University of Nottingham
WinSET Debate
3 July 2013
• So called, scissors diagrams are often used
to illustrate the “leaky pipeline” for
women along a career pathway
HE career progression at UK HE
institutions by gender, Maths 2007/08
Data source: HESA (2008)
Pipeline: Progression in physics by gender,
2007/08
Data source: HESA (2008)
• Two key issues are recruitment into a
subject at UG level and subsequent
retention of those students into the
profession
• A crude measure of the leakage of women
along the higher education pipeline is the
ratio of the proportion of UGs who are
female and the proportion of professors
who are female
Pipeline: Progression in physics by gender,
2007/08 [UG(%F):P(%F) ~ 4:1]
Data source: HESA (2008)
Pipeline: progression in biology by gender
2007/08 [UG(%F):P(%F) ~ 3.5:1]
Data source: HESA (2008)
HE career progression at UK HE institutions by
gender, Maths 2007/08 [UG(%F):P(%F) ~ 9:1]
Data source: HESA (2008)
Pipeline: progression in chemistry by gender,
2007/08 [UG(%F):P(%F) ~ 7.5:1]
Data source: HESA (2008)
Pipeline: progression in clinical medicine by
gender 2010/11 [UG(%F):P(%F) ~ 2.5:1]
Chemistry data used for GCSE and A Level
Data source: HESA (2008)
Pipeline: progression in psychology by
gender, 2011/12 [UG(%F):P(%F) ~ 2.5:1]
Data source: HESA (2008)
• Perhaps the so-called “leaky pipeline” is
just a reflection of times when smaller
proportion of women read science
• Perhaps women just choose to leave
academia
• Examining the proportions of male and
female permanent academic staff who are
professors, respectively, in particular age
bands provides a comparison of the
likelihood of men and women being
professors, irrespective of the make up or
history of the cohort
Proportion permanent academic staff who
are professors by age (all cost centres)
30%
28.0%
Male
25%
Female
19.4%
20%
15%
11.1%
10%
5%
6.4%
3.6%
1.0%
0%
31-40
41-50
51-60
Age
Data source: HESA (2012)
Proportion permanent academic staff who
are professors by age (physics)
70%
Female
Male
60%
62.4%
47.6%
50%
40%
36.2%
30%
22.8%
20%
10%
7.6%
4.9%
0%
31-40
41-50
51-60
Age
Data source: HESA (2012)
Proportion permanent academic staff who
are professors by age (chemistry)
60%
Male
50%
40%
Female
35.8%
30%
25.8%
20%
10%
48.8%
13.1%
8.6%
2.6%
0%
31-40
41-50
51-60
Age
Data source: HESA (2012)
Proportion permanent academic staff who
are professors by age (mathematics)
60%
Male
50%
40%
Female
49.6%
35.0%
30%
20%
12.0%
10%
11.6%
6.8%
2.9%
0%
31-40
41-50
51-60
Age
Data source: HESA (2010)
• Nationally, a significant proportion of
mathematics staff are classified as
“teaching-only”. Women are more likely
to be in teaching-only positions than men.
Examining the mathematics staff data
excluding teaching-only staff give a
different picture, albeit women are still less
likely than men to be professors
Proportion permanent academic staff who
are professors by age (mathematics: without
teaching-only staff)
70%
Male
60%
Female
60.2%
50%
39.5%
40%
27.0%
30%
17.1%
20%
10%
8.0%
4.5%
0%
31-40
41-50
51-60
Age
Data source: HESA (2012)
Proportion permanent academic staff who
are professors by age (biosciences)
50%
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
Male
Female
44.1%
26.7%
22.0%
9.7%
4.6%
0.1%
31-40
41-50
51-60
Age
Data source: HESA (2012)
Proportion permanent academic staff who
are professors by age (psychology)
40%
Male
35%
Female
35.1%
30%
25%
17.9%
20%
14.6%
15%
10%
6.0%
5.9%
5%
1.4%
0%
31-40
41-50
51-60
Age
Data source: HESA (2012)
Proportion permanent academic staff who
are professors by age (Nursing & Paramedical
Studies)
9%
8%
Male
7%
Female
7.9%
6.1%
6%
4.7%
5%
4%
3%
2%
2.6%
2.1%
1%
0.5%
0%
31-40
41-50
51-60
Age
Data source: HESA (2012)
• In only one cost centre women more likely to be
professors than men, chemical engineering
Proportion permanent academic staff who
are professors by age (chemical engineering)
70%
65.8%
Male
60%
Female
55.2%
50%
40%
30.0%
30%
20.1%
20%
10%
6.4%
10.0%
0%
31-40
41-50
51-60
Age
Data source: HESA (2012)
• In every subject bar one, men are more likely to
be professors than women, often significantly so
• The biggest disparities are in materials and
mathematics
• If you are male and want to be a professor, study
physics
• If you are female and want to be a professor,
study chemical engineering
Thank you
Sean McWhinnie
Tel: 01235 439188
Email: sean.mcwhinnie@oxfordresearchandpolicy.co.uk