HIS-CAM - Leuven, Nov HIS-CAM - Presentation and evaluation of an historical occupational stratification scale based upon the analysis of social interaction Presentation to: Historical Demography (section on occupation), workshop on The occupation in historical research, Leuven, November 30 th Paul LambertStirling University Richard Zijdeman, Ineke MaasUtrecht University Ken PrandyCardiff University Marco van LeeuwenInternational Institute for Social History

HIS-CAM - Leuven, Nov Occupations and social structure Starting from the occupational titles themselves [HISCO – van Leeuwen, Maas & Miles 2002] Comparative historical research This talk: 1)HIS-CAM and the CAMSIS approach 2)Approaches to universality and specificity

HIS-CAM - Leuven, Nov CAMSIS ( Social Interaction Social Stratification Index of occupations positions Social interaction data (occupations of associates) –Partnership – Readily available in contemporary countries –Friendship; Intra-generational mobility; Inter-generational mobility;... Specific approach –Many scales - for countries, gender, time periods, using detailed occ. codes CAMSIS – Cambridge Social Interaction & Stratification Scales –Stewart, A., Prandy, K. and Blackburn, R.M. (1980) Social Stratification and Occupations. MacMillan. Other related applications: –Laumann, E. O., & Guttman, L. (1966). The relative associational contiguity of occupations in an urban setting. American Sociological Review, 31, –Chan, T. W., & Goldthorpe, J. H. (2007). Class and Status: The Conceptual Distinction and its Empirical Relevance. American Sociological Review, 72,

HIS-CAM - Leuven, Nov CAMSIS scale derivations Work on 27 countries so far, full derivations for 14 –Australia 1996; Slovakia 1995; Austria 1991/5; Slovenia ; Britain 2001, 1991, 1971, C19th; Spain 2002; Sweden 1990; Czech 1994; Switzerland 1990; Germany 1991/5; Turkey 1990; Hungary 1990/6; USA 1960, 1990, 2000; Ireland 1996 ISCO and national occupational unit schemes Downloaded as zip archives with index file matching Further national derivations actively pursued Empirical perspective – scales neutrally derived

5 CAMSIS scale construction methods We use Goodmans RC-II Association models in lEM (Vermunt 1997); correspondence analysis also suitable RC-II allows us to separate out other influences on social interaction in occupations through pseudo-diagonals and subsidiary dimensions Husbands Job Units Occ Units Derived scores Wifes Job Units

HIS-CAM - Leuven, Nov CAMSIS for historical comparative research? Preserve detailed occupational differences –Typically 300+ different scores in a dimension of stratification –Easy to add employment status dimension(s) if required Comparative properties –Tell us about relative positions of occupations within their contexts {national / temporal / gendered / other} Inter-generational occupational links –Data on social interaction between occupations marriage records for husband-wife and their parents household census returns (within-household occups)

HIS-CAM - Leuven, Nov HIS-CAM in short Version 0.1 ( May 2006) Netherlands, Germany, France, Sweden, UK, Canada Small range of scales linked to HISCO units & sub-groups One cross-national scale (universal), and 6 national scales (specific), for Version 0.2 (in process) Improved micro-data on 6 core countries (extended coding quality review; increased volume of cases) Consideration of US micro-data from IPUMS A larger range of universal and specific scales, using different permutations of countries, time periods, and gender

HIS-CAM - Leuven, Nov HIS-CAM scales prove to have very similar properties to contemporary CAMSIS scales Clearly reflect an order of stratification advantage / disadvantage in occupations Jobs with educational requirements tend to be highest ranked (Univ. professors) Low skilled labouring jobs tend to be lowest ranked Correlate around 0.7 with prestige scales, class schemes Some plausible differences between different specific scales Agricultural jobs show most variation in relative positions between countries Service sector jobs change positions over period

HIS-CAM - Leuven, Nov HIS-CAM at length We have numerous possible specific scales How do we decide between them.. => 2) Approaches to Universality and Specificity in historical data

HIS-CAM - Leuven, Nov Previous paper (May 2006) It is easy to justify attention to specificity Statistically, specificity makes for a better model Substantively, specific differences often make sense

HIS-CAM - Leuven, Nov Nested scale estimates using lEM (Vermunt 1997)

HIS-CAM - Leuven, Nov

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HIS-CAM - Leuven, Nov v0.2: There are problems with specificity i.Its a great deal of work to produce specific scales… ii.Users dont want measures which are too complex iii.There are possible measurement errors –Coding practices varying by countries –Model estimates rely on data management / adaptations

HIS-CAM - Leuven, Nov Permutations and Occupations C9 national groupings (7 countries, plus all countries, plus all countries excl. US) L5 levels of occupational detail (major groups, 1-digit, 2-digit, 3-digit, 5 digit) S4 gender groupings (all occupations combined; male occupations only; female occs based on daughter-father; female occs based on daughter-mother) T5 time periods (whole period; pre- and post- 1891; pre- and post national specific point of transition in agriculture/manufacturing balance) 9*5*4*5 = 900 different v0.2 HIS-CAM scales

HIS-CAM - Leuven, Nov Data used in v # child-parent data points (% male-male) Netherlands (47) (39) (61) Germany 7710 (97)5499 (99)2211 (86) France (45)40931 (47)24377 (44) Sweden (75)18079 (74)1087 (88) UK (78)28848 (82)16669 (72) Canada (Quebec) (98)91680 (99) (98) US (43)56310 (20) (53)

HIS-CAM - Leuven, Nov

HIS-CAM - Leuven, Nov The impact of data Distribution of cases into occupations on each of the 900 samples is substantially different –(in v0.1, this was ignored by using common coding in a nested model framework) Ideally, a principle of specificity would involve national experts in occupational coding and statistical modelling, iteratively reviewing coding and categorisations whilst optimising statistical models [=>relatively few contemporary CAMSIS scales…] In practice…

HIS-CAM - Leuven, Nov v0.2 strategies Automated recoding of sparse occupations –(to popular or generic subgroup codes) Standard model selection criteria –(2 dim model, excluding diagonals) Est. 2 hrs data management and 1 hour scale estimation processing time per scale

HIS-CAM - Leuven, Nov Example results so far… Core Country; time with relatively.. Relatively…HighestLowest 0/1 Professional / agriculturalCanada; lateGermany; early 2 Administrative / managerialNetherlands; earlyCanada; late 3 Clerical and relatedSweden; earlyGermany; late 4 Sales workersGermany; earlyNetherlands; late 5 Service workersCanada; lateSweden; early 6 AgriculturalGermany; earlyNetherlands; late 7/8/9 Production, etcNetherlands; lateUK; early

HIS-CAM - Leuven, Nov Current conclusions Country patterns influence pooled patterns (e.g. Dutch structure dominates pooled models) Argues for specificity within countries May be better to use national scales internationally, than derive pooled scales Universality / specificity is largely about practical concerns

HIS-CAM - Leuven, Nov Conclusions – HIS-CAM and other Occupation-based social classifications HIS-CAM is an effective measure of stratification inequality –Concepts and measures debate in social classifications… HIS-CAM a fruitful approach for examining particular occupational circumstances within countries HIS-CAM is potentially sensitive to structural differences in occupational distributions between contexts Challenges of working with and communicating large volumes of occupational information..