1. Lambert/Griffiths, BSA, April 2010 1 Social Networks and Occupational Structure http://www.camsis.stir.ac.uk/ http://www.camsis.stir.ac.uk/ Paul Lambert and Dave GriffithsUniversity of Stirling

2. Lambert/Griffiths, BSA, April 20102 Analysis of personal connections between occupations helps us to understand both the structure of social stratification, and the mechanisms by which it is generated/sustained (1) Broad stability in occupational orders (Treiman constant) [Treiman, 1977], but some interesting change across countries/time [Lambert et al., 2008] –..changes across contexts which effect social relations of occupations include.. Occupational segregation by gender (and ethnic group) Educational expansion & industrial restructuring Changing institutions (e.g. key linking occupations) –..can study social positions of occupations (revealed by personal connections), not their objective qualities [e.g. Bottero et al., 2009, cf. Rose and Harrison, 2010] Occupations, stratification, & personal networks

3. Analysis of personal connections between occupations helps us to understand both the structure of social stratification, and the mechanisms by which it is generated/sustained (2) Exploring interpersonal inheritance in occupations and in stratification advantage/disadvantage –Strong empirical trends of occupational homogamy/endogamy [Brynin et al., 2008] and inter- and intra-generational stability [e.g. Breen, 2004] –The principle of kinship [Young, 1958] Share socio-economic resources: parents/children; spouses; wider family connections; friends Lifelong values and aspirations [e.g. Devine, 2004] Parents use their networks to help their children find work [Jaeger and Holm, 2007] Lambert/Griffiths, BSA, April 2010 3

4. Data on occupations and personal networks is abundant… Social Status in Great Britain (1974) Lambert/Griffiths, BSA, April 20104

5. ..friendship data.. University of Oxford, & Oxford Social Mobility Group (1978). Social Mobility Inquiry, 1972 [computer file]. Colchester, Essex: UK Data Archive [distributor], SN: 1097. Blackburn, R. M., Stewart, A., & Prandy, K. (1980). Social Status in Great Britain, 1974 [computer file]. Colchester, Essex: UK Data Archive [distributor], SN: 1369. University of Essex, & Institute for Social and Economic Research. (2009). British Household Panel Survey: Waves 1-17, 1991-2008 [computer file], 5th Edition. Colchester, Essex: UK Data Archive [distributor], March 2009, SN 5151. Lambert/Griffiths, BSA, April 20105

6. ..family connections data.. Lambert/Griffiths, BSA, April 20106

7. Complex survey designs measure various connected occupations (e.g. BHPS indvs/hhlds over time) Connections between multiple interviewed adults (e.g. previously co- resident siblings now living apart) All interviewed adults also give retrospective data on their parents occupations and their best friends occupations Lambert/Griffiths, BSA, April 20107..family connections data.. [Lambert and Gayle, 2008] ->

8. Lambert/Griffiths, BSA, April 2010 8 Methods to explore occupational structure 1)Social Interaction Distance analysis of occupations 2)Social network analysis of occupations

9. Lambert/Griffiths, BSA, April 20109 Part 1: CAMSIS, www.camsis.stir.ac.ukwww.camsis.stir.ac.uk Lays out a methodology for analysing social interaction for the purpose of social stratification research Analyse pairs of occupations linked by a social interaction (marriage; friendship; inter- and intra- generational connections) Use correspondence analysis (SPSS; Stata) or RC-II association models (Stata; lEM) on pairs of occupations Tradition of specificity: makes an empirical calculation within a context (country; time period)

10. 10 Derived scores predict frequency of interactions (#cases per cell) The scales describe one or more dimensions of a structure of social interaction… …this turns out to also represent a structure of social stratification… …resulting in scale scores which measure an occupations relative position within the structure of stratification. Husbands Job Units Occ Units 12..407 Derived scores 75.070.0..10.0 Wifes 1 72.0 3015..0 Job 2 72.5 13170..1 Units.. 407 11.0 02..80

11. Lambert/Griffiths, BSA, April 201011

13. Lambert/Griffiths, BSA, April 201013 Contributions: Social interaction distance and occupations CAMSIS is a Social Interaction Distance analysis –Homophily –The reproduction of social inequality is both exemplified by, and sustained through, social interactions [Bottero et al. 2009; Stewart et al. 1980] Explores the overall empirical structure of stratification and social inequality (probabilistic; prevalence) ?..but there are other influences on interaction (pseudo-diagonals).. Provides a potential measure of stratification position (there are plenty others..!)

14. Lambert/Griffiths, BSA, April 2010 14 2) A social network analysis of occupations The same data on {pairs of} connections between occupations could be analysed as network links Without any controls, most occupations will have at least one connection with most others in a large dataset We have begun to explore criteria which define whether occupational connections occur more often than would be expected given their national prevelance (i.e. at least r times more often)

15. Lambert/Griffiths, BSA, April 201015 Methodology We dont know of other applications of network analysis to explore large- scale patterns of occupational connections Cf. studies of using personal networks to obtain employment [Bartus 2000] Preliminary evaluations on data on marriage/cohabitation or friendship pairings taken from five surveys Occupational Unit Group codes (OUGs) available for each individual ego/alter = the respondent / their partner or friend An expectation ratio created for each combination of occupations –Number of actual relationships cf. expected number, produces an r value –i.e., if there were 15 instances of a male banker being married to a female baker, but we only expect 10 such partnerships given the numbers of people in those occupations by gender, the ratio would be 15/10, therefore r=1.5 –In general, r > 2 starts to show revealing patterns of occupational connections –To avoid the over-representation of smaller occupations which might find a single combination being much greater than expected, only combinations occurring at least two times are used

16. Lambert/Griffiths, BSA, April 201016 Scotland (marriage), 1881, r>2 Evidence of network structure (honestly!) There is a core- periphery structure. There is a single node, female domestic indoor servants, with a high number of ties. (arrows show male OUG married to female OUG) Female domestic servants Schoolmaster Coal miner

17. UK (friendship), 1970s, r>3 Lambert/Griffiths, BSA, April 201017 This network explores male friendship patterns There is a core- periphery structure, with a node on the right providing many links (clerks). Similar patterns, examining different relationships, nearly a century apart. Clerks, cashiers Primary/secondary school teachers Underground miners

18. Lambert/Griffiths, BSA, April 201018 USA (marriage), 2000, r>2 Lighter nodes are in the top quarter of CAMSIS. Darker nodes are lowest quarter. A divided structure with two clusters is evident, based around CAMSIS scores. Evidence of members of different OUGs moving in differing social circles.

19. Lambert/Griffiths, BSA, April 201019 USA (marriage), 2000, r>2, core only The K-core shows the greatest number of mutual ties in the network. Each of these are connected to at least 48 other OUGS. The divided structure is more evident. Occupations are heavily bonded but within different circles. Evidence of key linking occupations relevant to social reproduction? Painting workers Extruding, forming, pressing, and compacting machine setters, operators and tenders Sales and related workers (not elsewhere classified) Inspectors, testers, sorters, samplers and weighers Industrial workers (including health and safety) Artists and related workers

20. 20 Scotland (marriage), 1881, r>4 A comparable core pattern to contemporary USA, but farmers seem to be key linking occupations in 1881 Scotland? Lambert/Griffiths, BSA, April 2010

21. 21 SNA methodological issues Data-oriented options –Different occupational linkages (multiple friendships; data subsets; etc) –Education-Occupational combinations –Different expectation ratio definitions (e.g. recognising stratification) Triad census [Moody, 1998] –Counting number of connections between OUGS, e.g. to understand how the most/least advantaged occs interact with other occupations QAP (Quadratic Assignment Procedure) –[Krackhardt, 1988] –regression analysis to explore influences on whether occupations are linked (e.g. occupational characteristics) Longitudinal analysis –[Snijders 2005] – compare network structures over time to explore social change and contours of social connections UK 1970s to 1990s: increase in same occupational friendships (2.5% to 5.5% in same SOC), but so far no major change evident in wider occupational networks

22. Summary and plans (project 2010-2012) Generating new social interaction distance scales –Updating existing resources at www.camsis.stir.ac.ukwww.camsis.stir.ac.uk –Refining / promoting methodological resources make_camsis.do Improved understanding of pseudo-diagonals Social network analysis of occupational connections –Numerous emergent issues to explore/interpret.… –Generating new methodological resources on suitable SNA techniques Lambert/Griffiths, BSA, April 201022

23. References Bartus, T. (2000) Fitting Social Capital, Informal Job Search, and Labor Market Outcomes in Hungary. Connections, 23 (1), 72-83. Bottero, W., Lambert, P. S., Prandy, K., & McTaggart, S. (2009). Occupational Structures: The Stratification Space of Social Interaction. In K. Robson & C. Sanders (Eds.), Quantifying Theory: Pierre Bourdieu (pp. 141-150). Amsterdam: Springer Netherlands. Breen, R. (Ed.). (2004). Social Mobility in Europe. Oxford: Oxford Univeristy Press. Brynin, M., Longhi, S., & Martinez Perez, A. (2008). The Social Significance of Homogamy. In M. Brynin & J. Ermisch (Eds.), Changing Relationships. London: Routledge. Devine, F. (2004). Class Practices: How parents help their children get good jobs. Cambridge: Cambridge University Press. Krackhardt, D. (1988) Predicting with networks: Nonparametric multiple regression analysis of dyadic data, Social Networks, 10, 359-381. Lambert, P. S., & Gayle, V. (2008). Individuals in Household Panels: The importance of person-group clustering. Naples: ISA RC33 7th International Conference on Social Science Methodology, & www.longitudinal.stir.ac.uk/bhps/.www.longitudinal.stir.ac.uk/bhps/ Lambert, P. S., Tan, K. L. L., Gayle, V., Prandy, K., & Bergman, M. M. (2008). The importance of specificity in occupation-based social classifications. International Journal of Sociology and Social Policy, 28(5/6), 179-192. Minnesota Population Center. (2009). Integrated Public Use Microdata Series - International: Version 5.0. Minneapolis: University of Minnesota. Moody, J. (1998) Matrix Methods for calculating the triad census, Social Networks, 20 (4), 291-299. North Atlantic Population Project and Minnesota Population Center. (2008). NAPP: Complete Count Microdata. NAPP Version 2.0 [computer files]. Minneapolis, MN: Minnesota Population Center [distributor] [http://www.nappdata.org] Prandy, K., & Bottero, W. (1998). The use of marriage data to measure the social order in nineteenth-century Britain. Sociological Research Online, 3(1), U43-U54. Prandy, K., & Bottero, W. (2000). Reproduction within and between generations - The example of nineteenth-century Britain. Historical Methods, 33(1), 4-15. Rose, D., & Harrison, E. (Eds.). (2010). Social Class in Europe: An Introduction to the European Socio-economic Classification London: Routledge. Snijders, T.A.B. (2009) Longitudinal Methodsd of Network Analysis in Meyers, R.A. (ed) Encyclopedia of Complexity and System Science, Springer Verlag. Stewart, A., Prandy, K., & Blackburn, R. M. (1980). Social Stratification and Occupations. London: MacMillan. Treiman, D. J. (1977). Occupational Prestige in Comparative Perspective. New York: Academic Press. Young, M. (1958). The Rise of the Meritocracy 1870-2033. Harmondsworth: Penguin.