Occupational marriage networks in the USA, 1970-2010

Dave Griffiths & Paul LambertSchool of Applied Social Science, University of Stirling

Paper presented to Social Stratification Research Seminar, 1 September 2011, University of Stirling

Work for this paper is supported by the ESRC as part of the project ‘Social Networks and Occupational Structure’, see

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

• Generating networks sociograms of the occupational structure

• Testing reliability of obtaining data from large-scale social surveys

• Initial results of mapping occupational structure using SNA methods

• Examine occupational categorisation schemes

% of Lawyers married to..

% of all working husbands married to..

CAMSIS score (US 2000)

Lawyers 11.6% 0.6% 81.5Primary school teachers 7.2% 4.5% 66.2Registered nurses 4.4% 4.5% 56.8Secretaries 3.8% 5.3% 55.5Preschool and kindergarten teachers 2.8% 1.2% 62.7Accountants and auditors 2.4% 1.8% 65.2Counsellors 2.4% 0.8% 65.0Paralegals and legal assistants 2.4% 0.5% 64.2Postsecondary teachers 2.4% 1.0% 79.8Managers 2.1% 1.8% 62.2Bookkeepers 2.1% 2.5% 53.1

% of Labourers married to…

% of all working husbands married to..

CAMSIS score (US 2000)

Registered nurses 3.9% 4.5% 56.8Nursing, psychiatric and home healing assistants

3.9% 1.9% 42.6

Secretaries 3.9% 5.3% 55.5Customer service representatives 3.6% 1.7% 51.8Receptionists 3.2% 1.6% 53.2Cashiers 3.2% 1.8% 41.3Labourers 2.9% 0.4% 32.0Janitors and building cleaners 2.5% 1.7% 32.5Maids and housekeeping cleaners 2.2% 0.3% 27.4Retail salespersons 2.2% 1.9% 51.9Tellers 2.2% 0.6% 46.3

Most common occupations for the wives of lawyers and labourers in the USA

Source: Current Population Survey 2010.

% of Lawyers married to..

% of all working husbands married to..

CAMSIS score (US 2000)

Lawyers 11.6% 0.6% 81.5Primary school teachers 7.2% 4.5% 66.2Registered nurses 4.4% 4.5% 56.8Secretaries 3.8% 5.3% 55.5Preschool and kindergarten teachers 2.8% 1.2% 62.7Accountants and auditors 2.4% 1.8% 65.2Counsellors 2.4% 0.8% 65.0Paralegals and legal assistants 2.4% 0.5% 64.2Postsecondary teachers 2.4% 1.0% 79.8Managers 2.1% 1.8% 62.2Bookkeepers 2.1% 2.5% 53.1

% of Labourers married to…

% of all working husbands married to..

CAMSIS score (US 2000)

Registered nurses 3.9% 4.5% 56.8Nursing, psychiatric and home healing assistants

3.9% 1.9% 42.6

Secretaries 3.9% 5.3% 55.5Customer service representatives 3.6% 1.7% 51.8Receptionists 3.2% 1.6% 53.2Cashiers 3.2% 1.8% 41.3Labourers 2.9% 0.4% 32.0Janitors and building cleaners 2.5% 1.7% 32.5Maids and housekeeping cleaners 2.2% 0.3% 27.4Retail salespersons 2.2% 1.9% 51.9Tellers 2.2% 0.6% 46.3

Most common occupations for the wives of lawyers and labourers in the USA

Source: Current Population Survey 2010.

www.camsis.stir.ac.uk/sonocs/do/pajek.do**create frequency datasetcapture drop freqgen freq = 1collapse (count) freq, by(hocc wocc)list in 1/20*****Find total for each categorycapture drop totegen tot=sum(freq)summarize tot*******Find totals for men and womencapture drop nhocccapture drop nwoccegen nhocc=sum(freq), by(hocc)egen nwocc=sum(freq), by(wocc)****Find percentage for each category for men and womencapture drop phocccapture drop pwoccgen phocc=nhocc/totgen pwocc=nwocc/totSummarize*******Calculate expected numbers of womencapture drop ewoccgen ewocc=pwocc*nhoccSummarize**************create expectation surpluscapture drop valuegen value=freq/ewocc************Create standard error predictionscapture drop propgen prop = freq/totcapture drop staner gen staner = sqrt((prop)*(1 - prop) / tot)list freq tot phocc pwocc ewocc value prop staner in 1/20

capture drop pro_obsgen pro_obs = freq/totcapture drop pro_expgen pro_exp = ewocc/totcapture drop pro_mingen pro_min = pro_obs – stanercapture drop pro_maxgen pro_max = pro_obs + stanercapture drop valuegen value = pro_obs / pro_expcapture drop val_mingen val_min = pro_min / pro_expcapture drop val_maxgen val_max = pro_max / pro_exp***label variableslabel variable tot "total number in sample"label variable nhocc "total number of males in occupation"label variable nwocc "total number of females in occupation"label variable phocc "percentage of men in occupation"label variable pwocc "percentage of women in occupation"label variable ewocc "expected number of partnerships"label variable staner "Standard error for tie"label variable pro_obs "Observed proportion of all ties"label variable pro_exp "Expected proportion of all ties"label variable pro_min "Lower confidence interval of observed proportion"label variable pro_max "Higher confidence interval of observed proportion"label variable value "Observed value of representation"label variable val_min "Value of representation for lower confidence interval"label variable val_max "Value of representation for higher confidence interval"

1101. Jurists1102. Health professionals

1103. Professors and instructors1104. Natural scientists

1105. Statistical and social scientists1106. Architects

1107. Accountants1108. Journalists, authors, and related writers

1109. Engineers1201. Officials, government and non-profit organizations

1202. Managers1203. Commercial Managers

1204. Building managers and proprietors1301. Systems analysts and programmers

1302. Aircraft pilots and navigators1303. Personnel and labor relations workers

1304. Elementary and secondary school teachers1305. Librarians

1306. Creative artists1307. Ship officers

1308. Professional, technical, and related workers, n.e.c.1309. Social and welfare workers

1310. Workers in religion1311. Nonmedical technicians

1312. Health semiprofessionals1313. Hospital attendants

1314. Nursery school teachers and aides3101. Real estate agents

3102. Other agents3103. Insurance agents

3104. Cashiers3105. Sales workers and shop assistants

3201. Telephone operators3202. Bookkeepers and related workers

3203. Office and clerical workers3204. Postal and mail distribution clerks

4101. Craftsmen and kindred workers, n.e.c.4102. Foremen

4103. Electronics service and repair workers4104. Printers and related workers

4105. Locomotive operators4106. Electricians

4107. Tailors and related workers4108. Vehicle mechanics

4109. Blacksmiths and machinists4110. Jewelers, opticians, and precious metal workers

4111. Other mechanics4112. Plumbers and pipe-fitters

4113. Cabinetmakers4114. Bakers

4115. Welders and related metal workers4116. Painters

4117. Butchers4118. Stationary engine operators

Bricklayers, carpenters & related4120. Heavy machine operators

4201. Truck drivers4202. Chemical processors

4203. Miners and related workers4205. Food processors

4206. Textile workers4207. Sawyers and lumber inspectors

4208. Metal processors4209. Operatives and kindred workers, n.e.c.

4210. Forestry workers4301. Protective service workers

4302. Transport conductors4303. Guards and watchmen

4304. Food service workers4305. Mass transportation operators

4306. Service workers, n.e.c.4307. Hairdressers

4308. Newsboys and deliverymen4309. Launderers and dry-cleaners

4310. Housekeeping workers4311. Janitors and cleaners

4312. Gardeners5101. Fishermen

5201. Farmers and farm managers5202. Farm laborers

9990. Members of armed forces

USA

Romania

Phillipines

Venezuela

Male CAMSIS scale scores across four countries using 'microclass' units.

Hypothetical network: 469 US OUGs & micro-classes

Green: professional; Blue: routine non-manual; Red: manual; Yellow: primary; Black: military

Dental hygienists

Medical professionals

Medical and dental technicians

(Four different isolated components with internal links within microclass but no external links)

(further isolated components)

‘Pseudo-diagonal’ or ‘situs’

Occupational Structure, USA 2010Source: CPS 2010

Green: Professional; Yellow: routine non-manual; Red: Manual; Black: Farming

1970 19751980 1985

1990 19952000 2005

Occupational Structure, USA 2010Source: CPS 2010

Green: Professional; Yellow: routine non-manual; Red: Manual; Black: FarmingFood service

managers and food preparation managers and waitresses

Primary school teachers connecting to a range of occupations

Estate agents between stratified blocks

Farming communities with ties to all social levels

Teaching assistants crossing prestige levels

IT

teaching

Hotel workers

1990 19952000 2005Position of Receptionists

05,

000

10,0

0015

,000

20,0

0025

,000

Sam

ple s

ize

1970 1975 1980 1985 1990 1995 2000 2005 2010

Samplw sizes of both-working married couplesSource: CPS 1970-2010

02

46

8

% w

ithin

OU

G

1970 1975 1980 1985 1990 1995 2000 2005 2010

Percentage of married couples within same OUGSource: CPS 1970-2010

02

46

810

% w

ithin

mic

rocl

ass

1970 1975 1980 1985 1990 1995 2000 2005 2010

Percentage within same microclassSource: CPS 1970-2010

010

2030

4050

% w

ithin

mac

rocl

ass

1970 1975 1980 1985 1990 1995 2000 2005 2010

Percentage within same macroclassSource: CPS 1970-2010

020

4060

8010

0%

non

-gra

duat

es m

arry

ing

non-

grad

uate

s

1970 1975 1980 1985 1990 1995 2000 2005 2010

Percentage of non-graduates marrying non-graduatesSource: CPS 1970-2010

020

4060

80%

gra

duat

es m

arry

ing

grad

uate

s

1970 1975 1980 1985 1990 1995 2000 2005 2010

Percentage of graduates marrying graduatesSource: CPS 1970-2010

020

4060

80%

pro

fess

ions

with

deg

rees

Percentage of professionals with degreesSource: CPS 1970-2010

010

2030

4050

% m

anag

ers

with

deg

rees

Percentage of managers with degreesSource: CPS 1970-2010

020

4060

% a

ssoc

iate

pro

fess

ions

with

deg

rees

Percentage of associate professionals with degreesSource: CPS 1970-2010

010

2030

% r

outin

e no

n-m

anua

l with

deg

rees

Percentage of routine non-manual with degreesSource: CPS 1970-2010

05

10%

man

ual w

ith d

egre

es

Percentage of manual with degreesSource: CPS 1970-2010

05

1015

20%

farm

ers

with

deg

rees

Percentage of farmers with degreesSource: CPS 1970-2010

Graduate Non-graduate1970 Mechanical engineer Nurses

Buyers and department heads

Clerical and kindred workers

Pharmacists SalespersonsManagers n.e.c Personal and labour

relationsPrimary school teachersReal estate agents

Accountants Hucksters and peddlersArtists and art teachers FarmersSocial workers Auctioneers

1975 Managers n.e.c Dental assistantsAccountants Hucksters and peddlersHealth advisors SecretariesPublic administratorsIndustrial engineers

Craftsmen

Secondary school teachers Cafeteria workersFarmers Farm LabourersElectrical engineers Teacher aides

Misc. electrical workers1980 Physicians and surgeons Nurses

Public administratorsSchool administrators

Teacher aides

Secondary school teachers Primary school teachersManagers n.e.c. Health advisorsKindergarten teachers Sales representatives

(retail, n.e.c)Sales representatives (Manufacturing)

Managers n.e.c.

Cafeteria workers Waitresses

Graduate Non-graduate1985 Sales representatives

Secondary school teachersPhysicians and surgeonsPublic administratorsOther financial workers

Nurses

Sales representativesDentists

Receptionists

Dentists Managers n.e.cVeterinaries BookkeepersPurchasing agents Secretaries

1990 Health diagnosing professionals

Managers n.e.c

1995 Accountants and auditors Public administratorsSecondary school teachers Electrical power installers

2000 Clergy Managers n.e.c.Social workers HairdressersLawyers Designers

Legal assistantsData processing repairers Secretaries

2005 Maids Janitors2010 Bookkeepers Construction managers

Dentists Office supervisors

Over-represented graduate non-graduate marriage ties in USA 1970-2010Source: Current Population SurveyNote: Italics indicate the female occupation.

Managers in… 1985 1990 1995 2000 2005 2010 2010 CAMSIS

Public Administration/education

81.7 74.9 74.5 80.7 80.1 83.8 71.2

Personnel and labour relations

46.0 57.1 47.6 51.9 60.2 68.9 55.7

Chief Executives 37.5 14.3 40.0 37.5 67.5 67.0 70.7Business and promotions 52.0 58.8 63.6 66.7 70.6Medicine and health 62.5 66.2 47.5 50.2 62.9 66.8 66.6Marketing 45.8 52.3 62.8 65.3 56.4 65.8 65.3Financial managers 50.0 56.9 63.0 53.6 60.0 62.8 66.8Purchasing 65.4 43.2 61.7 46.2 55.6 54.6 60.5Properties 33.6 31.0 36.0 40.1 38.6 37.4 59.8Construction 23.5 29.1 57.8Food service 20.5 23.6 22.0 26.0 47.9Gaming 22.2 9.1 55.7n.e.c. 33.9 35.2 41.5 42.0 51.3 48.7 62.2

Source: Current Population Survey: 1985-2010 (http://www.cps.ipums.org/cps)

Percentage of graduates in managerial roles, USA 1985-2010

Conclusions

• Social Network Analysis can provide empirical evidence of occupational stratification

• Networks should be interpreted in terms of wide trends rather than specific occupations

• Little evolution of marriage networks in last 40 years of USA, but educational cohort effects are emerging

• Microclasses generally a sound way to group occupations, although social interaction patterns suggest not quite maximal.

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