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Paul Lambert 1 , David Griffiths 1 , Richard Zijdeman 2 , Ineke Maas 2 , Marco van Leeuwen 2

Comparing network and association models in the analysis of historical patterns of occupational interactions and stratification. Paul Lambert 1 , David Griffiths 1 , Richard Zijdeman 2 , Ineke Maas 2 , Marco van Leeuwen 2

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Paul Lambert 1 , David Griffiths 1 , Richard Zijdeman 2 , Ineke Maas 2 , Marco van Leeuwen 2

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  1. Comparing network and association models in the analysis of historical patterns of occupational interactions and stratification Paul Lambert1, David Griffiths1, Richard Zijdeman2, Ineke Maas2, Marco van Leeuwen2 Paper presented to the European Social Science History Conference, 11-14 April 2012, University of Glasgow, UK University of Stirling, UK, contact email: paul.lambert@stirling.ac.uk University of Utrecht, Netherlands

  2. Motivation • Studying social interactions and social connections can help us to understand social trends and transformations • Social mobility; homogamy; industrialisation; etc • Taking full advantage of historical occupational codes, new data, and new analytical opportunities • HISCO/NAPPHISCO/Microclass standardised codes… • …capture fine-grained details, but potentially aggregate some occupations by sector rather than level • GB 1831 census “..occupational returns as ‘crude, undigested, and essentially unscientific’, a document ‘whose insufficiency is a national disgrace to us, for there the trading and working classes are all jumbled together in the most perplexing confusion, and the occupations classified in a manner that would shame the merest tyro’” [Thompson 1963: 25, citing Mayhew 1862]

  3. What’s new? 1) Data resources • Census returns with household sharers’ occupations as proxy for social distance 2) Occupational coding Originally in NAPP/PUMS codes (NAPPHISCO, or national unit) (Approximate) recode into HISCO R Zijdeman; www.geode.stir.ac.uk (Approximate) recode into ‘Microclass’ D Griffiths; www.geode.stir.ac.uk ‘Microclass’ (Weeden and Grusky 2005; Jonsson et al. 2009) – socially defined fine-grained occupational clusters

  4. Data sources

  5. Preliminary versions – contemporary microclasses a convenient way to measure and analysis fine-grained historical detail?

  6. What’s new? 3) Methods for analysing {within-household} social connections on large-scale and fine-grained data …Focus on the individual outcome.. • Model with occupation-based indicators (plus random or fixed effects) …Focus on the social connection.. • Association models • HISCAM (Lambert et al. 2012) • Chan (2010) on ‘status’ scales • Network analysis • ‘SONOCS’ (Griffiths & Lambert 2011) • Cf. Wellman & Berkowitz (1988) Characterise dimensions to the occupational interaction structure Identify particular ‘routes’ of occupational connects

  7. Microclasses

  8. Microclasses

  9. Microclasses

  10. Microclasses

  11. HISCO units

  12. What can we do with such data? • Statistical models of occupation-based outcomes • Statistical models of the association process • Network depictions of prevalence of connections

  13. (a) Model individual outcomes: Linear/random/fixed effects

  14. (b) Association models‘Cambridge Social Interaction and Stratification Scales’ Seewww.camsis.stir.ac.uk/hiscam & Lambert et al. (2012) for historical data e.g.s • Social Interaction Distance (‘SID’) analysis • RC(II) model / Correspondence analysis • First dimension of association can usually be labelled as ‘stratification’

  15. How to use SID analysis effectively..? • Carefully prepared specific analysis… • ..or semi-automated comparisons? • Fine- v’s coarse-grained analysis? • Scales scores can indicate change in occupations through context • Model fit statistics allow study of trends/structures

  16. Main contribution of association models are to tell us about average social positions of the incumbents of occupations (and change over societies)

  17. c) Network analysis Still looking at number of connections {within household} but change in emphasis on features of connections Note, for Canada and Scotland closeness centrality refers to largest component only.

  18. Canada 1881 Norway 1876 Microclasses with ties *2 expected + non-sparse; male-male links if >16yrs age gap Scotland 1881 USA 1880

  19. Scotland 1881 Lawyers (1101), medics (1102), teachers (1304) and the clergy (1310) form a clique at centre of the network Clerks (3203) and agents (3102) interact with various professionals Librarians (1305) and creative artists (1306) with links to printers (4104) and craftsmen Housekeepers (4310) Managers (1202) and ships’ officers (1307) link to their subordinates (4306) Farming community (5201, 5202), forestry workers (4210) and gardeners (4312)

  20. Canada 1881 Clerical and sales workers (3***) strongly interact, but few ties to professionals (1***) Ties not as obvious; sparse connections within mesoclasses, but stratification effects most observable Teachers (1304), clergy (1310), lawyers (1101) and medics (1102) have sparse ties Housekeepers (4310) Farmers (5201) and farm labourers (5202) do not have mutual ties to forestry workers Food service workers (4304) are the ‘sons’ of many other routine workers Librarians (1305) and creative artists (1306) don’t form any strong ties and aren’t represented

  21. Canada 1881 (left) with microclasses split by religion (red=catholic; white=non-catholic). Clear division on religious grounds in 1881. Canada 1891 (right) with microclasses split by religion (red=catholic; white=non-catholic). Religious divide continues, but much more common for cross-religion and microclass households.

  22. Summary: Social connections between occupations • Connections are central to social organisation of the stratification system [e.g. Bottero 2005] • Problems of data preparation and scale • Occupational coding – NAPP; HISCO; Microclass • Identify social connections (within hhld NAPP) • Select/discard some types of connections (e.g. farming) • Analytical approaches • Model with proxy indicators, random or fixed effects …Focus on the social connection.. • Association models • Network analysis

  23. References cited • Bottero, W. (2005). Stratification: Social Division and Inequality. London: Routledge. • Griffiths, D., & Lambert, P. S. (2011). Dimensions and Boundaries: Comparative analysis of occupational structures using social network and social interaction distance analysis Paper presented at the ISA RC28 Spring meeting, University of Essex, 13-16 April 2011. • Jonsson, J. O., Grusky, D. B., Di Carlo, M., Pollak, R., & Brinton, M. C. (2009). Microclass Mobility: Social Reproduction in Four Countries. American Journal of Sociology, 114(4), 977-1036. • Lambert, P. S., Zijdeman, R. L., Maas, I., van Leeuwen, M. H. D., & Prandy, K. (2012). The construction of HISCAM: A stratification scale based on social interactions for historical research. Historical Methods, forthcoming. • Mayhew, H. (1862) London Labour and the London Poor. • Thompson, E. P. (1980[1963]). The Making of25 the English Working Class. London: Penguin. • Weeden, K. A., & Grusky, D. B. (2005). The Case for a New Class Map. American Journal of Sociology, 111(1), 141-212. Data from: • Minnesota Population Center. (2011). Integrated Public Use Microdata Series, International: Version 6.1 [Machine readable database]. Minneapolis: University of Minnesota, and https://international.ipums.org/ (accessed 1 July 2011). • 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]

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