities in access to employment in the
United States: Empirical findings from situarion testing. Geneva: International Labour Office.
Resources available to you
 ALTERR web site

clas.uconn.edu/about/alterr.html
 Office of Diversity and Equity

ODE.uconn.edu
 Human Resources

hr.uconn.edu
 International hires

International Service and Programs (DISP)
www.disp.uconn.edu/visas/hiring.html
In summary:
 Intellectual life is for everyone.


There are excellent women and minority faculty
candidates in the applicant pool.
Pro-active recruiting works to ensure a critical mass
of otherwise under-represented groups at UConn.
Your experiences?
 Can you tell us your successful techniques to share
with other search committees to help in the faculty
search process?
 Questions?