Lambert/Griffiths, BSA, April 2010 1 Social Networks and Occupational Structure Paul Lambert.

Lambert/Griffiths, BSA, April 2010

1

Social Networks and Occupational Structure

http://www.camsis.stir.ac.uk/

Paul Lambert and Dave Griffiths University of Stirling


Lambert/Griffiths, BSA, April 2010 2

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

Occupations, stratification, & personal networks

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]


3

Data on occupations and personal networks is abundant…

Social Status in Great Britain (1974)


..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.


41274 100.00 XX........XX.XXXX 7746 18.77 100.00 (other patterns) 1218 2.95 81.23 ..........11..... 1406 3.41 78.28 ..........1...... 1431 3.47 74.88 ................1 1531 3.71 71.41 .............11.. 3127 7.58 67.70 ...............11 4071 9.86 60.12 ..............111 5066 12.27 50.26 .1............... 5369 13.01 37.99 ..........11.1111 10309 24.98 24.98 1................ Freq. Percent Cum. Pattern*

..family connections data..


• 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


..family connections data..

[Lambert and Gayle, 2008] ->


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Methods to explore occupational structure

1) Social Interaction Distance analysis of occupations

2) Social network analysis of occupations


Part 1: CAMSIS, www.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)


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• 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 occupation’s relative position within the structure of stratification.

Husband’s Job Units

Occ Units ↓ → 1 2 .. 407

Derived scores ↓ → 75.0 70.0 .. 10.0

Wife’s 1 72.0 30 15 .. 0

Job 2 72.5 13 170 .. 1

Units .. .. .. .. .. ..

407 11.0 0 2 .. 80


1050

90

0/1Managers

andProfess.

2Education

andcommunity

3 Healthand

protectiveservices

4 Salesand

service

5 Officesupport

and admin

6Construction

andagriculture

7Technicians

8Production

9Transport

andmaterials

CAMSIS scores by broad occuaptional groups (USA 2000)

Male CAMSIS Male N Female CAMSIS Female N

Chief Executives

Managers, All Other

Sales Reps, Wholesale

Retail Sales Supervisors/Managers

Retail Salespersons

Construction Supervisors/ManagersCarpentersProduction Workers Supervisors/Managers Automotive Service TechniciansDrivers and Truck Drivers Janitors and Building Cleaners

Laborers and Movers

020

4060

80

CAMSIS scores for 475 occupations (male CAMSIS scale)

Source: IPUMS USA, 3% sample, and www.camsis.stir.ac.uk Panel 1: Occupational groups are first digit of US SOC2000. N is sample N / 3,000,000. Panel 2: Marker size is proportional to number in occupation. Labels show 15 most common occupations.

USA, 2000

11

1

1

1

1

1

1 1

1

11 11

11

1

1

1

1

11

1

1

1

1

1

1

1

1

11

1

11

11

11

1

11

11 11

-2-1

.5-1

-.5

0.5

1D

ime

nsio

n 2

(2

6.0%

)

-1 -.5 0 .5 1 1.5Dimension 1 (61.0%)

Male scores

Female scores

Correspondence analysis biplot

-.5 0 .5

23. Refuse Matters22. General or Unspecified Commodities

21. Mineral Substances20. Vegetable Substances

19. Animal Substances18. Dress

17. Textile Fabrics16. Food and Lodging

15. Tobacco and Pipes14. Chemicals and Compounds

13. Ships and Boats12. Carriages and Harnesses

11. House, Furniture and Decorations10. Dealers in Machines and Implements

9. Books, Prints, Maps8. Animals

7. Agriculture6. Conveyance of men, goods and messages

5. Commercial Occupations4. Domestic Service or Offices

3. Professionals2. Defence of the country

1. General/Local Government

CAMSIS scores by broad occuaptional groups

CAMSIS N/100000

Source: NAPP, N=598000 (Intra-household male-female occupational combinations). Panel 1: Dimension scores from correspondence analysis of intra-household occupations Panel 2: Mean scores for males by 'occupational order'.

Scotland, 1881

Figure 1: Illustration of SID scales

1050

90

0/1Managers

andProfess.

2Education

andcommunity

3 Healthand

protectiveservices

4 Salesand

service

5 Officesupport

and admin

6Construction

andagriculture

7Technicians

8Production

9Transport

andmaterials

CAMSIS scores by broad occuaptional groups (USA 2000)

Male CAMSIS Male N Female CAMSIS Female N

Chief Executives

Managers, All Other

Sales Reps, Wholesale

Retail Sales Supervisors/Managers

Retail Salespersons

Construction Supervisors/ManagersCarpentersProduction Workers Supervisors/Managers Automotive Service TechniciansDrivers and Truck Drivers Janitors and Building Cleaners

Laborers and Movers

020

4060

80

CAMSIS scores for 475 occupations (male CAMSIS scale)

Source: IPUMS USA, 3% sample, and www.camsis.stir.ac.uk Panel 1: Occupational groups are first digit of US SOC2000. N is sample N / 3,000,000. Panel 2: Marker size is proportional to number in occupation. Labels show 15 most common occupations.

USA, 2000

11

1

1

1

1

1

1 1

1

11 11

11

1

1

1

1

11

1

1

1

1

1

1

1

1

11

1

11

11

11

1

11

11 11

-2-1

.5-1

-.5

0.5

1D

ime

nsio

n 2

(2

6.0%

)

-1 -.5 0 .5 1 1.5Dimension 1 (61.0%)

Male scores

Female scores

Correspondence analysis biplot

-.5 0 .5

23. Refuse Matters22. General or Unspecified Commodities

21. Mineral Substances20. Vegetable Substances

19. Animal Substances18. Dress

17. Textile Fabrics16. Food and Lodging

15. Tobacco and Pipes14. Chemicals and Compounds

13. Ships and Boats12. Carriages and Harnesses

11. House, Furniture and Decorations10. Dealers in Machines and Implements

9. Books, Prints, Maps8. Animals

7. Agriculture6. Conveyance of men, goods and messages

5. Commercial Occupations4. Domestic Service or Offices

3. Professionals2. Defence of the country

1. General/Local Government

CAMSIS scores by broad occuaptional groups

CAMSIS N/100000

Source: NAPP, N=598000 (Intra-household male-female occupational combinations). Panel 1: Dimension scores from correspondence analysis of intra-household occupations Panel 2: Mean scores for males by 'occupational order'.

Scotland, 1881

Figure 1: Illustration of SID scales


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..!)


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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)


Methodology• We don’t 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 individualego/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


Scotland (marriage), 1881, r>2Evidence 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

UK (friendship), 1970’s, r>3


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


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.


USA (marriage), 2000, r>2, core onlyThe 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

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Scotland (marriage), 1881, r>4

A comparable core pattern to contemporary USA, but farmers seem to be key linking occupations in 1881 Scotland?



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 connectionsUK 1970’s to 1990’s: increase in same occupational friendships (2.5% to 5.5% in same

SOC), but so far no major change evident in wider occupational networks

Summary and plans (project 2010-2012)

• Generating new social interaction distance scales – Updating existing resources at www.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



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/.• 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.

http://www.longitudinal.stir.ac.uk/bhps/

Lambert/Griffiths, BSA, April 2010 1 Social Networks and Occupational Structure Paul Lambert.

Documents

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