Courses, qualifications and career choices: does higher education amplify or reduce

gender inequalities?

Kate Purcell

Warwick Institute for Employment Research

GENDER, CLASS, EMPLOYMENT AND FAMILY INTERNATIONAL CONFERENCECity University, London, March 27-28, 2008

CURRENT CONTEXT• Human capital – in particular, university-educated labour –

increasingly regarded as crucial to economic development– successive UK governments have invested in increasingly high levels of

education on assumption that knowledge-based skills and innovation are increasingly crucial for competitiveness;

– evidence that educated labour is more innovative and adaptable;– development of social and material educational infrastructure.

• Economic restructuring – global, sectoral, organisational– SO changing demand for skills and knowledge due to

• transformation of UK manufacturing from labour-based to knowledge-based (e.g. growth of science-based industries – chemicals, biotechnology, ICT (– depends on highly skilled and educated labour);

• growth and globalisation of market services.

• Impact of technology on information management and communication.

• Global concern with the eradication inequalities.

0

5

10

15

20

25

30

35

40

Source: Office for National Statistics

API (

%)

Entry to Higher Education, Age Participation Index (API) 1961 to 2006

What does this mean?

• Increase in graduate labour supply• Reflects increase in range of skills and

knowledge being developed on undergraduate programmes

• Upskilling of population or increase in credentialism?

• Increase in women’s participation in higher education

• Change in the gender balance of power – decrease in female dependency?

• Contribution to gender equality of opportunity?

Changing structure of occupations UK 1981-2006

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

20,000

1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005

Tho

usan

ds

SOC2000 Major Groups 1, 2 and 3

SOC2000 Major Groups 4, 5, 6, 7, 8 and 9

Source: Unpublished estimates of employment: Warwick Institute for Employment Research / Cambridge Econometrics, 2005

Previous research on graduate careers and outcomes

• Higher education choices gendered – in terms of subject choices and qualifications achieved

• Women benefit from degree financially more than men BUT• Graduate women are more likely to be in ‘non-graduate’ employment

than male peers and are less likely to be satisfied with career progression

• Gender pay gap – that widens as careers progress (from first job to outcomes 7 years on)

• Gendered graduate labour market – in terms of sectoral, occupational outcomes

• Living in partnerships and having children widens gender pay gap and impacts on career planning.

• Women value high earnings less and having work of social value more than men BUT similarities in career attitudes and expectations

• High-flying women make different choices, report reduced bargaining power than male peers

• Surprising incidence of women in early-mid-30s making career changes as a result of values (desire for generativity?) and for expediency in terms of accommodating family-building plans.

0 5 10 15 20 25 30 35

Other

Other public services

Education

Business services

Banking, finance, insurance

Information and communications sector

Transport and tourist services

Distribution, hotels, catering

Construction

Electricity, gas, water supply

Manufacturing

Agriculture, mining, quarrying

per cent

Female

Male

Sector of employment at time of survey, by Sector of employment at time of survey, by

gendergender

Source: Class of ’99 survey (Purcell et al. 2006)

Occupation held at time of survey

05

1015202530354045

Managers &Senior Officials

ProfessionalOccupations

AssociateProfessional &

TechnicalOccupations

Administrative &secretarial

Occupations

Other

Male

Female

%

Source: Class of ’99 survey (Purcell et al. 2006)

The impact of sector and occupation: three examples

Subject studiedHumanities Law Engineering

Males Females Males Females Males Females

Gender ratios 44:56 50:50 90:10

Average earnings £30,033 £24,114 £43,458 £33,824 £31,837 £28,789

Gender pay gap 20% 22 % 10%

Using degree subject knowledge in current job

31% 37% 85% 79% 75% 50%

Using degree skills 69% 74% 94% 89% 86% 75%

Source: Seven Years On: a survey of the career paths of 1995 graduates (Purcell and Elias 2005)

• Initial population census with targeted follow-up of under-represented groups.

• Reliance exclusively on web-based data collection.

• Contact with universities and colleges to maintain contact and ‘rebalancing’.

• Substantial resources devoted to:• retention of sample members;• co-ordination across HECSU wider research

programme;• dissemination of research findings.

• Longitudinal pilot survey, question testing, consultative approach to identification of priorities at each wave.

Futuretrack - The Research Design

506,304 UCASapplicants

84,932 ‘late applicants’or no email supplied

not e-mailed invitation (16.8%)

421,372invited to participatein survey(83.2%)

120,669responses in scope

(23.8% of allapplicants)

299,943no response

(59.2%)

SURVEY RESPONDENTS99,887 (82.8%)

accepted places in HE14,781 (12.2%)not accepted6001 (5.0%)

outcome not known

NON RESPONDENTS218,958 (73%)

accepted places in HE80,985 (27%)not accepted

OTHER APPLICANTS65,874 (77.6%)

accepted places in HE19,058 (22.4%)not accepted

HE NON-PARTICIPANTS

SHORT SURVEY7,591

respondents

760 responses not in scope

(0.2%)

Futuretrack Wave One: Population and response

Outcomes of applications, all applicants

Males Females Accepted in main scheme

80.7 78.6

Accepted in UCAS extra

0.7 0.9

Accepted in clearing 5.7 5.3 Not accepted 12.8 15

Multivariate analysis results*: factors relating to a successful application

• Strongest association is with tariff points• Age and gender (19-20 age group has

increased likelihood of success, as do men)• Social background significant, but effect not

large• Ethnicity matters - but only for a few groups:

• Asian Pakistani, Asian ‘other’, Black African, Black ‘other’ have lower probability of success

• Expectation of place in 1992 university• Small effect from ‘Father has HE quals’

Subject applied for, comparing male and female distributions (accepted applicants)

0 2 4 6 8 10 12 14

Interdisciplinary, other combined subjects

Social Science combined with arts

Science combined with social science

Education

Creative Arts & Design

Hist & Philosophical studies

Languages

Linguistics and Classics

Mass communication and Documentation

Business & Admin studies

Law

Social Studies

Architecture, Build & Plan

Engineering, Technologies

Mathematical & Comp Sci

Physical Sciences

Biology, Vet Sci, Ag & related

Subjects allied to Medicine

Medicine & Dentistry

Male Female

Career decision-making prior to HE application….

Why did they apply to study on full-time HE courses?

Why did thy choose to study at that particular university or college?

Why did they choose that subject or discipline?

What access did they have to career information and guidance?

Reasons for applying to HE by gender

0 10 20 30 40 50 60 70 80 90

Better than being unemployed

Friends are doing so

Teachers encouraged to apply

Normal thing to do

Want to be a student

Want to realise my potential

Want to study particular subject/course

Part of longer-term career plans

Enable to get a good job

Male Female

Percentage giving 'it will enable me to stay at home' as reason for choice of HEI, comparing ethnic origin by gender

0 10 20 30 40 50 60

White

Black other

Black Caribbean

Black African

Asian other

Asian Pakistani

Asian Indian

Asian Chinese

Asian Bangladeshi

Per cent

Female

Male

0 10 20 30 40 50 60 70 80 90

Other

Was advised that the course would be appropriate for me

Had difficulty deciding, was a reasonable option

Enables me to qualify for another course

Will lead to good employment opportunities

Need the course to enter particular profession

Opportunity to spend part of the course abroad

Modular course, keeps options open

Interested in the content of the course

Get good grades in subjects related to the course

Enjoy studying the subject

per cent

Female

Male

Reasons for choice of subject by gender

Subjects of study showing gender ratios

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Engineering, Technologies

Mathematical & Comp Sci

Architecture, Build & Plan

Physical Sciences

Business & Admin studies

Hist & Philosophical studies

Science combined with social science

Mass communication and Documentation

Medicine & Dentistry

Social Studies

Interdisciplinary, other combined subjects

Creative Arts & Design

Law

Social Science combined with arts

Biology, Vet Sci,Ag & related

Languages

Linguistics and Classics

Subjects allied to Medicine

Education

Not enough information about items identified, comparing selected

school students’ responses by gender

0

10

20

30

40

50

60

State School Single-sexschool

Fee-payingschool

State School Single-sexschool

Fee-payingschool

Males Females

Relation between courses an employment options Information about courses available

Not enough information about the implications of post-16 subject choices, comparing selected school students’ response by gender

0

5

10

15

20

25

30

35

40

State School Single-sexschool

Fee-payingschool

State School Single-sexschool

Fee-payingschool

Males Females

Not enough None

Degree of clarity about career ambitions, by gender

0

5

10

15

20

25

30

35

1 2 3 4 5 6 7

I have a clear idea of the occupation I want to enter......I have no idea [of what I want to do after my course]

Male Female

Career planning by subject

0 10 20 30 40 50 60 70 80 90 100

Historical and philosophical studies

Languages

Linguistics and classics

Physical sciences

Social science/arts

Maths and computing

Mass communication and documentation

Other interdisciplinary

Business and Admin.

Social studies

Biology, Vet and Agricultural related

Science/social science

Creative art and design

Engineering and technology

Law

Architecture, building, planning

Subjects allied to medicine

Education

Medicine & Related

% scoring 6 or 7 on career plans

% scoring 1 or 2 on career plans

Clarity of ideas about eventual occupation, main Business and Management sub-groups

0 10 20 30 40 50 60 70

Business studies

Management studies

Marketing

Tourism,Transport and Travel

Human Resource Management

Finance

Accounting

Self-scoring 1 or 7 on scale where 1 = 'I have a clear idea of the occupation I want to enter...'

Absolutely clear

Virtually clear

Clarity of ideas about ‘the occupation I eventually want to enter and the qualifications required to do so’

Factors associated with less clarity

Factors associated with greater clarity

Male Female

Young (under 19) at time of application

Older applicant (21+ at time of application)

White, Asian ethnic groups Black ethnic groups

Lower entry qualifications Higher entry qualifications

First choice subjects are: Languages, history and philosophical studies

First choice subjects are: Medicine, dentistry, education

Higher managerial and professional social background

Other social background

Independent school at time of application

Self-evaluated key skills, by gender

0

10

20

30

40

50

60

70

80

90

100

Male Female Male Female Male Female Male Female Male Female

WRITTENCOMMUNICATION

SPOKENCOMMUNICATION

NUMERACY COMPUTERLITERACY

SELF-CONFIDENCE

Excellent Very good Good

Self-rated ‘excellent’ or ‘very good’ numeracy skills by selected subject groups

0 20 40 60 80 100 120

Mathematics

Physics

Mechanical Engineering

Economics

Pre-clinical Medicine

Pharmacy/ Toxicology and Pharmacy

Electronic and Electrical Engineering

Architecture

Computer Science

Biology

Anatomy, Physiology and Pathology

Business Studies

Management Studies

Law (by area)

Sports Science

Combinations of science/ engineering with arts/humanities

Nursing

Psychology

Tourism, Transport and Travel

History by period

Design Studies

Languages

Sociology

Media Studies

Combinations of languages with arts/humanities

English Studies

Fine Art

Excellent or very good numeracy skills Excellent or very good written communication skills

Ethnic origin High self confidence rating (%)

Males Females Asian Bangladeshi 64 58 Chinese 44 34 Indian 62 51 Pakistani 63 54 Other 67 53 Black African 76 66 Caribbean 72 57 Other 70 57 White 51 40 Mixed 56 48 Total 54 43

Ethnicity and the gender confidence gap

Questions to be followed through

• How far are ‘vocational’ reasons related to actual or anticipated (gendered) caring roles?

• How far do attitudes and aspirations change as a result of HE participation and acquisition of skills and knowledge – and how does this differ according to subject and the gender balance of membership groups?

• How (and why) do gender outcomes differ during and beyond HE?

• Does the gender ‘confidence gap’ increase or shrink over the HE career?

• How far is numeracy competence related to a) self-confidence and b) career outcomes?

For further information on research discussed and related projects:

see www.warwick.ac.uk/go/glmf

www.hecsu.ac.uk

HECSU has developed a website primarily for Futuretrack members to provide information designed to encourage them to keep in touch with the project at:

www.futuretrack.ac.uk

Futuretrack methodological enquiries to the research team at

Futuretrack2006@warwick.ac.uk

Kate.Purcell@warwick.ac.uk