Measuring occupational sex segregation

1. Measuring occupational sex segregation Stephanie Steinmetz (UvA) InGRID expert workshop 11 February 2014

2. What is occupational sex segregation and why is it important?

3. Women & men work in different types of occupations and at different occupational levels !

4. Why is this of interest? Last decades an increasing participation of women • in education + on the labour market But,women still predominantly choose • typical female fields of study + typical female occupations And they are still underrepresented in high status positions  Persistent & universal phenomen in most industrialised societies  Leads to gender inequalities with respect to income, power etc.

5. Policy level – Equality measure • Degree/level of occupational sex segregation provides information on • how unequal the distribution of men and women across occupations and positions is, • how men and women are integrated in the workplace, and • how separated they are by the work they do. • Used as an ‘gender equality measure’… … for designing, evaluating & monitoring employment+social programmes as well as policies!

6. Occupational gender typing(ESS 2012, ISCO08-1)

7. Occupational concentration (ESS, 2012 / ISCO-3) ~25% of employed women concentrated in five occupations

8. Measuring occupational sex segregation

9. Common indices • D = Index of Dissimilarity(Duncan & Duncan 1955) • Sex segregation = different distribution of women and men across occupations • D=0 (complete equality) and 1 (complete dissimilarity) • Proportion of women & men who would need to change jobs in order to remove segregation

10. Alternative measures • Dst= Standardized Index of Dissimilarity (Gibbs 1965)  not affectedby occupational size effects  should therefore measure ‘pure’ sex typing • IP index (Karmel & MacLachlan, 1988) reflects relative size of both sexes + accounts for male & female share of all employed persons  should not be sensitive to variations in female labor force share • Marginal Matching Index (MM)/Index of Segregation (IS) (Blackburn 1993)  measures changes over time resulting exclusively from changes in sex composition of occupations • Association Index (Charles & Grusky, 2004)  based on log-linear models • WE index (OECD, 1980) • SR= Sex-Ratio Index (Hakim, 1979)

11. Used for change over time - 1992-2007 Source: Bettio & Verashchagina, European Commission, 2009 11

12. Role of definitions & classifications • Underestimation of the crucial role of definitions and classifications in data production. • Determine • what is to be covered or not and with how much detail a variable will be described. • the quality of resulting figures. • how well they reflect the actual situation of the different participants in the labor market.

13. Determinants of segregation indices • ‘Gender blindness’ of occupational classifications  Aggregated occupational groups masks sex segregation Classifications do not adequately capture important labour market changes • Occupational classifications Inconsistency • Concept of ‘occupation’  Country-specific occupational classifications might follow different construction principles

14. Occupational classifications ‘Gender blindness’ • Classifications cover labour market developments with some delay • Important changes (e.g. service sector expansion) are not captured adequately (female-dominated sector) • Many new occupations evolve which are allocated to few & heterogeneous occupational groups. • Level of detail matters!

15. Occupational detail • Advantage of using disaggregated occupational data  broad occupational groups hide occupational sex segregation  impacts on the calculation of segregation indices (value of D declines with more aggregation  it appears that there is less segregation than there really is)  more detailed occupations reveal a more accurate picture of the actual work experience of men & women  only then can gender distinction be revealed

16. Which occupations are gendered? • Example: Major group 3 – professionals  ‘integrated’ • But: 4-digit level! Source: ESS 2012

17. Change of the Index of Dissimilarity 17

18. BUT… • …unfortunately, even very detailed occupational groups may hide occupations’ sex segregation! WHY? • Tasks & duties of the same occupation may vary between men and women. • Example: cleaning occupations (Messing, 1998) &sales occupations (Dixon-Muller, Anker 1990) • Female occupations tend to be considered too ‘general’,  multitude of tasks linked to general skills (literacy, numeracy & interpersonal contacts & traditional housekeeping activities)

19. Occupational classifications Problem: Changingfrom 1-digit to more disaggregated2-/3-digit levelsomeoccupations in group 7 obviouslyrequirehigherdegrees of skill & longer training thansome of theoccupationsclassified in group 5. • Problem of inconsistency ISCO-08

20. Concept / Measurement of ‘occupation’ • Different national & cultural contexts might create country-specific occupational classifications following different construction /measurement principles  are transferred into ISCO08 classification  how ‘genderblind’ are these different measures?

21. Conclusion • Occupational classifications should describe men & women’s work characteristics equally well and detailed. • Provision of additional ‘gender relevant’ (job) information (i.e. tasks and duties, skills etc.) providing insights into how sex segregation works within occupations. • Use of aggregated indices as a measure of equality to evaluate progress should be limited!

22. THANK YOU! • Questions? Comments? Contact: s.m.steinmetz@uva.nl