socio-economic classifications derived from isco08 (and 88)
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Socio-economic Classifications derived from ISCO08 (and 88)
Eric Harrison, City University London
InGRID Expert Workshop Amsterdam, Feb 10-12, 2014
www.europeansocialsurvey.org
‘If you want to get rid of fuzzy job titles, then the last thing you should do is ask people for their job titles’.
(Birch 2014)
For data analysts, titles are just portals to tasks
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Overview
Preliminaries: Occupation and ClassThe ‘ESeC’Validation with EWCS and ESSConclusions
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From Occupation to Social Class
The accurate measurement of occupation is valuable not only in its own right, but also as a building block needed to derive many widely-used class schemas. In the context of cross-national research this also requires a high degree of harmonisation across countries. Despite considerable efforts in this direction, users accept that a combination of institutional differences and human error lead to less than optimal validity. Thus however conceptually rigorous the class measure, it is likely to be operationalised using survey data that is frequently imperfect and always incomplete.
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Occupation-based class schemas: Briefly
Employers, self-employed, employees
Then within employees….different types of employment
Lockwood – Market situation v Work situationGoldthorpe – redevelops and formalises this in terms of ‘contractual hazards for employers’
Asset specificity (marketable skills) Monitoring problems (autonomous work situation)
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Different forms of employer response
Service relationship
Labour contract
Pure and modified forms of both (lower managers & professionals, skilled workers)
‘Mixed’ forms of employment regulation where one dimension is high and one low
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Why surveys need social class variables
Sociology’s ‘only independent variable’It matters theoretically: central to both Marxian and Weberian discussions of inequality of resources and life-chancesIt works empirically: in many different versions and schemes it predicts y and explains r2
Most of the attitudes and/or behaviours measured by surveys will be correlated with class – users will expect to be able to do analysis
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Why class analysts need social surveys
Class positions are not inherently known to respondents – they are rooted in a person’s employment relations Can’t measure the subtleties of a person’s individual work and market situation (latent variables)We use a series of proxy questions to establish the employment relations that are typical of what we do know about that person’s employment relations
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Deriving class from survey information
Current job (in work), last job (unemployed), career typical job (retired) (1)Employment status (emp/self-emp) (1)If self-emp how many workers, if emp how many co-workers (2)Supervisory responsibility? If so, how many for? (2)Industrial sector of job (1)Occupation (3)
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And that’s just respondents!
Not all are economically active: if not, need to ask all those questions about partner (8)If no partner in place and/or if respondent living at home , may revert to status of principal parent May be interested in father and mother’s class position anyway (social origins and destinations) so ask questions about them too
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Occupation is Key
Though it’s nice to have full information, occupation drives 85%+ of a class allocation.Employment relations emerge out of occupation-specific custom and practiceThis makes its measurement crucialAccuracy of posting to main groupPrecision in specifying detailed occupation within this (up to 4 digits)
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‘ESeC’ESeC Class Common Term Employment regulation
1 Large employers, higher grade professional, administrative and managerial occupations
Higher salariat Service Relationship
2 Lower grade professional, administrative and managerial occupations and higher grade technician and supervisory occupations
Lower salariat Service Relationship (modified)
3 Intermediate occupations Higher grade white collar workers
Mixed
4 Small employer and self employed occupations (exc agriculture etc)
Petit bourgeoisie or independents
Not applicable
5 Self employed occupations (agriculture etc) Petit bourgeoisie or independents
Not applicable
6 Lower supervisory and lower technician occupations
Higher grade blue collar workers
Mixed
7 Lower services, sales and clerical occupations Lower grade white collar workers
Labour Contract (modified)
8 Lower technical occupations Skilled workers Labour Contract (modified)
9 Routine occupations Semi- and non-skilled workers
Labour Contract
10 Never worked and long-term unemployed Unemployed Not applicable
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‘ESeC’ESeC Class Common Term Employment regulation
1 Large employers, higher grade professional, administrative and managerial occupations
Higher salariat Service Relationship
2 Lower grade professional, administrative and managerial occupations and higher grade technician and supervisory occupations
Lower salariat Service Relationship (modified)
3 Intermediate occupations Higher grade white collar workers
Mixed
4 Small employer and self employed occupations (exc agriculture etc)
Petit bourgeoisie or independents
Not applicable
5 Self employed occupations (agriculture etc) Petit bourgeoisie or independents
Not applicable
6 Lower supervisory and lower technician occupations
Higher grade blue collar workers
Mixed
7 Lower services, sales and clerical occupations Lower grade white collar workers
Labour Contract (modified)
8 Lower technical occupations Skilled workers Labour Contract (modified)
9 Routine occupations Semi- and non-skilled workers
Labour Contract
10 Never worked and long-term unemployed Unemployed Not applicable
www.europeansocialsurvey.org 15
‘ESeC’ESeC Class Common Term Employment regulation
1 Large employers, higher grade professional, administrative and managerial occupations
Higher salariat Service Relationship
2 Lower grade professional, administrative and managerial occupations and higher grade technician and supervisory occupations
Lower salariat Service Relationship (modified)
3 Intermediate occupations Higher grade white collar workers
Mixed
4 Small employer and self employed occupations (exc agriculture etc)
Petit bourgeoisie or independents
Not applicable
5 Self employed occupations (agriculture etc) Petit bourgeoisie or independents
Not applicable
6 Lower supervisory and lower technician occupations
Higher grade blue collar workers
Mixed
7 Lower services, sales and clerical occupations Lower grade white collar workers
Labour Contract (modified)
8 Lower technical occupations Skilled workers Labour Contract (modified)
9 Routine occupations Semi- and non-skilled workers
Labour Contract
10 Never worked and long-term unemployed Unemployed Not applicable
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ISCO and ESeC
High degree of equivalence: Isco groups 1 and 2 map to top classes, and group 9 to class 9
3000 – 7000 much fuzzier. Associate professionals, technical and service work
So need more than 1 or 2 digits
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Rebasing ESeC on ISCO08
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Three forms of validation
Operational – does it work, can we apply it to a range of datasets? What happens after loss of information?
Criterion – does it measure what it purports to measure?
Construct - Does it predict the sorts of outcomes that theory suggests it should?
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Data from the EWCS
Fieldwork Jan – June 2010Face to face interviews outside the workplace43,816 respondents 15+ in employment 34 countriesAverage RR =44% (31to 74%)Most detailed survey of employment conditions and experiencesLong running series – EWCS #1 in 1991
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If you compare your situation with Jan 2009...
...have you experienced a change in the number of hours you work per week?...have you experienced a change in your salary or income?
Responses: Decrease, No change, Increase
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Change in Working time since 2009
ESeC 1 ESeC 2 ESeC 3 ESeC 4 ESeC 5 ESeC 6 ESeC 7 ESeC 8 ESeC 90
5
10
15
20
25
Increase in hoursDecrease in hours
%
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Change in earnings since 2009
ESeC 1 ESeC 2 ESeC 3 ESeC 4 ESeC 5 ESeC 6 ESeC 7 ESeC 8 ESeC 90
5
10
15
20
25
30
35
40
45
50
Increase in salaryDecrease in salary
%
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Generally, does your main paid job involve...
...meeting precise quality standards?
...assessing yourself the quality of your work?
...solving unforeseen problems on your own?
...monotonous tasks?
...complex tasks?
...learning new things?
Dichotomous response
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Job Content & Quality
ESeC 1 ESeC 2 ESeC 3 ESeC 4 ESeC 5 ESeC 6 ESeC 7 ESeC 8 ESeC 90
10
20
30
40
50
60
70
80
90
100
Complex tasksLearning new thingsSelf-assessed qualityProblem solvingMonotonous tasksQuality standards
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Is the pace of your work dependent on...
...the work of colleagues?
...demands of customers, passengers, clients etc?
...production or performance targets?
...movement of a machine or product?
...the direct control of your boss?
Dichotomous response
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Pace of work determined by...
ESeC 1 ESeC 2 ESeC 3 ESeC 4 ESeC 5 ESeC 6 ESeC 7 ESeC 8 ESeC 90
10
20
30
40
50
60
70
80
90
MachineryBossColleaguesTargetsCustomers
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Are you able to choose or change...
...your order of tasks?
...your methods of work?Your speed or rate of work?
Dichotomous response
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Autonomy over aspects of job
ESeC 1 ESeC 2 ESeC 3 ESeC 4 ESeC 5 ESeC 6 ESeC 7 ESeC 8 ESeC 90
10
20
30
40
50
60
70
80
90
100
Order of tasksMethods of workSpeed of work
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Discussion
Broad ‘tip to toe’ fit with expected class ‘gradient’Distinctive self-employment spikes consistent with theory and experienceAnomalies in classes 3, 6 and 7 largely consistent with theory: Classes are relational not hierarchicalSome interesting results on individual measures Customer /market ethos pervades modern societiesTotal quality improvement and target setting do not respect employment relations boundaries
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Three forms of validation
Operational – does it work, can we apply it to a range of datasets? What happens after loss of information?
Criterion – does it measure what it purports to measure?
Construct - Does it predict the sorts of outcomes that theory suggests it should?
www.europeansocialsurvey.org
ESS R5 data on work and wellbeing in recession
ESS rotating module geared specifically to concepts of interestAsset specificity (how easy for you to get another job + how difficult for employer to replace you?)Monitoring problems (how difficult for your immediate boss to know how much effort you’re putting in?)Job quality (variety in work + learn new things + support from co-workers + security)
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Analysis Strategy
Pooled R5 dataset with controls for countryDummies for each class (reference class 9)Controls for age, age sq, education (high, medium, ref= low), gender.Separate models for each of four derivation methods:• 3 digit occupation + supervision• 2 digit occupation + supervision • 3 digit occupation minus supervision• 2 digit occupation minus supervision
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Asset Specificity (0-20 scale) OLS coefficients (ref = class 9)
Class 1 Class 2 Class 3 Class 6 Class 7 Class 8 Class 90
0.20.40.60.8
11.21.41.61.8
2
3 digit +2 digit +3 digit -2 digit -
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Monitoring Problems
• Few if any significant results...
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Job Quality (0-12 scale) OLS coefficients (ref = class 9)
Class 1 Class 2 Class 3 Class 6 Class 7 Class 8 Class 90
0.5
1
1.5
2
2.5
3
3 digit +2 digit +3 digit -2 digit -
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Subjective Health (1-5 scale)
Class 1
Class 2
Class 3
Class 4
Class 5
Class 6
Class 7
Class 8
Class 9
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Most infoLeast info
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Happiness (0-10 scale)
Class 1
Class 2
Class 3
Class 4
Class 5
Class 6
Class 7
Class 8
Class 9
0
0.1
0.2
0.3
0.4
0.5
0.6
Most infoLeast info
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Discussion
Classes 3 and 6 sometimes in ‘wrong order’ but significantly distinct from each other – ‘mixed classes‘Class 8 outperforms 7 on criterion measures but this is reversed for construct validityIncomplete information has minimal impact on utility of scheme – but class 6 remains a problemCountry by country analysis and experiments with different and fewer classes needed
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Challenges to measurement of class through occupation
Working with international standard instrument - the new ISCO revision will take time to work throughImproving measurement in existing modes and adapting to changes in mode (self-administered web surveys)Enforcing better harmonisation across countries in both their collection of national data and their mapping to international measures
ESRA, Lausanne, 2011 39
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Remaining Issues
Sticking to 2 (or even 1!) digit ISCO would save time, reduce resource burden, increase national comparability
But over time would undermine theoretical foundations, i.e. individual occupations are where ER are embedded
Could use collapsed class schemas for general surveys but devote more resources to specialist research into social stratification and mobility across Europe (and beyond…)
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Thank you for listening.
Correspondence: eric.harrison.2@city.ac.uk
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