Concepts and Measures: Empirical Evidence on the interpretation of ESeC and other occupation-based social classificatio

1. Concepts and Measures: Empirical Evidence on the interpretation of ESeC and other occupation-based social classifications Paul Lambert University of Stirling Erik Bihagen University of Stockholm Paper presented to Social Stratification Research Seminar, Stirling 5-7 September 2007 Stratification - Stirling 2007

2. Summary: occupation-based social classifications Sensible taxonomies can rarely be judged true or false, only more or less useful for a given purpose [Mills & Evans, 2003:80] • Relevance of reviewing lots of schemes • (1) Broad concordance of most measures • (2) Optimum measures are ambiguous • (1) Lots of overlap in conceptual correlates • (3) A small residual difference does reflect concepts [EGP]...has a clear theoretical basis, therefore differences between groups in health outcomes can be attributed to the specific employment relations that characterise each group[Shaw et al., 2007:78] Stratification - Stirling 2007

3. This review • Relationships between concepts and measures • Properties of various contemporary occupation-based social classifications • via SOC90 / NYK/ ISCO88 and employment status • ESeC [Rose and Harrison 2007] • European Socio-Economic Classification • High degree of replicability • Empirical validation / criterion validity • Standardisation / consistency / widespread use • Theoretical integration (with EGP) Compare with unemployment [Elias & McKnight 2003; Chan & Goldthorpe 2007; Schizzerotto et al 2007] Stratification - Stirling 2007

4. Class 1: Large employers, higher grade professional, administrative and managerial occupations: 'the higher salariat' • Class 2: Lower grade professional, administrative and managerial occupations: higher grade technician and supervisory occupations: 'the lower salariat' • Class 3: Intermediate occupations: 'higher grade white collar workers' • Classes 4 and 5: Small employers and self-employed in non-professional occupations: 'petit-bourgeoisie or independents' • Class 6: Lower supervisory and lower technician occupations: 'higher grade blue collar workers' • Class 7: Lower services, sales and clerical occupations: 'lower grade white collar workers' • Class 8: Lower technical occupations: 'skilled workers' • Class 9: Routine occupations: 'semi- and unskilled workers' • Class 10: Never worked and long-term unemployed: 'unemployed' • The non-employed • Six, five and three class models Stratification - Stirling 2007

5. Britain 1991-2002 BHPS 1991, 4537 adults 23-55yrs in work 2710 adults observed every year till 2002 Sweden 1991-2002 LNU 1991, 2538 adults 23-55yrs in work Linked to PRESO administrative data until 2002 [Tomas Korpi] Micro-data Stratification - Stirling 2007

6. Reviewing occupation-based social classifications? • GEODE – Grid Enabled Occupational Data Environment, www.geode.stir.ac.uk • [e.g. Lambert et al 2007, International Journal of Digital Curation] Stratification - Stirling 2007

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8. => 31 Occupation-based social classifications Stratification - Stirling 2007

9. Results: Concepts and measures • Broad concordance of schemes • Ambiguity of optimal schemes • Some residual differences do reflect conceptual origins Stratification - Stirling 2007

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13. Results: Concepts and measures • Broad concordance of schemes • Measures mostly measure the same thing • Generalised concepts are better • Criterion validity is asymmetric [cf. Tahlin 2007] • Ambiguity of optimal schemes • Some residual differences do reflect conceptual origins Stratification - Stirling 2007

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15. Results: Concepts and measures • Broad concordance of schemes • Ambiguity of optimal schemes • Balancing explanatory power and parsimony • No schemes stand out as substantially stronger • ESeC & EGP 3- and 2-class versions limited • AWM favourable in Sweden • Some residual differences do reflect conceptual origins Stratification - Stirling 2007

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17. EGP cf. CAMSIS – critical individuals Stratification - Stirling 2007

18. Results: Concepts and measures • Broad concordance of schemes • Ambiguity of optimal schemes • Some residual differences do seem to reflect conceptual origins • Differences between schemes diminish but don’t vanish • G11 in Br explains more Unemp. [as Chan & Goldthorpe 2007] • E9 in Sweden explains more Unemp. • ??Are empirical differences due to (the concepts / employment relations of) certain specific occ.s Stratification - Stirling 2007

19. Conclusions • Do measures measure concepts? • Yes (sometimes) – criterion validity • No (not uniquely) • How should we choose between measures? • Practical issues • Conceptual assumptions – generalised schemes • What about ESeC? • Few clear strengths in empirical properties • Practical advantages if widely used Stratification - Stirling 2007

20. References • Chan, T. W., & Goldthorpe, J. H. (2007). Class and Status: The Conceptual Distinction and its Empirical Relevance. American Sociological Review, 72, 512-532. • Elias, P., & McKnight, A. (2003). Earnings, Unemployment and the NS-SEC. In D. Rose & D. J. Pevalin (Eds.), A Researcher's Guide to the National Statistics Socio-Economic Classification. London: Sage. • Goldthorpe, J. H., & McKnight, A. (2006). The Economic Basis of Social Class. In S. L. Morgan, D. B. Grusky & G. S. Fields (Eds.), Mobility and Inequality. Stanford: Stanford University Press. • Lambert, P. S., Tan, K. L. L., Turner, K. J., Gayle, V., Prandy, K., & Sinnott, R. O. (2007). Data Curation Standards and Social Science Occupational Information Resources. International Journal of Digital Curation, 2(1), 73-91. • Mills, C., & Evans, G. (2003). Employment Relations, Employment Conditions and the NS-SEC. In D. Rose & D. J. Pevalin (Eds.), A Researchers Guide to the National Statistics Socio-economic Classification (pp. 77-106). London: Sage. • Rose, D., & Harrison, E. (2007). The European Socio-economic Classification: A New Social Class Scheme for Comparative European Research. European Societies, 9(3), 459-490. • Schizzerotto, A., Barone, R., & Arosio, L. (2006). Unemployment risks in four European countries: an attempt of testing the construct validity of the ESeC scheme. Bled, Slovenia, and http://www.iser.essex.ac.uk/esec/: Paper presented to the Workshop on the Application of ESeC within the European Union and Candidate Countries, 29-30 June 2006. • Shaw, M., Galobardes, B., Lawlor, D. A., Lynch, J., Wheeler, B., & Davey Smith, G. (2007). The Handbook of Inequality and Socioeconomic Position: Concepts and Measures. Bristol: Policy Press. • Tahlin, M. (forthcoming). Class Clues. European Sociological Review. Stratification - Stirling 2007

21. Appendices Stratification - Stirling 2007

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23. Background – handling occupational data[e.g. Lambert et al 2007, International Journal of Digital Curation] Model is: • Record and preserve ‘source’ occupational data (i.e OUG) • Use a transparent translation code to derive occupation-based social classifications Challenges include: • Locating occupational information resources http://home.fsw.vu.nl/~ganzeboom/pisa/ http://www.iser.essex.ac.uk/esec/consort/matrices/ • Large volumes of data (country; time; updates) • Detail on occupational index units (OUGs) • Gaps in working practices (software; NSI’s v’s academics) • ESeC has many attractive features: well documented scheme with ‘criterion validity’; transparent access in SPSS; wide adoption likely Stratification - Stirling 2007

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