A new method to understand occupational gender segregation in European labour markets

A NEW METHOD TO UNDERSTAND OCCUPATIONAL GENDER SEGREGATION IN EUROPEAN LABOUR MARKETS

Brendan Burchell*, Vincent Hardy* Jill Rubery** and Mark Smith***

Advisory Committee on Equal Opportunities for Women and Men: Brussels, 22 May 2014

*University of Cambridge, ** University of Manchester *** Grenoble Ecole de Management

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Context• Segregation as the source of many inequalities on

the labour market [but not always negative for women.]

• Segregation occurs along various dimensions -- occupation, sector, public/private, workplace, etc

• Segregation is remarkably resistant to efforts to de-segregate.

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Why segregation matters … • segregation matters for gender inequality

– narrows employment choices and reinforces gender stereotypes– limit access to higher level jobs– Reflection of unequal division of unpaid work and family responsibilities– facilitates the undervaluation of women’s work– Protects women from male competition – Supply and demand side debates

– The big question: Is a women’s disadvantage in the labour market primarily because they are a woman, or because they do a woman’s job?

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Indicators … • Existing indicators capture only part of picture and

unable to disaggregate by other factors• Change in an indicator may be the result of a variety of

underlying trends• Indicators are sensitive to the coarseness of the measure

of occupations (eg pharmacists as one group or several)• The occupational classification schemes themselves are

the outcome of historical gendered power struggles and compromises to claim and value skills (thus finer gradations for male-dominated jobs than female jobs)

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Hierarchical Structure of ISCO88 (ISER)• Major group

– Sub-major group• Minor group

• Unit group

• 2 Professionals• 22 Life science and health professionals• 222 Health professionals (except nursing)• 2221 Medical Doctors• 2222 Dentists• 2223 Vetenarians etc• 223 Nurses and Midwives

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Gender Segregation Index for Occupations and Industry Sectors, EU27. Falling overall, but increasing in some countries

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Qualitative StudiesCase studies of occupations (eg Pharmacists, Clerks).

Change over longer time periods, WWII, technologies, gender legislation...

Effects of feminisation on structures, pay, TUs, etc

Case studies of employees, esp. as minorities (eg female construction trades, male midwives)

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Scotland's only male midwife: Dad David loves the job he has done for 25 yearsTHE 53-year-old dad worked as a miner before he decided to train and become a midwife.

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Under-representation of women by country and ISCO 1-digit

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Isco 2-digit by collar and gender mix in EU15 Source: EWCS 2005

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DatasetsTechnique first developed using 2010 European Working Conditions Survey

Current report based on Labour Force Survey, esp 2010 & 2005 (work-life balance ad hoc module), 2007 (risks)

Note: Attempts to capture and code a respondent’s occupation is a bit fuzzy; expect a lot of error

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Top occupations ISCO-88 by gender share and volume –EU26, 2010

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Example of Men’s advantage within each occupation: Supervising

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Different Occupations, Different Risks:

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Hours worked by full-timers. Both Women and Men benefit from shorter hours in female-dominated occupations

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Part-Time work for women is more prevalent in female-dominated occupations

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Examining international differences in occupational gender segregation

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High Stability in levels of segregation between 2005 and 2010.

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The Importance of the Public Sector for Women with Higher Education: EU-27, 2010

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Ratio of men and women’s pay to male average pay – EU-27, 2010

Women are paid less in almost all occupations.

Gap largest for Business and Admin Professionals and Health Professionals.

Reversed for two extreme male occupations.

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Ratio Cleaners and helpers’ female pay to average male pay, by country EU-27, 2010

Cleaners

Women in Low skilled occupations receive better pay in more equal countries – for example Cleaners and Helpers

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Ratio teaching professionals’ female pay to average male pay, by country EU-27, 2010

Teaching

Very different pattern for a high skill female-dominated occupation – eg teachers.

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Problems yet to be solved• 1 The transition between ISCO-88 and ISCO-08• 2 The policy-makers preference for a simple

measure: proportion of ‘Mixed jobs’ 40%-60% [a lumpy measure].

• 3 Integration of female labour market participation rates into the analyses.

• 4 Analysing several forms of gender segregation simultaneously (eg occupation and workplace).

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Last Comments…• Intuitive approach to complement other measures • …and frame analyses within occupations• Identification of impact of segregation– Gender effects within jobs (for example, supervision)– Gendering of occupations (for example working time)

• Tukey 1977 “Anything that makes a simpler description possible makes the description more easily handlable”.