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Stratification - Stirling 2007 1
Concepts and Measures: Empirical Evidence on the interpretation
of ESeC and other occupation-based social classifications
Paul Lambert University of StirlingErik Bihagen University of Stockholm
Paper presented to Social Stratification Research Seminar, Stirling 5-7 September 2007
Stratification - Stirling 2007 2
Summary: occupation-based social classifications
Relevance of reviewing lots of schemes (1) Broad concordance of most measures (2) Optimum measures are ambiguous
(1) Lots of overlap in conceptual correlates (3) A small residual difference does reflect concepts
Sensible taxonomies can rarely be judged true or false, only more or less useful for a given purpose [Mills & Evans, 2003:80]
[EGP]...has a clear theoretical basis, therefore differences between groups in health outcomes can be attributed to the specific
employment relations that characterise each group [Shaw et al., 2007:78]
Stratification - Stirling 2007 3
This review• Relationships between concepts and measures• Properties of various contemporary occupation-based social
classifications– via SOC90 / NYK/ ISCO88 and employment status
• ESeC [Rose and Harrison 2007]
– European Socio-Economic Classification High degree of replicability Empirical validation / criterion validity Standardisation / consistency / widespread use Theoretical integration (with EGP) Compare with unemployment [Elias & McKnight 2003; Chan &
Goldthorpe 2007; Schizzerotto et al 2007]
Stratification - Stirling 2007 4
• Class 1: Large employers, higher grade professional, administrative and managerial occupations: 'the higher salariat'
• Class 2: Lower grade professional, administrative and managerial occupations: higher grade technician and supervisory occupations: 'the lower salariat'
• Class 3: Intermediate occupations: 'higher grade white collar workers'
• Classes 4 and 5: Small employers and self-employed in non-professional occupations: 'petit-bourgeoisie or independents'
• Class 6: Lower supervisory and lower technician occupations: 'higher grade blue collar workers'
• Class 7: Lower services, sales and clerical occupations: 'lower grade white collar workers'
• Class 8: Lower technical occupations: 'skilled workers' • Class 9: Routine occupations: 'semi- and unskilled workers' • Class 10: Never worked and long-term unemployed: 'unemployed' • The non-employed • Six, five and three class models
Stratification - Stirling 2007 5
Micro-data• Britain 1991-2002 BHPS 1991, 4537 adults 23-
55yrs in work 2710 adults observed every
year till 2002
• Sweden 1991-2002• LNU 1991, 2538 adults 23-
55yrs in work• Linked to PRESO
administrative data until 2002 [Tomas Korpi]
Unemployment 1991-2002 (m/f; employees) Br Sw
Ever Unemployed 1991-2002 28% / 23% 36% / 39%
Unemployed for >1 year 1991-2002 9% / 6% 26% / 29%
‘Incidence rate’ (time Un. / active time) 3.4 / 2.3
Cumulative rate (log of total time Un.) 1.5 / 1.2 2.3 / 2.3
Stratification - Stirling 2007 6
Reviewing occupation-based social classifications? GEODE – Grid Enabled Occupational Data Environment, www.geode.stir.ac.uk
[e.g. Lambert et al 2007, International Journal of Digital Curation]
Stratification - Stirling 2007 7
Stratification - Stirling 2007 8
=> 31 Occupation-based social classifications
ES5 Employment Status (5) WR Wright (12 categories)
ES2 Employment Status (2) WR9 Wright (9) CM CAMSIS (male scale)
E9 ESeC (9 categories) G11 EGP (11 categories) CF CAMSIS (female scale)
E6 ESeC (6 categories) G7 EGP (7 categories) CM2 CAMSIS (male scale, S)
E5 ESeC (5 categories) G5 EGP (5 categories) CF2 CAMSIS (female, S)
E3 ESeC (3 categories) G3 EGP (3 categories) CG Chan-Goldthorpe status
E2 ESeC (2 categories) G2 EGP (2 categories) AWM Wage mobility score
K4 Skill (4 ISCO categories) MN Manual / Non-M (2) WG1 Wage score (S)
O17 Oesch work logic (17) WG2 Wage score (S)
O8 Oesch work logic (8) ISEI (via ISCO88) WG3 Wage score (B)
O4 Oesch work logic (4) SIOPS (via ISCO88) GN Gender segregation index
Stratification - Stirling 2007 9
Results: Concepts and measures
1) Broad concordance of schemes
2) Ambiguity of optimal schemes
3) Some residual differences do reflect conceptual origins
Stratification - Stirling 2007 10
0.1
.2.3
.4.5
.6.7
.8.9
1C
ram
er's
V
ES5
ES2E9
E6E5
E3E2
G11G7
G5G3
G2K4
WRWR9
O17 O8
o4MN
Employemt Status ESeC schemes EGP schemes Skill classification
Wright schemes Oesch schemes Manual / Non-manual
Britain0
.1.2
.3.4
.5.6
.7.8
.91
Cra
mer
's V
ES5
ES2E9
E6E5
E3E2
G11G7
G5G3
G2K4
WRWR9
O17 O8
o4MN
Men Women
Sweden
(2.1) Categorical - Categorical relations, Cramer's V
Stratification - Stirling 2007 11
0.1
.2.3
.4.5
.6.7
.8.9
1A
nova
R
ES5
ES2E9
E6E5
E3E2
G11G7
G5G3
G2K4
WRWR9
O17 O8
o4MN
CAMSIS / CG Scale ISEI SIOPS
AWM Income averages Gender segregation
Britain0
.1.2
.3.4
.5.6
.7.8
.91
Ano
va R
ES5
ES2E9
E6E5
E3E2
G11G7
G5G3
G2K4
WRWR9
O17 O8
o4MN
Men Women
Sweden
(2.3) Categorical-Metric relations, Anova R
Stratification - Stirling 2007 12
Men and Women (categorical social classifications)
0.1
.2.3
.4.5
.6.7
.8.9
1R
or
pseu
do-R
ES5
E9
E6E5
E3E2
G11G7
G5G3
G2K4
WRWR9
O17 O8
o4MN
Promotion / retention Pay - bonus / increments Hours and level of monitoring
Labour contract type Subjective skill requirements
Men and Women (metric social classifications)
0.1
.2.3
.4.5
.6.7
.8.9
1R
or
pseu
do-R
CM
CFCM2
CF2CG
ISEISIOP
AWMWG1
WG2WG3
GN
Britain Sweden
(2.6) Associations - Employment Relations and Conditions
Stratification - Stirling 2007 13
Results: Concepts and measures
1) Broad concordance of schemes• Measures mostly measure the same thing
Generalised concepts are better
• Criterion validity is asymmetric [cf. Tahlin 2007]
2) Ambiguity of optimal schemes
3) Some residual differences do reflect conceptual origins
Stratification - Stirling 2007 14
-.01
.01
.03
.05
.07
.09
NullES5
ES2E9
E6E5
E3E2
G11G7
G5G3
G2K4
WRWR9
O17O8
O4MN
CMCF
CGISEI
SIOPAWM
WG3GN
Pseudo R-squared Increase in BIC
Britain, Males
-.06
-.04
-.02
0.0
2.0
4.0
6
NullES5
ES2E9
E6E5
E3E2
G11G7
G5G3
G2K4
WRWR9
O17O8
O4MN
CMCF
CM2CF2
ISEI
SIOPAWM
WG1WG2
GN
Sweden, Males
(3.4a) R-2 and BIC for predicted unemployment risk
Stratification - Stirling 2007 15
Results: Concepts and measures
1) Broad concordance of schemes
2) Ambiguity of optimal schemes Balancing explanatory power and parsimony No schemes stand out as substantially stronger ESeC & EGP 3- and 2-class versions limited AWM favourable in Sweden
3) Some residual differences do reflect conceptual origins
Stratification - Stirling 2007 16
0.0
25
.05
E9
E3G11
G7K4
CMISEI
AWM
Decrease in log-like
Increase in BIC
(1): with additional explanatory variables
0.0
25
.05
.075
E9
E3G11
G7K4
CMISEI
AWM
(2): (1) plus industry indicator variables
0.0
25
E9
E3G11
G7K4
CMISEI
AWM
(3): Heckman selection, Industry = public sector services
0.0
25
E9
E3G11
G7K4
CMISEI
AWM
(4): Heckman selection, Industry = private manufacturing
(4.1): Unemployment risks (British men)
Stratification - Stirling 2007 17
EGP cf. CAMSIS – critical individuals
Britain (males)
Better EGP predicted risk of Un. (H – rightly higher; L – rightly lower)
7121 (L) Builders (traditional)
8322 (L) Car / taxi drivers
1314 (L) Wholesale / retail managers
7141 (L) Painters
7231 (H) Motor mechanics
2411 (H) Accountants
4131 (H) Stock clerks
7124 (H) Carpenters / joiners
8324 (H) Truck / Lorry drivers
Better CAMSIS predicted risk of Un. (H – rightly higher; L – rightly lower)
5169 (L) Protective service workers
4212 (L) Tellers / counter clerks
4190 (L) Office clerks
7230 (L) Machinery mechanics/fitters
1314 (H) Wholesale / retail managers
Stratification - Stirling 2007 18
Results: Concepts and measures
1) Broad concordance of schemes
2) Ambiguity of optimal schemes
3) Some residual differences do seem to reflect conceptual origins
Differences between schemes diminish but don’t vanish G11 in Br explains more Unemp. [as Chan & Goldthorpe 2007] E9 in Sweden explains more Unemp. ??Are empirical differences due to (the concepts / employment
relations of) certain specific occ.s
Stratification - Stirling 2007 19
Conclusions
• Do measures measure concepts? – Yes (sometimes) – criterion validity
– No (not uniquely)
• How should we choose between measures? – Practical issues
– Conceptual assumptions – generalised schemes
• What about ESeC? – Few clear strengths in empirical properties
– Practical advantages if widely used
Stratification - Stirling 2007 20
References
• Chan, T. W., & Goldthorpe, J. H. (2007). Class and Status: The Conceptual Distinction and its Empirical Relevance. American Sociological Review, 72, 512-532.
• Elias, P., & McKnight, A. (2003). Earnings, Unemployment and the NS-SEC. In D. Rose & D. J. Pevalin (Eds.), A Researcher's Guide to the National Statistics Socio-Economic Classification. London: Sage.
• Goldthorpe, J. H., & McKnight, A. (2006). The Economic Basis of Social Class. In S. L. Morgan, D. B. Grusky & G. S. Fields (Eds.), Mobility and Inequality. Stanford: Stanford University Press.
• Lambert, P. S., Tan, K. L. L., Turner, K. J., Gayle, V., Prandy, K., & Sinnott, R. O. (2007). Data Curation Standards and Social Science Occupational Information Resources. International Journal of Digital Curation, 2(1), 73-91.
• Mills, C., & Evans, G. (2003). Employment Relations, Employment Conditions and the NS-SEC. In D. Rose & D. J. Pevalin (Eds.), A Researchers Guide to the National Statistics Socio-economic Classification (pp. 77-106). London: Sage.
• Rose, D., & Harrison, E. (2007). The European Socio-economic Classification: A New Social Class Scheme for Comparative European Research. European Societies, 9(3), 459-490.
• Schizzerotto, A., Barone, R., & Arosio, L. (2006). Unemployment risks in four European countries: an attempt of testing the construct validity of the ESeC scheme. Bled, Slovenia, and http://www.iser.essex.ac.uk/esec/: Paper presented to the Workshop on the Application of ESeC within the European Union and Candidate Countries, 29-30 June 2006.
• Shaw, M., Galobardes, B., Lawlor, D. A., Lynch, J., Wheeler, B., & Davey Smith, G. (2007). The Handbook of Inequality and Socioeconomic Position: Concepts and Measures. Bristol: Policy Press.
• Tahlin, M. (forthcoming). Class Clues. European Sociological Review.
Stratification - Stirling 2007 21
Appendices
Stratification - Stirling 2007 22
Males, Britain-2-1
01
2
Males, Sweden
-2-1
01
2
Higher salariatLower salariat
IntermediateSmall Self-emp
FarmersLow. sup./technic
Low. serv./cler.Low. technical
Routine
Ever experienced unemployment 1991-2002 Unemployment incidence rate
1 year or more unemployed Log of total unemployment
Source: LNU and BHPS 1991-2002
Comparison intervals for ESeC categories, by unemployment measure
Figure 3.1: Predictions of Unemployment risk, 1991-2002
Stratification - Stirling 2007 23
Background – handling occupational data [e.g. Lambert et al 2007, International Journal of Digital Curation]
Model is: 1) Record and preserve ‘source’ occupational data (i.e OUG)2) Use a transparent translation code to derive occupation-based
social classifications
Challenges include:– Locating occupational information resources
http://home.fsw.vu.nl/~ganzeboom/pisa/http://www.iser.essex.ac.uk/esec/consort/matrices/
– Large volumes of data (country; time; updates) – Detail on occupational index units (OUGs)– Gaps in working practices (software; NSI’s v’s academics)
ESeC has many attractive features: well documented scheme with ‘criterion validity’; transparent access in SPSS; wide adoption likely
Stratification - Stirling 2007 24
Stratification - Stirling 2007 25
Stratification - Stirling 2007 26
Men and Women (categorical social classifications)0
.1.2
.3.4
.5.6
.7R
or
pseu
do-R
ES5
E9
E6E5
E3E2
G11G7
G5G3
G2K4
WRWR9
O17 O8
o4MN
Promotion / retention Pay - bonus / increments Hours and level of monitoring
Labour contract type Subjective skill requirements
Men and Women (metric social classifications)
0.1
.2.3
.4.5
.6.7
R o
r ps
eudo
-R
CM
CFCM2
CF2CG
ISEISIOP
AWMWG1
WG2WG3
GN
Britain Sweden
(2.6b) Employment Relations / Conditions (excluding contract data)
Stratification - Stirling 2007 27
-.05
0.0
5.1.
15.2
.25.
3
ES5
ES2E9
E6E5
E3E2
G11G7
G5G3
G2K4
WRWR9
O17O8
O4MN
CMCF
CGISEI
SIOPAWM
WG3GN
Increase in R-squared Increase in BIC
Britain
-.05
0.0
5.1
.15
.2.2
5.3
.35
ES5
ES2E9
E6E5
E3E2
G11G7
G5G3
G2K4
WRWR9
O17O8
O4MN
CMCF
CM2CF2
ISEI
SIOPAWM
WG1WG2
GN
Sweden
(3.5) R-2 and BIC for Years of Education
Stratification - Stirling 2007 28
-.01
.01
.03
.05
.07
.09
NullES5
ES2E9
E6E5
E3E2
G11G7
G5G3
G2K4
MN
CMCF
CGISEI
SIOPAWM
WG3GN
Pseudo R-squared Increase in BIC
Britain, Males (Father's effects)
-.01
.01
.03
.05
NullES5
ES2E9
E6E5
E3E2
G11G7
G5G3
G2K4
MN
CMCF
CM2CF2
ISEI
SIOPAWM
WG1WG2
GN
Sweden, Males (Father's effects)
(3.4c) R-2 and BIC unemployment risk, father's scheme
Stratification - Stirling 2007 29
0.0
25.0
5
E9
E3G11
G7K4
CMISEI
AWM
Decrease in log-like
Increase in BIC
(1): with additional explanatory variables
0.0
25.0
5
E9
E3G11
G7K4
CMISEI
AWM
(2): (1) plus industry indicator variables
0.0
25
E9
E3G11
G7K4
CMISEI
AWM
(3): Heckman selection, Industry = public sector services
0.0
25
E9
E3G11
G7K4
CMISEI
AWM
(4): Heckman selection, Industry = private manufacturing
(4.2): Unemployment risks (Swedish men)