Sociological classifications and simulation models of social inequality

Homogamy and social structure over time in FinlandJani Erola and Paul LambertSocial Stratification Research Seminar, Utrecht, 8-10 September 2010 AimsConstruct CAMSIS scales for FinlandTest the effects of homogamy on partnership matching with the scaling approarchCAMSIS scale for FinlandModel the social distance between occupational units using average patterns of social interaction/ cohabitation between incumbents of occupationswww.camsis.stir.ac.uk Correspondence analysis for large numbers of units using Stata macro; RC2 association models in R (gnm) for smaller numbers of units for standard errors Interpret the social distance dimension as indicating the structure of social stratification (the reproduction of social inequality) Census data inputs Cohabiting couples, current or previous occupationJob coded into 4 digit ISCO Plus 2 category employment status5 yearly and pooled data

Employment status(self-employed/ employee)

Could ignore this data (noise/inconvenience)We choose to use it for groups 6-9 only

Occupational unitsOccupations were recoded to finest level of detail available (in ISCO-by-employment status location) according to a rule of thumb that at least 30 cases must represent the occupationPre-defined recoding rules (use ISCO sub-groups) 1970758085909520002005allNumber of occsM108129158172183221237248350F7191104120135160186208283Scale derivations using algorithmsAlgorithms proceed by:

Define any cohabiting combinations to be excluded from models (ISCO diagonals and farming related pseudo-diagonals 1311; 6***; 9211)

Recode occupations to avoid sparsity for the remaining cases

Perform CA and extract dimension scores

Standardise scores to mean 50, sd 15

Distribute dimension scores from analytical categories to all ISCO categories according to recoding algorithm

Some further illustrative examplesThe role of detailed occupational differences Illustrative male and female scale valuesThe problem of farmers

Males: Combined scale (1970-2005)

Male and female CAMSIS scale scores for those ISCO units with over 4000 males in each ISCO

Females: Combined scale (1970-2005)

Male and female CAMSIS scale scores for those ISCO units with over 4000 females in each ISCONote how men in female jobs often have higher averages: e.g. 9132 is a average job in the male distribution, but is more than 1 SD below average in the female distribution.

i.e. The placement of farmers is influential to the correlation with other things, and is likely to change between scales/time

CAMSIS/ISEI micro comparisonsEducationIncome quintilesErikson-Goldthorpe classes

Separately for men and womenUsing male scalesAssociations with education, men

R2ISEIFCS1970443819754442198042431985474919904750199552532000474920055548Associations with education, women

R2ISEIFCS1970314819753049198030521985335119903251199541502000384920053947Associations with income, men

R2ISEIFCS1970231619751613198016131985161319901413199513112000151320051716Associations with income, women

R2ISEIFCS1970203219751824198016181985182319901521199518222000192120052124Associations with EGP, men

R2ISEIFCS1970827019758279198080771985797519907770199577732000797420057875Associations with EG, women

R2ISEIFCS1970767219757675198074771985747519907172199571712000737320057376Changes in homogamyArgument: homogamy increasing in most societiesKalmijn, 1998; Sweeney & Cancian, 2004; Schwarz & Mare, 2005; Blossfeld, 2009Natural test with couple-data based stratification dataChange in scales = change in the way how couple relationships are stratifiedDoes changing homogamy play a role in this?30Loglinear RC-modelsRC-coefficients for men and women, changing marginals, diagonal cells controlledRC-estimates for men and women, allowing change in diagonalsRC-coefficients assuming no yearly change should be the same as the scale values from CAThe impact of the changes in homogamy should be observed as a change in RC coefficients between the models

31Models for ISCO88 Major groups L-squareddfDIBICAICMod 1. year:men + year:women + Diagonals(men:women)48087,64960,11741540,347081,6Mod 2. 1 + RC-association3713,94810,029-2638,12737,9Mod 3. 2 + Linear change in diagonals3015,74730,025-3219,12057,7Mod 4. 2 + Non-lin. change in diagonals2816,64250,022-2715,31966,632The effects of the change in homogamy on RC coefficientsNo changeLinear changeNon-lin changeCoeffSECoeffSECoeffSEMenManag/legis/offic000000Profess-0,030,01-0,010,01-0,010,01Tech/Assoc profs0,420,010,420,010,420,01Clerks0,620,010,610,010,610,01Service/Sales0,590,010,590,010,590,01Agriculture0,780,010,780,010,780,01Crafts/Trades1,030,011,020,011,020,01Mach operators1,090,011,080,011,080,01Elementary101010WomenManag/legis/offic000000Profess-0,050,01-0,050,01-0,050,01Tech/Assoc profs0,240,010,240,010,240,01Clerks0,410,010,400,010,400,01Service/Sales0,640,010,640,010,640,01Agriculture0,850,010,850,010,850,01Crafts/Trades0,830,010,830,010,830,01Mach operators1,050,011,050,011,050,01Elementary101010Homogamy estimates change to wrong direction!Homogamy change forCoef.SEManag/legis/offic0,000,01Profess-0,120,01Tech/Assoc profs0,000,01Clerks0,020,01Service/Sales0,000,01Crafts/Trades-0,040,01Mach operators0,010,01Elementary-0,080,01CaveatsPrevious results suggest increasing homogamy according to education => occupations different story?1-digit level simply too coarse?Now all cohabs, restricting analyses to marriages?ConclusionsSocial interaction distance scales appear to measure stratification quite well on Finnish dataDifferences between men and womenMain difference between years involves farmersHomogamy trends dont seem to matter

Work very much in beginning