FEMINISM COUNTS: Quantitative Methods and Feminist Research 7th November 2008, University of Warwick

Research as evidence: understanding the world in order to change it

Kate PurcellInstitute for Employment Research, University of Warwick

What I’m going to talk about

• A little bit of biography; where I’m coming from epistemologically, ontologically and methodologically;

• Feminism and doing research that provides evidence to inform policy and practice;

• The importance of measuring, counting and mapping inequalities and differences;

• Higher education expansion;• Occupational change;• Careers;• The power of mixed methods research.

Background: the personal is political – research evolution over the last 30 years

• Methodologically: policy-related quantitative research – ethnography – economic sociology

• Industrial relations /industrial sociology/ FEMINISM / gender at work/ Labour market change/ Economic and organisational restructuring /occupational change

• Gender inequalities in employment and careers• The implications of HE expansion on labour market

change• Participation in HE, subject choices and the

'Knowledge Economy’• Higher education, partnership and family formation

Feminist methodology?

• Critical - of concepts, definitions and categories;• Reflexive;• Concerned to minimise power relativities –

particularly between researchers and researched;• ‘Real world research’ and eclectic – interested in ALL

evidence;• Politically informed and engaged.

Data sources and methods drawn on

• National administrative data sources (e.g. Universities and Colleges Admissions Service, Censuses of Population and Labour Force Survey data

• Longitudinal graduate surveys (1995 graduates recontacted in 1998/9, 2002/03 and 2005, 1999 graduates surveyed in 2003-4 and first sweep of new 2006 higher education applicant census)

• Follow-up qualitative interviews with sub-samples of respondents

(See www.warwick.ac.uk/go/glmf for details)

Participation by young people in Higher Education, Age Participation Index (API) GB 1961 to 2006

0

5

10

15

20

25

30

35

40

Source: Elias and Purcell (2007)

API (

%)

Students in higher education: by type of course and gender (UK, 1970/71 – 2000/01)

Thousands

Undergraduate Postgraduate

Full time Part time Full time Part time

All in higher education

Males

1970/71 241 127 33 15 416

1980/81 277 176 41 32 526

1990/91 345 193 50 50 638

2000/01 511 228 82 118 940 Change 1970/71 – 2000/01 212% 180% 248% 787% 226%

Females

1970/71 173 19 10 3 205

1980/81 196 71 21 13 301

1990/91 319 148 34 36 537

2000/01 602 320 81 124 1,128 Change 1970/71 – 2000/01 348% 1684% 810% 4133% 550% Notes: 1 Home and overseas students.

2 At December each year. Includes Open University. Sources: Department for Education and Skills; National Assembly for Wales; Scottish Executive;

Northern Ireland Department for Employment and Learning.

Why?• Human capital – in particular, university-educated labour – is

increasingly regarded as crucial to economic development and competitiveness– 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– 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.

• Change in sexual division of labour and global concern with the eradication inequalities.

UCAS tariff points by gender

Self-assessment of key skills prior to HE entry, by gender

0

10

20

30

40

50

60

70

80

90

100

Male Female Male Female Male Female Male Female Male Female

WRITTEN COMMUNICATION

SPOKEN COMMUNICATION

NUMERACY COMPUTER LITERACY SELF-CONFIDENCE

Excellent Very good Good

Self-rated excellent or very good self-confidence, by ethnic origin and gender

Ethnic origin High self confidence rating (%)

Males FemalesAsian

Bangladeshi 64 58Chinese 44 34Indian 62 51Pakistani 63 54Other 67 53

BlackAfrican 76 66Caribbean 72 57Other 70 57

White 51 40Mixed 56 48

Total 54 43

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

Source: Futuretrack Stage 1 survey (2006)

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

Proportions of applicants opting for selected subjects, by gender

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

Achievement at first degree level by sex: UK, 2005/06

Average annual gross earnings of 1995 graduates by gender

The combined effects of various factors on the gender difference in annual earnings of 1995 graduates seven

years after graduation

0 2 4 6 8 10 12 14 16 18 20

Residual gender difference

Adjusted for weekly hours,sectors and workplace

segmentation

Adjusted for weekly hours andsector

Adjusted for weekly hours

Unadjusted gender difference

% difference between female annual gross earnings and male annual gross earnings

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

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)

We have taken economic theory and econometric techniques as far as we can, yet there are still unexplained inequalities in earnings and career outcomes.

•AND OUTCOMES (-EVEN REWARDS FROM WORK) ARE NOT JUST EARNINGS;•AND OTHER DIFFERENCES CAN BE COUNTED…..

Qualitative research (oral accounts of work histories, reasons given for decisions taken and accounts of employment experiences) indicate:

• different contributory factors in different work contexts• the importance of partnership and fertility intentions• the importance of public versus private employment experiences• the role of values and motivations• social background, cultural capital and self-confidence as contributory factors

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)

The SOC(HE) classification*

• Traditional graduate occupations

• Modern graduate occupations

• New graduate occupations

• Niche graduate occupations

• Non-graduate occupations

*See Elias and Purcell 2004 NIER article (on IER website)

0

5

10

15

20

25

30

35

40

1980 2000 1980 2000

Females Males

Traditional graduate job Modern graduate job

New graduate job Niche graduate job

The changing structure of graduate occupations in the UK, 1980 - 2000

Source: New Earnings Survey Panel Dataset 1975-2000

Use of skill clusters in current jobs by SOC(HE)

0

1

2

3

4

5

6

7

8

9

TraditionalGraduate Job

ModernGraduate Job

New GraduateJob

Niche GraduateJob

Non-graduateJob

Mea

n sc

ore

(out

of 1

0)

Expertise

Strategic & Managerial Skills

Interactive Skills

Source: Graduate Careers 7 Years On transcribed follow-up interview data ( 201 respondents)

 

Employment change

93-06 % with degree % female

Graduate premium

(%)

Average female graduate

earnings as a % males

(gender pay gap)

93-94 04-06 93-94 04-06 93-94 04-06 93-94 04-6

New graduate occupations 41 60 36 43 19 23 83 79

Marketing, sales managers Growth 33 53 39 39 26 20 78 84

Personnel, training etc managers Strong growth 40 56 57 65 48 40 79 86

Chartered & certified accountants Declining 47 80 30 42 16 4 82 81

Laboratory technicians Growth 40 60 38 49 22 18 108 90

Niche graduate occupations 17 35 38 43 24 28 85 76

Nurses Stable 5 34 86 83 -2 9 105 99

Artists, graphic designers etc Growth 27 48 31 41 0 -4 81 89

Police officers - sergeant & below Stable 8 24 13 30 -1 -3 80 94

Non graduate occupations 4 10 35 37 21 14 94 87

Vocational, industrial trainers Strong growth 18 35 39 55 -56 19 135 107

Accounts clerks, book-keepers etc Declining 11 22 71 68 40 33 82 88

Sales assistants Stable 5 11 56 45 20 10 89 106

All occupations 19 35 36 41 41 47 84 81

New graduate occupations 41 60 36 43 19 23 83 79

Within which:

Marketing, sales managers Growth 33 53 39 39 26 20 78 84

Personnel, training etc managers Strong growth 40 56 57 65 48 40 79 86

Chartered & certified accountants Declining 47 80 30 42 16 4 82 81

Laboratory technicians Growth 40 60 38 49 22 18 108 90

Declining

Niche graduate occupations 17 35 38 43 24 28 85 76

Within which:

Nurses Stable 5 34 86 83 -2 9 105 99

Artists, graphic designers etc Growth 27 48 31 41 0 -4 81 89

Police officers - sergeant & below Stable 8 24 13 30 -1 -3 80 94

Non graduate occupations 4 10 35 37 21 14 94 87

Within which:

Vocational, industrial trainers Strong growth 18 35 39 55 -56 19 135 107

Accounts clerks, book-keepers etc Declining 11 22 71 68 40 33 82 88

Sales assistants Stable 5 11 56 45 20 10 89 106

All occupations 19 35 36 41 41 47 84 81

Trends in the graduate labour market, by occupation, gender and earnings, 26-35 year olds in full-time jobs in 1993-94 and 2004-06

(Source: LFS data – plus ongoing work by Purcell and Elias, currently being revised for publication in 2009)

0

10

20

30

40

50

60

70

80

90

100

Male Female

% r

espondin

g a

ffirm

ativ

ely

Does not live with partner

Lives with partner

Partnership and careers 7 years after graduation:expectation of achieving a higher position within the next five

years

Source: Graduate Careers 7 Years On Survey

Significant quantitative research findings that don’t get talked about enough and rarely make headlines

• Higher education expansion has been disproportionately the increase of women’s HE participation

• Women more likely than men to participate in HE; and they achieve better results.

• But similarly-qualified female applicants to HE have lower chance of acceptance than males...

• And gendered outcomes include:• persistent and increasing gender pay gap as careers progress;• gender segmentation in graduate jobs;• lower reported female satisfaction with career development;• persistent under-representation of women in ‘top jobs’;• significantly lower fertility among female graduates (around one

third remaining childless at age 40).

The completion of motherhood: 22-26 year old women in 1981 by whether or not have had own children by

2001, by degree and occupation

Source: Longitudinal Census analysis (Purcell and Elias (2007 and work in progress)

Findings from quantitative analysis of 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• 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• Graduate women are more likely to be in ‘non-graduate’

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

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

BUT • Quantitative research: How many? How often? Which

categories? When? and How much? Do not explain enough: the big question WHY? remains.

Qualitative research (oral accounts of work histories, reasons given for decisions taken and accounts of

employment experiences) indicate:

• different contributory factors in different work contexts

• the importance of partnership and fertility intentions

• the importance of public versus private employment experiences

• the role of values and motivations

• social background, cultural capital and self-confidence as contributory factors.

The qualitative follow-up interviews• Women value high earnings less and having work of social value more

than men BUT similarities in career attitudes and expectations and may plan lifecycle careers rather than sequential careers;

• High-flying women, particularly those who want to have children, are coerced into or make different choices, report reduced bargaining power than male peers (- maternity leave, taking advantage of flexibility rights after childbirth, succumb to informal peer group pressures...)

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

• Most people do not make work choices and career decisions purely in terms of their individual interests: the notion of careers and employment choices as individual needs radical rethinking.

• Need to reconsider work group interconnections (– back to Kanter)!

Kate.Purcell@warwick.ac.uk

Some of the statistics cited in the presentation are not fully referenced or derive from ongoing work. Please do

not cite without permission.For further information and links relating to the research

drawn on for this presentation and IER’s wider programmes of higher education and labour market

research and related projects see also:

http://www2.warwick.ac.uk/fac/soc/ier/research/glmf