The National Statistics Socio-economic Classification: Origins, Development and Use

Transcription

1 The National Statistics Socio-economic Classification: Origins, Development and Use David Rose and David J Pevalin (with Karen O Reilly) Institute for Social and Economic Research University of Essex

2 Crown copyright 2005 Published with the permission of the Controller of Her Majesty s Stationery Office (HMSO). This publication, excluding logos, may be reproduced free of charge, in any format or medium for research or private study subject to it being reproduced accurately and not used in a misleading context. The material must be acknowledged as crown copyright and the title of the publication specified. This publication can also be accessed at the National Statistics website: For any other use of this material please apply for a free Click-Use Licence on the Office of Public Sector Information website: or write to The Licensing Division, St Clements House, 2-16 Colegate, Norwich, NR3 1BQ Fax: or [email protected] First published 2005 by PALGRAVE MACMILLAN Houndmills, Basingstoke, Hampshire RG21 6XS and 175 Fifth Avenue, New York, NY Companies and representatives throughout the world. PALGRAVE MACMILLAN is the global academic imprint of the Palgrave Macmillan division of St. Martin s Press, LLC and of Palgrave Macmillan Ltd. Macmillan is a registered trademark in the United States, United Kingdom and other countries. Palgrave is a registered trademark in the European Union and other countries. ISBN This book is printed on paper suitable for recycling and made from fully managed and sustained forest sources. A catalogue record for this book is available from the British Library A National Statistics publication National Statistics are produced to high professional standards as set out in the National Statistics Code of Practice. They are produced free from political influence. About the Office for National Statistics The Office for National Statistics (ONS) is the government agency responsible for compiling, analysing and disseminating economic, social and demographic statistics about the United Kingdom. It also administers the statutory registration of births, marriages and deaths in England and Wales. The Director of ONS is also the National Statistician and the Registrar General for England and Wales. About the Economic and Social Research Council The Economic and Social Research Council is the UK s leading research agency addressing economic and social concerns. The Council aims to provide high quality research on issues of importance to business, the public sector and government. The issues considered include economic competitiveness, the effectiveness of public services and policy, and our quality of life. The ESRC is an independent organisation, established by Royal Charter in 1965, and funded mainly by government. For enquiries about this publication, contact The Editor, David Rose Tel: [email protected] For general enquiries, contact the National Statistics Customer Contact Centre. Tel: (minicom: ) [email protected] Fax: Post: Room 1015, Government Buildings, Cardiff Road, Newport NP10 8XG You can also find National Statistics on the internet at Printed and bound in Great Britain by Ashford Colour Press Ltd, Gosport.

3 The National Statistics Socio-economic Classification: Origins, Development and Use Contents Contents Page List of tables and figures List of abbreviations Preface and acknowledgements v vi vii 1. Introduction 1 2. Recommendations 5 3. Reasons for developing a new government socio-economic classification Why do we need SECs? Problems with the former SECs Criteria for assessing SECs The four phases of the Review The conceptual basis of the NS-SEC The Goldthorpe class schema Creating the NS-SEC Causal narratives The NS-SEC: structure, categories and related measurement issues The structure of the NS-SEC Categories and continuity The NS-SEC operational categories The NS-SEC analytic classes Measurement issues Maintaining the NS-SEC Creating and validating the NS-SEC Measuring employment relations Creating SOC2000 NS-SEC Continuity issues Phase 4 validation studies Conclusions 55 iii

4 Contents The National Statistics Socio-economic Classification: Origins, Development and Use Page Appendices Review Committee membership Continuity issues: SC, SEG and NS-SEC The SOC2000 NS-SEC derivation table: simplified and full methods, operational categories The SOC2000 NS-SEC derivation table: simplified and reduced methods, operational categories The SOC90 NS-SEC derivation table: simplified and full methods, operational categories The SOC90 NS-SEC derivation table: simplified and reduced methods, operational categories Employment relations questions on the LFS The concept of validity in relation to the Review 99 References 107 iv

5 The National Statistics Socio-economic Classification: Origins, Development and Use List of tables and figures List of tables and figures Page List of tables Table 1 Social Class based on Occupation 8 Table 2 Socio-economic Group 9 Table 3 Social Class based on Occupation by NS-SEC operational version 24 Table 4 Socio-economic Group by NS-SEC operational version 25 Table 5 NS-SEC seven-class by sex 35 Table 6 NS-SEC eight-class by sex and nation, aged (Census 2001) 36 Table 7 Frequencies and percentages of NS-SEC seven-class by different methods (LFS 1996/97) 42 Table 8 Frequencies and percentages of the operational version of NS-SEC by different methods (LFS 1996/97) 42 Table 9 SOC2000 NS-SEC by SOC90 NS-SEC (SEC90) seven-class 52 List of figures Figure 1 The conceptual derivation of the NS-SEC 17 Figure 2 Categories of the operational version of the NS-SEC 23 Figure 3 The NS-SEC analytic classes: nine- or eight-class versions 35 Figure 4 NS-SEC operational categories and their relation to the main analytic class variables 38 Figure 5 Projected dominance rules for assigning household NS-SEC 41 v

6 List of abbrevations The National Statistics Socio-economic Classification: Origins, Development and Use List of abbreviations ESRC GHS HIH HRP LFS NS-SEC ONS OPCS OUG RGSC SC SEC SEC90 SEG SOC Economic and Social Research Council General Household Survey Highest income householder Household reference person Labour Force Survey National Statistics Socio-economic Classification Office for National Statistics Office of Population Censuses and Surveys Occupational Unit Group Registrar General s Social Class Social Class based on Occupation Socio-economic classification NS-SEC based on SOC90 Socio-economic Groups Standard Occupational Classification SOC90 Standard Occupational Classification 1990 SOC2000 Standard Occupational Classification 2000 SRS SSEC Service relationship score Simplified NS-SEC vi

7 The National Statistics Socio-economic Classification: Origins, Development and Use Preface and acknowledgements Preface and acknowledgements Much has already been written, not least by us, concerning the National Statistics Socio-economic Classification (NS-SEC). It might therefore be thought that another report constitutes overkill. However, there are two reasons why it was decided that this final report on the work of the Economic and Social Research Council (ESRC) Review of Government Social Classifications was necessary. First, the Office for National Statistics (ONS) required a comprehensive reference volume bringing together in one publication an account of the whole Review. As such, this report is designed as a companion volume to two others: National Statistics Socioeconomic Classification User Manual (ONS 2005) and A Researcher s Guide to the National Statistics Socio-economic Classification (Rose and Pevalin 2003a). Second, our previous report (Rose and O Reilly 1998) presented the interim version of the NS-SEC, based on the Standard Occupational Classification (SOC) of 1990 (SOC90). Following the publication of that report, the SOC was substantially revised and so the NS-SEC had to be rebased on the new SOC of 2000 (SOC2000). No public account of either the full details of the final version of the NS-SEC or its final phase of development has previously been available. In essence, therefore, this report is a substantially revised and updated version of our 1998 report. Inevitably it reproduces some of the content of that earlier report, along with new material relating to the fourth and final phase of the Review. It also summarises some of the content of the two companion volumes. However, those requiring more details on issues such as the derivation of the NS-SEC will need to consult the National Statistics Socio-economic Classification User Manual. Similarly, full details of the NS-SEC validation studies are to be found in the Researcher s Guide. We wish to express our thanks to the Review Committee and all the other colleagues who assisted us with validation studies. We are especially grateful to David Lockwood, who chaired the Review, for his enthusiastic support and critical judgements. Equally, John Goldthorpe and Gordon Marshall gave generously of their knowledge and expertise and helped us to clarify many issues. Without the detailed knowledge of occupational classifications and information given to us by Peter Elias and Tessa Staples, our task would have been far harder. Jean Martin acted as the ONS link person for the Review and made crucial contributions to our research and deliberations. Finally, we wish to thank our colleagues in the Institute for Social and Economic Research, University of Essex, especially Janice Webb, Jenifer Tucker, Kate Tucker, Lindsay Moses, Helen FitzGerald, Judi Egerton, Terry Tostevin, Jane Rooney, Mary Gentile, Jonathan Gershuny and Nick Buck. David Rose David J Pevalin Karen O Reilly March 2005 vii

8 Preface and acknowledgements The National Statistics Socio-economic Classification: Origins, Development and Use viii

9 Introduction Chapter 1

10 Chapter 1 The National Statistics Socio-economic Classification: Origins, Development and Use 1.0 Purpose of this report. This report offers a comprehensive account of the Economic and Social Research Council (ESRC) Review of Government Social Classifications and thus of the development of the National Statistics Socio-economic Classification (NS-SEC). Therefore, it presents not only the final recommendations of the Review Steering Committee (see membership in Appendix 1), but also discusses the reasons why the Review was established, provides an account of the conceptual basis and a full description of the NS-SEC and summarises the research undertaken to create and validate it together with a discussion of its use in research. In a previous report (Rose and O Reilly 1998), we discussed the interim version of the NS-SEC, based on the Standard Occupational Classification (SOC) of 1990 (SOC90). Here we present the final recommended version of the classification based on the new version of SOC, SOC2000 (ONS 2000a and b). 1.1 Structure of the report. In the rest of this chapter we outline the terms of reference of the Review, the aims of each of its four phases and the procedures that have been followed in each phase. Chapter 2 provides a summary of the various recommendations of the Review Committee. Chapter 3 sets out the principal reasons for developing a new government socio-economic classification (SEC). Chapter 4 discusses the conceptual basis of the NS-SEC. Chapter 5 describes the new classification in more detail and discusses various associated measurement issues. Finally, Chapter 6 summarises the research undertaken to create and validate the NS-SEC as a measure. The appendices provide further details. Appendix 2 shows the relationships between the categories of the NS-SEC and those of Social Class based on Occupation (SC) and Socio-economic Groups (SEG), the former government social classifications. Appendix 3 contains the matrix for creating the NS-SEC with SOC2000. Appendix 4 gives the matrix for the reduced and simplified versions of NS-SEC. Appendices 5 and 6 provide similar matrices for NS-SEC using SOC90. Appendix 7 gives details of the questions carried on the 1996/97 Labour Force Survey (LFS) in order to allocate occupational groups to categories of the NS-SEC. Finally, Appendix 8 discusses the background to our approach to validity issues. 1.2 Terms of reference (1). The ESRC Review of Government Social Classifications was established at the instigation of the Office of Population Censuses and Surveys (OPCS, now part of the Office for National Statistics, ONS) in October The Review had the following terms of reference: (1) to review the characteristics, use and perceptions of Social Class based on Occupation (SC) and Socioeconomic Groups (SEG); (2) to review existing alternative social classifications; (3) to propose recommendations for the revision of government social classifications; and (4) to assess the effectiveness of recommended revisions. 1.3 Terms of reference (2). The terms of reference were further elaborated at a meeting between the Review Committee and senior management of ONS. It was made clear that Phase 1 of the Review would be zero-based. Initially, therefore, the Review Committee had to indicate why government social classifications should continue to be produced. This was to be assessed by reference to issues such as who benefits from these government classifications and in what ways. Relevant evidence would include demonstrable direct or indirect benefits to national and local government policy-making and to policy-making in the private sector; the general value which social classifications bring to public statistics and understanding; and the effective use of government classifications in academic research. The remainder of the Review would only proceed if the continued need for government social classifications (or, from now on, socio-economic classifications SECs) could be demonstrated. (For our purposes, we make no distinction between the terms social classification and socio-economic classification : see Rose and Pevalin 2003c: Each is purely a descriptive term, but SEC was eventually preferred by ONS). 1.4 The four phases of the Review. The Review was conducted in four phases with aims as set out in the following paragraphs. A report on Phase 1 was produced in March 1995 (Rose 1995). An interim report on Phase 2 followed one year later (Rose 1996) and the full Phase 2 report was produced in April 1997 (Rose and O Reilly 1997a). An edited volume setting out the work of the Review in more detail (Rose and O Reilly 1997b) accompanied this. In 1998, a more substantial report was produced, containing our interim recommendations for the NS-SEC based on SOC90 and thus included full details of Phase 3 (Rose and O Reilly 1998). Phase 4, described for the first time here, led to the final recommended form of the NS-SEC. 1.5 The aims of Phase 1 were to establish: (1) whether there was a continuing need for government socio-economic classifications; (2) whether there was a need to revise or replace the existing classifications; (3) the criteria for assessing a revised or new classification; and (4) the work required to produce a revised or new classification. 2

11 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter The aims of Phase 2 were: (1) to undertake both the conceptual development and substantive research necessary for deriving a new occupationally-based socio-economic classification; (2) using a variety of relevant datasets, to produce, assess and test an interim version of the classification against both the current government socio-economic classifications and, where possible, existing alternative classifications; (3) to make recommendations to ONS Census Division on the implications of the Review for the design of the census enumeration form; (4) to create an information database on the 371 occupational unit groups (OUGs) of SOC90, one of the principal building blocks for SECs; and (5) to address the transitional arrangements which might be necessary in order to minimise the disruptive effects of introducing a new SEC. 1.7 The aims of Phase 3 were to continue the work of Phase 2 by: (1) analysing LFS data on employment relations and conditions at the OUG level of SOC90 in order to operationalise the new SEC; (2) producing a derivation matrix for the new SEC; (3) bridging the current ONS socio-economic classifications to the new SEC; (4) using a variety of datasets in order to undertake validation studies with the new classification; (5) writing a report on all of this work for ESRC and ONS; and (6) providing users of the new SEC with full details of its conceptual basis and construction. At the conclusion of Phase 3, ONS decided to name the new SEC the National Statistics Socio-economic Classification, NS-SEC. 1.8 The aims of Phase 4 were to consolidate and extend the work of Phase 3 through: (1) further specification of the NS-SEC in both conceptual and operational terms; (2) re-basing the NS-SEC on SOC2000; (3) new validation studies using SOC2000 NS-SEC. 1.9 Procedures in Phase 1. In order to meet its terms of reference, in Phase 1 the Committee invited written evidence from a wide range of organisations central government departments, local authority associations and representatives, government agencies, employers and employees associations, market research organisations as well as from learned societies and individual experts in academia and elsewhere. In addition, the Committee organised meetings with central government users and with academic users and classification experts (see Rose 1995 and 1997). The report on Phase 1 first demonstrated a continuing need for government SECs (see and Rose 1995:2 6); second, it indicated the weaknesses of the existing classifications and developed arguments for replacing them (see and Rose 1995:6 7); and, third, it indicated the criteria for assessing a new classification (see and Chapter 6; see also Rose 1995:10 12 and 16). The report also set out the development work required to produce a new classification (Rose 1995:12 17) Procedures in Phase 2. In line with the recommendations of Phase 1, the Committee created a sub-group to produce a single classification with a clear conceptual rationale, improved population coverage and the necessary associated operational and maintenance rules. Data were collected from three National Statistics Omnibus Surveys in order to undertake preliminary validation of an initial version of the proposed classification. These data were analysed by members of the committee and its various consultants and a book was produced detailing our conclusions (see and Rose and O Reilly 1997b; c.f. O Reilly and Rose 1998c). In addition, as a resource for Phase 3, data on occupations from the 1991 Census and from various government surveys were brought together into a database on the 371 OUGs of SOC90 (see McKnight and Elias 1997). An interim report on Phase 2 was submitted to ONS and it was agreed that a third phase of the review should use specially collected employment relations data from the LFS in order to operationalise a SOC90-based version of the new classification Procedures in Phase 3. Phase 3 involved the analysis of LFS data on employment relations in order to produce a number of potential operational versions of the new SEC for testing. This eventually led to the creation of the interim NS- SEC in its various recommended forms, depending on the quality and extent of employment data available to analysts (see and Rose and O Reilly 1998). This was followed by a series of validation studies (see ). In the process, we produced the necessary matrices incorporating the operational 3

12 Chapter 1 The National Statistics Socio-economic Classification: Origins, Development and Use rules for the different versions of the interim NS-SEC. We also addressed the issue of continuity between SC, SEG and the NS- SEC (see Rose and O Reilly ibid.) Procedures in Phase 4. Having created an interim SOC90- based NS-SEC, we were then faced with the task of re-basing it on SOC2000. This final phase also offered an opportunity to refine the classification in various ways (see ). These refinements were partly induced by the structure of SOC2000, as we explain in Chapters 5 and 6. However, other changes from the Phase 3 interim version were the result of further reflections on the operationalisation of the conceptual base of NS-SEC. In addition, we considered a range of new information on the employment relations of various occupations, some of which were then re-assigned within the NS-SEC. The final version of the NS-SEC is presented in Chapter 5. The results of some of our validation work on the final version are discussed in the final part of Chapter 6. Further details of the validation studies may be found elsewhere (Rose and Pevalin 2003a). In Chapter 4 we offer some advice on the use of the NS-SEC (and c.f. Rose and Pevalin 2003c:36 40). We also assisted ONS in the production of the National Statistics Socio-economic Classification User Manual (ONS 2005, and also available at The user manual should be consulted for further detailed information relating to the procedures for creating and deriving the NS- SEC. 4

13 Recommendations Chapter 2

14 Chapter 2 The National Statistics Socio-economic Classification: Origins, Development and Use 2.0 Here we present all the principal recommendations arising from the four phases of the Review. 2.1 Recommendation 1. Because of the widespread demand from users in government, local authorities, academia and the private sector, the Office for National Statistics (ONS) should continue to produce and maintain socio-economic classifications (SECs). 2.2 Recommendation 2. Given their recognised conceptual and operational deficiencies, Social Class based on Occupation (SC) and Socio-economic Groups (SEG) should be replaced by a single National Statistics Socio-economic Classification, or NS-SEC, based conceptually on an employment relations approach, and uniting the most important features and advantages of SC and SEG. The NS-SEC should have hierarchical or nested properties, that is, it should have an operational version that acts both as a bridge between SC, SEG and the NS-SEC and which can be collapsed in a variety of ways into a smaller number of categories for analytic purposes. Since SEG is closer than SC to a measure of employment relations and conditions, the NS-SEC should, in its operational version, be as similar as possible to the current SEG. In its collapsed version it should resemble SC. 2.6 Recommendation 6. Data on employment relations and conditions at the Standard Occupational Classification (SOC) occupational unit group-level (OUG) should be collected intercensally for the continued validation, maintenance and revision of the NS-SEC. This exercise should ensue any revision of SOC. Attention should also be paid to the possibility of deriving the classification from evidence provided by a sampling and analysis of employment contracts. 2.7 Recommendation 7. The Committee recommends that future revisions of both NS-SEC and SOC should be more closely integrated. 2.3 Recommendation 3. A number of other recommendations are integral to recommendations 1 and 2. First, in order to improve population coverage, and in response to user demand, it is important to include as many as possible of those not in paid employment within the NS-SEC. The Committee therefore recommends that all individuals not currently in paid employment be classified by reference to their last main job. It may be necessary for some purposes to have a special NS-SEC category for the never worked and the long-term unemployed. The Committee therefore recommends that such a category be allowed for in the operational version of the NS- SEC. 2.4 Recommendation 4. It is also recommended that terms such as manual and non-manual and all references to skill be avoided in naming and describing the categories of the NS- SEC. References to skill are inappropriate to the conceptual base of the NS-SEC; and the manual/non-manual divide is simply not a meaningful distinction given the nature of work and occupations in 21st-century market economies. 2.5 Recommendation 5. Users should note the theoretical and thus the measurement principles of the NS-SEC. Like SEG, the NS-SEC is a nominal measure rather than, as with SC, an ordinal one. Ordinality with respect to particular outcome measures should not therefore be assumed and analyses should be performed by assuming nominality. 6

15 Reasons for developing a new government socio-economic classification Chapter 3

16 Chapter 3 The National Statistics Socio-economic Classification: Origins, Development and Use Introduction 3.0 Here we discuss the first term of reference, our review of the characteristics, use and perceptions of Social Class based on Occupation (SC) and Socio-economic Groups (SEG). Evidence arising from Phases 1 and 2 of the Review (covering both the research and other sources on which we based recommendations 1 and 2) has been discussed in previous reports and publications (Rose 1995 and 1996; Rose and O Reilly, 1997a and b). Here we simply reiterate the most salient issues. Why do we need SECs? 3.1 Why do we need SECs?. Before we begin summarising the evidence in support of our recommendations for the replacement of SC and SEG, a brief consideration of the history and principal uses of government socio-economic classifications (SECs) is necessary. This short excursus will help to explain both why official SECs are still needed and why SC and SEG fell short of what is ideally required of an effective SEC. 3.2 Researching health inequalities (1). As Fitzpatrick (2003: 173) has noted: (M)easuring and monitoring socio-economic differentials in mortality and other health inequalities in the UK has been a key part of the work of the office responsible for the registration of deaths since the establishment of the General Register Office (GRO) in The GRO has since been subsumed within the Office for National Statistics (ONS) and it is now ONS that carries on the tradition of reporting on health variations today. This role continues to be of major importance as health inequalities are as much a public health issue today as they were over 150 years ago, when the GRO was set up. 3.3 Researching health inequalities (2). The earliest analyses of mortality differences were undertaken by reference to occupation and industry. However, from the beginning of the 20th century, the development of SC gave a clearer framework for identifying and understanding health differentials within the population. It was demonstrated that there was a class gradient in health in particular in mortality rates and despite the creation of the National Health Service in 1948, class inequalities in health and life expectancy have persisted. Overall, those in partly skilled and unskilled occupations in SC Classes IV and V had far higher mortality rates and lower life expectancy than those in professional and managerial occupations in Classes I and II. 3.4 Researching health inequalities (3). These inequalities are of continuing concern. The UK Department of Health Green Paper, Our Healthier Nation, and the subsequent White Paper Saving Lives: Our Healthier Nation, each acknowledged that health inequalities in the 1990s were actually widening and that the poorest in our society are hit harder than the well off by most of the major causes of death. The Department also gave a firm commitment not only to improve the health of the population as a whole, but specifically to improve the health of the worst off in society and to narrow the health gap. This national pledge complements the aims of the European Health For All Strategy, to which the UK fully subscribed. This made Equity in Health its first target specifically that by the Year 2000 the differences in health status between countries and between groups within countries should be reduced by at least 25 per cent by improving the level of health of disadvantaged nations and groups. Most recently, these concerns have been reiterated in a report by Derek Wanless to the Prime Minister, the Secretary of State for Health and the Chancellor of the Exchequer (Wanless 2004). 3.5 Researching health inequalities (4). As Fitzpatrick remarks: Quantifying the absolute and relative differences in people s health within a population is a prerequisite for developing appropriate strategies to address them Identifying and measuring health inequalities is essential for monitoring public health, for planning and targeting health care services and the distribution of resources, for identifying new and emerging health problems, for assisting in the discovery of causal factors, and for formulating and developing effective health service policies (ibid:174). In all these respects, the SC in particular played a key role. It was devised by T H C Stevenson (1928) and the first published reference appears in the 74th Annual Report of the Registrar General for 1911, issued in From that time it was integral to the analysis of health inequalities and policies designed to tackle them. The original classes of SC comprised groupings of occupations and, in some cases, industries. The final version of SC is given in Table 1. Table 1 Social Class based on Occupation I II III (N) (M) IV V Professional, etc, occupations Managerial and technical occupations Skilled occupations Non-manual Manual Partly skilled occupations Unskilled occupations The occupation groups included in each of these categories were selected in such a way as to bring together, as far as possible, people with similar levels of occupational skill. In general, each occupation group was assigned as a whole to one or other social class and no account was taken of differences between individuals in the same occupation group, for example, differences in education. However, for persons having the employment status of foreman or manager the following additional rules applied: (a) each occupation was given a basic social class; (b) persons of foreman status whose basic social class was IV or V were allocated to Social Class III; (c) persons of manager status were allocated to Social Class II with certain exceptions. 8

17 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter Uses of SC. The GRO itself was thus the initial user of the SC and continued as a major user, as in turn did its successors the Office of Population Censuses and Surveys (OPCS) and ONS. The Scottish GRO was also an important government user. Apart from its use in census reports, decennial supplements, the 1 per cent Longitudinal Study of the Census, and analyses of health inequalities, mortality and fertility, SC was also featured in most of ONS s major social survey reports. Other major users included the Departments of Health; Work and Pensions; Education and Skills; and Environment and the Regions, and the Northern Ireland Office s Policy Planning and Research Unit. SC was also used in many academic studies. Not surprisingly, given its origins, its use was particularly widespread in research on health and mortality (see, for example, Donkin, Goldblatt and Lynch 2002; White et al 2003; Goldblatt 1989; Power et al 1991; Fox and Benzeval 1995; Benzeval et al 1995; Bosma et al 1997; Davey-Smith et al 1997; Manor et al 1997; Davey-Smith et al 1998) and in demography (see Benjamin 1989; Diamond 1989; Murphy 1989; Coleman and Salt 1992). However, for a variety of reasons, academics in disciplines other than health studies and demography have used alternatives to the SC. 3.7 Alternatives to SC. Some choices of alternatives to the SC were no doubt purely contingent and/or conventional, especially in government, but others reflected dissatisfaction with the SC on theoretical, conceptual and technical grounds. This led some researchers (even in health studies) to seek other socio-economic indicators for their analyses (for example, Goldblatt and Fox 1978; Goldblatt 1990; Osborn and Morris 1989). Meanwhile in sociology, where social class is such a crucial explanatory concept, alternative class schemata and occupational scales were derived on what are regarded as more satisfactory theoretical foundations. These alternatives have been reviewed in previous reports (see Rose 1995:9 10 and 38 39; Rose and O Reilly 1997b:Ch.1). 3.8 SEG. One alternative to SC was the second of the UK government SECs. In 1951 a new classification was introduced alongside SC: Socio-economic Groups (SEG see Table 2). In their original form, the SEGs were defined so as to preserve the (then) five social classes. The 1951 SEGs were only used for fertility analyses and did not survive in their initial form for long. In 1960 they were revised to conform to European requirements and the relationship between SC and SEG was lost (see Boston 1984:Ch.3). Although much less discussed in the literature than SC, SEG was a more social scientific measure, one that spoke theory without knowing it. In particular, SEG had an operational requirement to take into account employment status and size of employing organisation as well as occupation. In that sense it came closer than SC to sociological measures of social class such as the Goldthorpe schema (see Chapter 4). When we note that SEG was proposed by a social scientist with an interest in social mobility, David Glass, we can see why this might be the case. Table 2 Socio-economic Group Classification by Socio-economic Group (SEG) was introduced in 1951 and extensively amended in The classification aimed to bring together people with jobs of similar social and economic status. The allocation of occupied persons to SEG was determined by considering their employment status and occupation (and industry, though for practical purposes no direct reference was made since it was possible in Great Britain to use classification by occupation as a means of distinguishing effectively those engaged in agriculture). (1.1) Employers in industry, commerce, etc (large establishments) (1.2) Managers in central and local government, industry, commerce, etc (large establishments) (2.1) Employers in industry, commerce, etc (small establishments) (2.2) Managers in industry, commerce, etc (small establishments) (3) Professional workers self-employed (4) Professional workers employees (5.1) Intermediate non-manual workers ancillary works and artists (5.2) Intermediate non-manual workers foremen and supervisors non-manual (6) Junior non-manual workers (7) Personal service workers (8) Foremen and supervisors manual (9) Skilled manual workers (10) Semi-skilled manual workers (11) Unskilled manual workers (12) Own-account workers (other than professional) (13) Farmers employers and managers (14) Farmers own account (15) Agricultural workers (16) Members of armed forces (17) Inadequately described and not stated occupations 3.9 Uses of SEG. SEG was also extensively used in ONS and government departments and, in modified form, was preferred to SC for General Household Survey (GHS) analyses and reports. It was also employed in many academic studies, although, because there were no rules to guide researchers, it was collapsed to an analytic variable in several different ways. However, some academics preferred SEG precisely because they perceived it as closer to a sociological conception of class than SC. For example, Heath (1995) has noted that, in political analysis, the predictive power of SC was not impressive when compared with either Goldthorpe s class schema or SEG. When collapsed into fewer categories, SEG showed much better systematic and theoretically intelligible variation than SC (for example, own-account workers are distinctive in attitudes and 9

18 Chapter 3 The National Statistics Socio-economic Classification: Origins, Development and Use behaviour from employees in the same occupations, a fact that is comprehensible). Similarly, in reporting results of analyses of British Household Panel Study data conducted for the Rowntree Inquiry into Income and Wealth, Hamnett (1995) observed that collapsed-seg was a good predictor of housing value (see Rose 1997) Need for government SECs. Given their long history and widespread use, it is not surprising that the evidence gathered in Phase 1 demonstrated complete unanimity across central and local government, academia and the private sector that government SECs remained important and necessary analytic tools. Central government departments need them because they provide convenient summaries of complex data relevant to the analysis of social variation and thus to policy formulation, targeting and evaluation, as well as needs assessment. The many area classifications and indices of deprivation used by government departments in determining resource allocation include elements of the classifications. The classifications are also essential for monitoring the health of the population, as we have seen. In the private sector official classifications are a vital element in the creation of area classifications by companies in the market analysis field (see Dugmore 1995). Moreover, the Institute for Practitioners in Advertising s Social Grade schema used in market research and now maintained by the Market Research Society (with categories A, B, C1, C2, D and E see MRS 2003) was itself based on SC. Academic researchers need the classifications for scientific analyses, especially in health, medical, geographic and demographic research. As a further indication of the importance of the classifications to users, they were featured by request in more than Census tabulations. For both government departments and academic users, the long time-series provided by SC in particular was of great value both in the interpretation of social trends and in policy evaluation. For this reason, as demonstrated later, the Review Committee took seriously the issue of continuity between the NS-SEC and both SC and SEG (see Heath et al 2003) Providing an authoritative standard. Finally, not least among the advantages of producing a standard official SEC is that this leaves government in control of definitions and hence of the information that must be collected in order to produce classifications. Since ONS is the main collector and processor of the building block information, it is only sensible that ONS should also determine how data are classified and thereby provide an approved standard for use in all government departments Continued need for occupationally-based SECs. Although critical of both SC and SEG, the Review Committee noted that for both pragmatic and theoretical reasons, occupationally based classifications would continue to remain vital tools for scientific and policy analyses for the foreseeable future. Pragmatically, they are based on routinely and widely collected data and, theoretically, it remains the case that a person s employment situation is a key determinant of life chances (see Chapter 4). Problems with the former SECs 3.13 (1) Social Class based on Occupation. The limitations of a classification that remained substantially unchanged for 80 years are, not surprisingly, legion. SC was correctly described by Marsh (1986a and b) as an intuitive or a priori scale. Especially when we consider that it was created in the context of a 19th century debate between eugenicists and environmentalists, and thus in a time before serious theoretical social science had emerged in Britain (see Szreter 1984), it is not surprising that the SC was considered inadequate by many academic researchers Criticisms of SC. A plethora of articles and book chapters have appeared in the last 25 years calling attention to the problems of SC (see Rose 1994 for more details). Many writers criticised it because they claimed, with Marsh, that it had no coherent theoretical basis. As Thomas (1990) conceded, even the champions of its empirical usefulness agreed on this. Others have demonstrated that what conceptual basis it did have a hierarchy in relation to social standing or occupational skill in fact reflected an outmoded 19th century view of social structure, which can be traced directly to eugenicist ideas (see Szreter 1984; Donnelly 1997) Validity of SC. Even when judged in its own terms, questions were raised regarding the validity and reliability of the SC. For example, Bland (1979) provided cogent evidence that any claim that the SC related to social standing could not be justified. This judgement was also shown to apply to the post-1980 claims that the schema related to a hierarchy of occupational skill (see Gallie 1995). As Thomas argued (1990: 28), those responsible for periodic revision of SC have to make explicit or implicit judgements about the relative position of occupations on the underlying continuum whatever that is considered to be (emphasis added) (2) Socio-economic Groups. The problems that arose with SEG were somewhat different from those of SC. As we have seen, for many sociologists, SEG was regarded as a better measure than SC for social scientific purposes (for example, 10

19 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 3 Hamnett 1995; Heath 1995; Rose 1997). Its 17 groups could be collapsed to produce a schema not dissimilar from that proposed by Goldthorpe (1980) and his associates for their studies of social mobility and class structure. Unfortunately, however, there was no explanation available of the conceptual basis of SEG; and there were no rules to guide researchers on how SEGs might best be collapsed for analysis, hence the many and varied (and often incoherent) ways in which this was done. Like SC, it also relied on outmoded distinctions skill and the manual/non-manual divide. Partly as a consequence of this, it reflected women s positions in the social structure very inadequately, with the heterogeneous SEGs 6 and 7 (respectively junior non-manual workers and personal service workers) being particularly responsible for this. Finally, in terms of its derivation matrix, the logic of the allocation of combinations of OUGs/employment statuses to SEG seemed especially complex and opaque (3) Conceptual rationale. Of greatest concern to the Review Committee was the conceptual weakness of the former SECs. The claim that both SC and SEG lacked a clear conceptual rationale was long-standing, had never been denied and had never been properly addressed by OPCS and its predecessors. We suspect the reason why this particular criticism was disregarded for so long was that, until recently, it had been made almost exclusively by socio-economic classification experts rather than by users of the SECs. Government departments do not explicitly deal in theories of society and therefore are unlikely to demand a clearer conceptual basis, especially if they see SECs merely as pragmatic tools for the reduction and summarisation of complex data. Other users were content to use the SECs without fully appreciating the conceptual issues, even though they might want to ask interesting social scientific questions about the patterns revealed by their results. From the ONS viewpoint, however, the lack of a conceptual rationale for SC and SEG, and thus of clear allocation rules relating to the derivation matrices, made them increasingly difficult to maintain Why a conceptual rationale? We believe that those who use SECs in research, and even the more pragmatic users, should be concerned to know what it is that government classifications are supposed to be measuring so that they can (a) use them correctly; (b) improve their explanation of results; (c) investigate whether the classifications are valid; and (d) maintain and revise them over time. How can we say, for example, what the mortality patterns revealed by SC mean, if we are not clear what SC is measuring? This is no academic quibble. The lack of a clear conceptual rationale has important consequences in limiting the scope for influencing policy. If we do not understand the causal pathways that lead to the regular patterns revealed by research (that is, the processes that generate empirical regularities) then it is not apparent how recommendations can be provided on relevant policy actions to address these persistent variations. Examples include the difficulties encountered in setting targets for reducing health variations that can be linked to achievable policies and, more generally, in developing policies to target deprived groups (such as the partly skilled and unskilled occupations in Social Classes IV and V and those who are involuntarily excluded from the labour force). Of course, we are not suggesting that having a clear conceptual rationale for an SEC removes all the barriers to explaining what class differences mean. Not everything can be explained by what an SEC measures directly and employment is not the only determinant of life chances. However, a properly constructed and validated SEC will remove at least one barrier to explanation when compared to the previous situation. Moreover, we suspect that much of the dissatisfaction with the former classifications discussed earlier was directly related to the failure to provide a clear rationale and all that flowed from this conceptual void, such as how and in what circumstances to use and maintain particular classifications and for what purposes. For these reasons, the Review Committee was convinced that its first concern in Phase 2 had to be with the conceptual rationale for a new classification. We return both to this issue and to others raised in this paragraph in Chapter 4. Criteria for assessing SECs 3.19 Criteria for assessing classifications (1). Precisely because of the need to produce a conceptually sound, reliable and valid measure, throughout the Review we were mindful of the theoretical and methodological issues noted in past discussions of SECs. For example, Fox (1981) posed a series of questions in a paper on alternative measures of social class. He observed that answers to these questions are necessary to the selection of appropriate SECs for particular tasks: To what purpose is the classification to be put? How easily available is the relevant information? To what population is the classification to be applied? How much time and money would it take to build and apply the classification? How much discrimination is obtained by applying different classifications? How much mobility is measured through the different classifications? 11

20 Chapter 3 The National Statistics Socio-economic Classification: Origins, Development and Use 3.20 Criteria for assessing classifications (2). Goldthorpe (1988) similarly suggested criteria for the critical evaluation of SECs. These criteria are: Theoretical derivation: how explicitly and coherently is the classification or scale related to theoretical ideas? Technical derivation: how explicit and replicable is the method through which the classification is produced or scale values determined? Capacity to display variation: how well does the classification or scale identify and display variation in dependent variables, the relationship of which to class or status is of interest? Analytic transparency: how well does the classification or scale, at the same time as displaying variation, help the analyst to see further just how associations or correlations are being brought about? The four phases of the Review (4) the creation of a new matrix relating SOC90 OUGs and employment statuses to the categories of the NS-SEC (see Rose and O Reilly ibid.: Appendix 5); (5) validation studies of the interim (SOC90) version of the NS-SEC (see Rose and O Reilly ibid.: section 5); and (6) bridging and continuity between SC, SEG and NS-SEC (Rose and O Reilly ibid.: section 3) Phase 4. Essentially, Phase 4 involved repeating projects 4 6 above in relation to the new SOC, SOC2000. The results of this work are discussed in Chapters 5 and 6. This led to the production of the final form of the NS-SEC. In the following chapters of this report we reiterate the conceptual model that underpins the NS-SEC (Chapter 4). This discussion will render more intelligible the description of the NS-SEC and our various comments on measurement issues in Chapter 5. Finally, Chapter 6 provides an account of how the NS-SEC was developed and validated Phase 1 recommendations. In light of all the above evidence, the Phase 1 report (Rose 1995) argued the need for a single, occupationally-based SEC to replace the former SECs (that is, in similar manner to SC and SEG, an SEC based operationally on the Standard Occupational Classification, SOC). The new SEC would also require a clear conceptual rationale and therefore be capable of validation both initially and in the future. That is, it was necessary to be clear about what a new SEC was measuring and how in the future to allocate occupations to it as occupational classifications change and as society and the labour market change. Finally, the Phase 1 report also noted that any new SEC should be hierarchical in the sense that a larger number of nominal categories (property of SEG) could be collapsed into a smaller number of categories for analytic purposes (property of SC) Phases 2 and 3. In order to achieve our ultimate objectives, Phases 2 and 3 involved six inter-related projects as discussed in previous reports: (1) advice to ONS on the census design requirements of the SEC (discussed in Rose and O Reilly 1998: Appendix 3); (2) the establishment of a conceptual basis, operational rules and other required properties for the new SEC (Rose and O Reilly, ibid.: sections 3 and 4); (3) as a research resource to the Review, the creation of a database on the 371 OUGs of SOC90, one of the principal building blocks for SECs (see McKnight and Elias 1997); 12

21 The conceptual basis of the NS-SEC Chapter 4

22 Chapter 4 The National Statistics Socio-economic Classification: Origins, Development and Use Introduction 4.0 In terms of its conceptual basis, the NS-SEC follows a well-defined sociological position that employment relations and conditions are central to delineating the structure of socioeconomic positions in modern societies (see, for example, Goldthorpe 2000b and 1997; Erikson and Goldthorpe 1992; and c.f. Goldthorpe 1980; Lockwood 1958/1989). Although not explicitly based on this theory, we have seen that the Socio-economic Groups (SEGs) made distinctions of this kind. Since SEG captured the essential elements of a truly social scientific socio-economic classification (SEC) quite well, it offered a sound starting point for a new SEC. Thus the NS-SEC attempts to make explicit what was latent in SEG categories by reference to employment status characteristics that are widely recognised as significant in the literature (such as mode of payment, promotion prospects and autonomy: see 6.7 and Appendix 7; c.f. Goldthorpe, 1997) and are partially defining features of the Goldthorpe class schema which we shall now explain in more detail. The Goldthorpe class schema 4.1 The Goldthorpe class schema. While operationally similar to Social Class based on Occupation (SC) and SEG (that is, requiring information on occupation and employment status and in some cases size of establishment in order to allocate people to classes) class analysts regard the Goldthorpe schema as having a far more satisfactory theoretical and conceptual basis. The Goldthorpe schema was originally conceived as bringing together into classes individuals who shared similar work and market situations (see 4.3 and also Lockwood 1958/ 1989; Goldthorpe 1980). Subsequently Goldthorpe modified this conception (Erikson and Goldthorpe 1992). He and Erikson now prefer the concept of employment relations in the context of occupations in order to emphasise the idea of a class structure of empty places that individuals fill (Erikson and Goldthorpe 1992; Rose et al 2001). The Goldthorpe schema has been profitably used in many ways: international studies of social mobility (Erikson and Goldthorpe 1992); a major study of class in Britain (Marshall et al 1988); international studies of social justice (Marshall et al 1997) and of health inequalities (Kunst et al 1998a and b); and, in revised form, in recent British Election Studies (for example, Andersen and Heath 2002; Heath et al 1985). In addition, a series of studies have endorsed the basic validity of the Goldthorpe schema (for example, Evans 1992, 1996; Birkelund et al 1996; O Reilly and Rose 1998c; Evans and Mills 1998 and 2000). 4.2 Basic positions. The primary distinctions made in Goldthorpe s approach are those between: (1) employers, who buy the labour of others and assume some degree of authority and control over them; (2) self employed (or own-account ) workers who neither buy labour nor sell their own to an employer; and (3) employees, who sell their labour to employers and so place themselves under the authority of their employer. Thus any class schema based on employment relations, that is, that defines positions in terms of social relationships at work, must include these three basic class positions. Why these basic positions exist should be obvious for any society based on the institutions of private property and a labour market. However, we can immediately note that Goldthorpe s distinctions separately identify the self-employed, a category that was egregiously absent from SC. 4.3 Employment regulation. Employees account for anything up to 90 per cent of the active working population. Clearly, they do not all hold similar class positions. That is, employers do not treat all employees alike in respect of their relations with them as defined by the explicit and implicit terms of employment contracts. There is differentiation in employers relations with employees. Thus, crucial to Goldthorpe s conception is a further level of distinction within the employment relations of employees. To observe that there are quite diverse employment relations and conditions among employees is another way of saying that they occupy different labour market situations and work situations (Lockwood 1958/1989) as expressed through employment contracts. Labour market situation equates to issues such as source of income, economic security and prospects of economic advancement. Work situation refers primarily to location in systems of authority and control at work, although degree of autonomy at work is a secondary aspect. Hence, in this conceptual construction, variation in employment contracts provides the main basis for establishing its construct validity (see Chapter 6 and Appendix 8). That is, membership of the classes it distinguishes, as well as having differing sources and levels of income, also have differing degrees of stability of both income and employment and differing expectations as to their economic futures that together condition both their life chances and many aspects of their attitudes and patterns of action (Goldthorpe 2000a: ). The Goldthorpe schema thus distinguishes broadly different positions (not persons) as defined by social relationships in the work place that is, by how employees are regulated by employers through employment contracts (Goldthorpe 2000b). Three forms of employment regulation are distinguished. 4.4 The service relationship. First, there is the service relationship in which the employee renders service to the employer in return for compensation in terms of both 14

23 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 4 immediate rewards (for example, salary) and long-term or prospective benefits (foe example, an occupational pension, assurances of security and career opportunities). This relationship is likely to be found where it is required of employees that they exercise delegated authority or specialised knowledge and expertise in the interests of their employing organization (Erikson and Goldthorpe 1992:42 emphasis in the original). Therefore, within this relationship, employers must allow a certain amount of autonomy and discretion to the employee. Equally, employees must be encouraged to make a moral commitment to the employing organisation. The service relationship is designed to create and sustain this type of commitment. The service relationship typifies higher professional, senior administrative and senior management occupations. This is where the largest responsibilities in decision-making attach and which will in turn offer the fullest range of beneficial conditions associated with the service relationship (ibid:43). However, the service relationship is also found in a more restricted or attenuated form in lower professional and managerial occupations, as well as in higher technical occupations. 4.5 The labour contract. In contrast with the service relationship, the labour contract entails a relatively short-term exchange of money for effort. Employees are closely supervised and give discrete amounts of labour in return for a wage (or nowadays even a salary in the limited sense of a direct payment to a bank account). Payment is calculated on or related to the amount of work done or required or by the actual amount of time worked. The labour contract is typical of working class occupations, but again is found in attenuated forms, for example for supervisors and skilled workers. That is, these occupations have slightly more favourable employment terms than others in the working class where external controls can be fully effective. 4.6 Intermediate or mixed forms of employment regulation. These combine aspects from both the service relationship and the labour contract. Intermediate forms of regulation are typical for clerical occupations, as well as for some technical, sales and service occupations. They are especially prevalent in large, bureaucratic organisations. 4.7 Further comments on employment regulation. The contrast between the service relationship and the labour contract is ideal-typical. In the real world, actual employment relations may only approximate these types. Goldthorpe (2000b) discusses the reasons why these forms of employment regulation exist and are common across countries with developed market economies. Briefly, two factors are implicated in determining the form of employment regulation: (1) the degree to which work may be monitored by the employer (external controls); and (2) the specificity of human capital used by employees in their jobs. Thus, where employers have difficulty in monitoring the work of employees and employee human capital is high, a service relationship will exist. Where work is easily monitored and controlled and where human capital of employees is low, a labour contract will exist. Erikson and Goldthorpe (1992:42) have noted that the distinction between the service relationship and the labour contract is similar to some conventional distinctions made in several European countries. France, of course, distinguishes between cadres or employés and ouvriers; Germany between Beamte or Angestellte and Arbeiter; and the UK between staff and workers. Even if the latter distinction now sounds outmoded, evidence for the continuing relevance of the service relationship/labour contract distinction is clear (see, for example, Goldthorpe and McKnight 2003 and Chapter 6). 4.8 Employers and the self-employed. The Goldthorpe schema also separately identifies categories for the other two basic class positions discussed in 4.2: employers and the selfemployed. Employers are divided between large and small. The distinction here is between employers who delegate at least some managerial tasks ( large ) and those who tend to undertake these tasks themselves ( small ). The former are allocated to the same class as higher professionals and senior managers (Class I) and the latter to the self-employed class (Class IV). Because of their different market and work situations, Goldthorpe also distinguishes between professional and non-professional small employers, in his classes I and IV respectively. This consideration also applies to the selfemployed. 4.9 Choosing Goldthorpe s approach. The decision to adopt (but adapt through thorough ex ante validation) the Goldthorpe schema as the basis for the NS-SEC was made precisely because the former is widely used and accepted and is conceptually clear. Moreover, it has been very reasonably validated ex post facto both in criterion terms as a measure and (importantly from the viewpoint of any proposed government SEC) in construct terms as a good predictor of health and educational outcomes. In terms of its conceptual basis, therefore, the NS-SEC follows that of Goldthorpe s schema as just described. However, the NS-SEC is not identical to the Goldthorpe schema, but is an adaptation of it. 15

24 Chapter 4 The National Statistics Socio-economic Classification: Origins, Development and Use Creating the NS-SEC 4.10 Creating the NS-SEC. Although the Economic and Social Research Council (ESRC) review team adopted the Goldthorpe schema as its model, it did not accept its current instantiation. Unlike Goldthorpe, we were able to undertake ex ante validation. Thus, the NS-SEC was created by analysing employment relations data, especially collected on the Labour Force Survey (LFS see Chapter 6 and Appendix 7), and applied to the unit groups of the Standard Occupational Classification (SOC). Each NS-SEC class brings together combinations of occupational groups and employment statuses that share similar employment relations, but are different in these terms from those in the other classes (c.f. Bailey 1994) Operational requirements. Although we have specified a new SEC to replace SC and SEG, its operational requirements are basically unchanged from those used for the old classifications. The data required and the method used for creating the NS-SEC from the Census and from social surveys are the same as was required for SC and SEG (and, indeed, for the Goldthorpe schema), that is, data on occupation, organisation size and employment status. The derivation matrices in Appendices 3 6 provide users with the information needed to create the NS-SEC in all its variants (as discussed in Chapter 5) and with both SOC2000 and SOC90 (see 6.35 and Table 9 below). The National Statistics Socio-economic User Manual (ONS 2005) provides further details on these matters. As explained in the manual, priority rules are used to fill empty cells in the matrices. These cells are empty because they are deemed to have incompatible or non-allowable combinations of occupation code and employment status code. However, in Appendices 3 6 we have filled the empty cells with NS-SEC values using the priority rules. The equivalent matrices in the User Manual are shaded to show which cells have been treated in this way Basic socio-economic positions. Figure 1 offers a diagrammatic representation of the way in which the NS-SEC is derived. We shall describe this classification in more detail in the next chapter. As with the Goldthorpe schema, the primary distinction made by the NS-SEC is between employers, employees and the self-employed. To these we added a fourth basic position for those who are involuntarily excluded from employment relations altogether. However, as we have seen, such a primary classification is not exhaustive, as Figure 1 shows Employers and the self-employed. Modern corporate forms of property mean that most employers are organisations rather than individuals. The individual employers who do remain are largely small employers (L8 in Figure 1), but an SEC needs to recognise both them and the tiny proportion (0.1 per cent) of larger individual employers (L1), few of whom today are heroic capitalists. Similarly the self-employed without employees (L9) occupy a distinctive position and must be kept separate from employees Employees. The category of employees has both grown and become more differentiated within bureaucratic enterprises. As we have noted, employees occupy a very wide range of market and work situations, that is, their employment relations and conditions are sufficiently variable that we can make meaningful distinctions between them in class terms. In terms of these distinctions, we have followed the crucial line of division made by Goldthorpe, and depicted in Figure 1, between employment relations and conditions based on a service relationship and those based on a labour contract. The latter typifies positions in the working class (L12 and L13). The former typifies managerial, professional and administrative positions (the service class or salariat ), notably in categories L2 and L3. In practice, of course, members of the lower salariat (L4, L5 and L6) have less of the full range of conditions associated with the service relationship; and some members of the working class have a more relaxed form of the labour contract (L10 and L11). In addition, there are intermediate groups routine clerical workers, for example who have a mixed form of employment regulation between the service relationship and the labour contract (as in L7). All these points will become more apparent as we explain the NS-SEC in more detail in the next chapter. Before we do this, however, let us consider the importance and consequences of having a classification with a clear conceptual rationale. Causal narratives 4.15 Causal narratives. Why do we need an SEC conceived and constructed in the manner set out here? In we explained our concerns with the old SECs in terms of their lack of a clear and explicit conceptual rationale. One of the strengths of the approach we took in the Review, indeed its underlying principle, is that the NS-SEC offers not necessarily improved statistical associations over the former SECs, but that it lends itself to the possibility of explaining the associations we find. Because we know the NS-SEC is measuring employment relations and conditions, that is, aspects of work and market situations and of the labour contract, we can construct causal narratives which specify how the NS-SEC links to a range of outcomes via a variety of intervening variables (see Marshall 1997:21 22; Wilkinson 1997:593; Breen and Rottman 1995; and Rose and Pevalin 2003a: Parts 2 and 3). 16

25 17 Figure 1 The conceptual derivation of the NS-SEC Basic SEC Positions EMPLOYERS SELF-EMPLOYED WORKERS EMPLOYEES EXCLUDED Form of employment regulation Large Small SERVICE RELATIONSHIP INTERMEDIATE LABOUR CONTRACT Professional Clerical Services Tech- Engin- Super- Tech- Semi Routine Never Unem- Managerial, nical eering visory nical Routine Worked ployed etc Higher Lower Higher Lower Other Higher Lower Agric. Other Higher Lower Agric. Other Prof. Man. Prof/ Man. Sup. prof/ prof. prof/ prof. prof/ prof. Tech. Tech. Tech. Tech. Operational L3 L1 L1 L3 L4 L8.2 L8.1 L3 L4 L9.2 L9.1 L3 L2 L4 L5 L6 L7.1 L7.2 L7.3 L7.4 L10 L11 L12 L13 L14.1 L14.2 Nine Eight Five Three The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 4

26 Chapter 4 The National Statistics Socio-economic Classification: Origins, Development and Use This was decidedly not the case for SC and SEG, since it was not clear what they measured. They may have shown statistical associations with dependent variables of interest, but they did not lend themselves to causal explanations (see, for example, Fitzpatrick et al 1997). They had neither a clear theoretical derivation nor analytic transparency The example of health inequalities. We can illustrate our point by returning to the example of health inequalities, which as we saw in Chapter 3 is extremely important in terms of the need for government SECs. One of the major uses of SECs has been in studies of fertility, morbidity and mortality, that is, as a means of obtaining a macro or societal perspective on these issues. The NS-SEC defines structural positions that can be seen conceptually to exist independently of the individuals who occupy those positions at any particular time. The positions condition and shape the lives and the life chances of their occupants. That is, the life chances of individuals and families depend mainly on their position in the division of labour and on the material and symbolic advantages that derive from it. Thus, for example, health inequalities are differences between class positions in respect of morbidity and mortality. By analysing the relationships between the NS-SEC and health indicators, we can reveal how different types of employment relations and conditions affect health outcomes. That is, we can render more visible the socio-economic factors which affect health outcomes (see, for example, Arber and Cooper 2003; Fitzpatrick 2003; Bartley et al 1998; Fitzpatrick et al 1997). We are therefore linking health with social organisation. This is vital for a range of public policy and monitoring issues (for example, World Health Organisation and UK government targets for reducing social differences in health) Alternatives to social class. Of course one can use other independent variables than class to study health and other outcomes of interest, for examples, income, education, housing, consumption, but none of these alternatives is designed to capture the basic structuring principles of society in the way that social class does. Thus when we pose questions about how the social structure shapes outcomes, social class is of prime importance. Moreover we need to keep the idea of social class analytically distinct from the possible consequences which the occupancy of a position may give rise to, for example, income or housing. This will allow us to examine the mechanisms that link class to outcomes. The same is true for individual attributes that are necessary for the occupation of positions, for example, education or skill level. Therefore, SECs should not be based on measures of skill, for example, although they will tend to correlate highly with it (see, for example, Gallie 1995) Analytic issues (1). Thus, when it comes to analysis using the NS-SEC (or any similar measure) there seem to us to be three issues which must be considered. First, of course, we accept that there may be situations where, for example, the class mortality relationship might reduce or disappear when other variables are introduced into a model. Equally, however, we need to be clear about what this might mean. Second, we also have to think of the basic modelling and measurement issues, that is, are our procedures technically correct and appropriate to the problem? For example, we should be careful in our analyses not to set up a variable race between different independent variables that do not have a common metric (see, for example, Breen and Goldthorpe 1999:7). Third and most importantly, we have to think theoretically before we think statistically. We need an explicit causal or explanatory narrative formed into testable hypotheses about the class mortality relationship. In this regard, we would argue that variables such as housing tenure and income are themselves conditioned by class. It could certainly be argued that class might have direct relations with aspects of health; but it might also be mediated via the life chances that derive from class position. Introducing life chance or deprivation measures into a model investigating the class health relationship could then be expected to reduce the direct effects of class, but it would be a mistake then to conclude that this reduces the contribution which class makes to our understanding of health outcomes. On the contrary, such a finding would be in line with a class causal narrative. Therefore we need first to think not of relations between variables, but of social relationships and class is, of course, a crucial form of social relationship. This is why we are not impressed by research which is merely concerned with the predictive power of different socioeconomic measures, as in the case of statistical associations between alternative measures of socio-economic position and health outcomes (see, for example, Macintyre et al 2003). What we observe about socio-economic position does not depend only on how we measure it, as Macintyre and her colleagues suggest, but crucially on how we conceptualise and theorise it. That is, as paragraph 4.15 implies, we are not only concerned with the ability of a measure to display variation in dependent variables of interest, but also in its theoretical derivation and its analytic transparency (see 3.20 above). Thus, while social class gradients in outcomes such as health may be very appealing to analysts, they can also be misleading. We urge researchers to consider some of the new ways of thinking about old issues that the NS-SEC offers. We shall have more to say about both the measurement issues surrounding 18

27 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 4 the NS-SEC (see ) and the novel findings obtained through its use ( ) Analytic issues (2). Nor should we take the narrow view that class is only about the employment relations that the NS- SEC directly measures. That is not the case either. As we explain in Chapter 6, we were only able to measure a small sub-set of a potentially wider range of employment relations variables. This sub-set was used to assist us to validate the class variable, but we should not then suppose that they must alone explain how class relates to dependent variables of interest. And, as we have just noted, there are in any case life chances which flow from people s work and market situations (or employment relations ), including housing and income, as well as other aspects of material circumstances Income and class. In this respect, therefore, we would also argue that the use of SECs in research is not simply to act as a proxy for income where income data themselves are unavailable. We use SECs because they are measures designed to help us identify key forms of social relations to which income is merely epiphenomenal. Hence, again, the need for thinking theoretically before thinking about appropriate forms of analysis. It is also the case that SECs are relatively more general and stable measures than income. Income is well known to fluctuate over the lifecourse; indeed the British Household Panel Survey data reveal a high level of income churning from year-to-year (Jenkins and Jarvis, 1997; and see also Coburn 2004). What the NS-SEC might reasonably be expected to proxy is the lifecourse/earnings profile and it does (see Goldthorpe and McKnight 2003). However, absolute income is by no means a straightforward determinant of health or mortality. Health inequality is linked to relative deprivation, relative income, relative poverty indeed the very concept of inequality is inherently relative (see Marshall and Swift 1996: 376). Studies which show that, contrary to popular belief, it is those at the bottom of employment hierarchies who are most stressed (Marmot et al 1991 and 1997; Bosma et al 1997; and c.f. Davey-Smith et al 1997). Similarly, Goldthorpe (1996), Jonsson (1993) and Jonsson et al (1996) have demonstrated the capacity of a classification such as the NS-SEC to display variations in educational attainment of a theoretically expected kind Specifying class effects. What we require, therefore, are more multivariate analyses that show how class effects are mediated via specific intervening variables. This approach will go far in meeting certain criticisms of class analysis (see, for example, Pahl, 1989 and 1993). How class has its effect will vary according to what it is we wish to explain. We must thus construct and test different models designed to link a range of different outcomes with what the NS-SEC and its components measure, in similar manner to the validation studies discussed in Chapter 6 (and c.f. Rose and Pevalin 2003c:38 40). With this conceptual background in mind, we now turn to a description of the NS-SEC and associated measurement issues The Whitehall Studies. Breen and Rottman (1995:467) have pointed to the need to hypothesise and test a number of different intervening variables that would represent alternative mechanisms linking class and outcome, that is, specifying causal narratives (and see also Wilkinson 1997). For example, there is growing evidence that the amounts of control and autonomy a person has at work are important factors in explaining heart disease (Bosma et al 1997). The service relationship s prospective perspective associated with secure, career employment among top managers and professionals has components such as greater control and autonomy at work, more self-esteem, greater self-care with regard to factors such as diet and exercise, more choice over medical treatment and so on. This we have learned, for example, from the Whitehall 19

28 Chapter 4 The National Statistics Socio-economic Classification: Origins, Development and Use 20

29 The NS-SEC: structure, categories and related measurement issues Chapter 5

30 Chapter 5 The National Statistics Socio-economic Classification: Origins, Development and Use Introduction 5.0 In this chapter, first we describe the structure of the NS- SEC and some basic issues of nomenclature. Second, we show the relationship of the NS-SEC to Socio-economic Groups (SEG) and Social Class based on Occupation (SC). Third, we discuss theoretical, conceptual, operational, face validity and continuity issues in relation to each of the categories of the operational version of the NS-SEC, including rules for dealing with the non-employed. Fourth, we address the methods by which the classification may be collapsed for research purposes and measurement issues in relation to the collapsed versions. Fifth, we present details of reduced and simplified versions of the NS-SEC for use with registration and other data where not all elements in the operational algorithm for the classification are available. Sixth, we discuss the version of the NS-SEC developed for use on self-completion surveys. Finally, we discuss general maintenance rules. Further details may be found in the User Manual (ONS 2005). The structure of the NS-SEC 5.1 The structure of the NS-SEC. The operational categories and sub-categories of the classification, depicted in Figure 2, have two purposes. First, they are the principal means by which we translate between both SC and SEG and the NS-SEC (see Appendix 2). Second, categories have been designed to offer researchers maximum flexibility in terms of different possible and allowable collapses (within the underlying conceptual model of employment relations) to nine, eight, seven, six, five and three category analytic class variables, as discussed later in this chapter (see ). The flexibility of this nested structure even allows analysts to use the categories of the operational version to look inside the classes of the analytic versions. Categories and continuity 5.2 Operational categories. The operational categories (indicated in bold in Figure 2) represent a variety of labour market positions and employment statuses which can be collapsed into analytic classes as defined by an employment relations approach (see Goldthorpe 1997). The prefix L for the operational categories indicates long version, our original term for what is now termed the operational version. L14 is an optional category. L15, L16 and L17 are the residual categories that are excluded when the classification is collapsed into classes (see below). All the sub-categories in the operational version are component codes required for bridging and continuity to SC and SEG rather than necessary sub-categories in terms of the conceptual base of the NS-SEC. For example, L3 is sub-divided between positions which were recognised by both SEG and SC as professional traditional professionals and those (for example, computer analysts) which now appear to be professional positions on the basis of research conducted to produce the NS-SEC new professionals. L4 is equivalently treated in terms of lower professional positions (or what SC termed technical occupations in class II and SEG 5.1 referred to as ancillary workers ). Similarly, L7, L8, L9, L11, L12 and L13 are also sub-divided to aid continuity with the former socioeconomic classifications. 5.3 NS-SEC category names. Except in the three-class variant, none of the category names in any of the versions of the NS- SEC makes reference to either skill or the manual/nonmanual divide. This is quite deliberate, of course. The concept of skill has no part in the conception of the NS-SEC and so to use category names that refer to it would be inconsistent with an employment relations approach. As for the manual/non-manual divide, changes in the nature and structure of both industry and occupations has rendered this distinction both outmoded and misleading. Although it might be argued that no great importance needs to be attached to category names or class labels, nevertheless conceptually neither the degree of manuality of the work involved nor its skill level are considerations that should determine the allocation of occupation-by-employment units to classes (Goldthorpe 1997:48). And, as we shall see, empirically the relationship between the manual/non-manual divide and the labour contract/service relationship distinguished by an employment relations approach is less than is generally perceived. Consequently what were previously referred to in SEG as intermediate, junior or skilled non-manual occupations now become, respectively, lower professionals or higher supervisors, and intermediate or semi-routine occupations. Skilled, partly skilled and unskilled manual occupations in SC become respectively lower technical, semi-routine and routine occupations. Further details are in Appendix Categories, concepts and continuity explained. We now turn to a description and discussion of the NS-SEC operational categories. For each category, the following paragraphs present (a) category descriptions, and thus face validity issues the degree to which categories make intuitive sense; (b) conceptual and operational issues; and (c) continuity with SC and SEG, for which it was necessary to create SOC2000 derivation matrices for the former classifications (see 6.26; and see also Heath et al 2003, Elias 1997, Martin 1997). 22

31 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 5 Figure 2 Categories of the operational version of the NS-SEC L1 Employers in Large Organisations L10 Lower Supervisory Occupations L2 Higher Managerial Occupations L11 Lower Technical Occupations L11.1 Lower technical craft occupations L3 Higher Professional Occupations L11.2 Lower technical process operative occupations L3.1 Traditional employees L3.2 New employees L12 Semi-routine Occupations L3.3 Traditional self-employed L12.1 Semi-routine sales occupations L3.4 New self-employed L12.2 Semi-routine service occupations L12.3 Semi-routine technical occupations L4 Lower Professional and Higher Technical Occupations L12.4 Semi-routine operative occupations L4.1 Traditional employees L12.5 Semi-routine agricultural occupations L4.2 New employees L12.6 Semi-routine clerical occupations L4.3 Traditional self-employed L12.7 Semi-routine childcare occupations L4.4 New self-employed L13 Routine Occupations L5 Lower Managerial Occupations L13.1 Routine sales and service occupations L13.2 Routine production occupations L6 Higher Supervisory Occupations L13.3 Routine technical occupations L13.4 Routine operative occupations L7 Intermediate Occupations L13.5 Routine agricultural occupations L7.1 Intermediate clerical and administrative occupations L7.2 Intermediate service occupations L14 Never Worked and Long-term Unemployed L7.3 Intermediate technical and auxiliary occupations L14.2 Long-term unemployed L7.4 Intermediate engineering occupations L15 Full-time Students L8 Employers in Small Organisations L8.1 Employers in small organisations in industry, L16 Occupations not stated or inadequately commerce, services, etc. described L8.2 Employers in small organisations in agriculture L9 Own-account Workers L9.1 Own-account workers (non-professional) L9.2 Own-account workers in agriculture L17 Not classifiable for other reasons In the case of continuity, Table 3 cross-tabulates SC by NS-SEC, using data from the Labour Force Survey (LFS) 1996/97 winter quarter. Thus it shows the relationship between SC categories and each of the operational categories of the NS-SEC. Therefore it also provides the method for calculating how well SC can be derived from the NS-SEC. The bold cells of the table show that, if each NS-SEC operational sub-category is assigned to SC based on the highest percentage within the columns of the table (for example, NS-SEC L2 is assigned to Social Class II, NS-SEC L3.1 to Social Class I and so on), 87.5 per cent of cases can be allocated to the correct SC category. Table 2 gives the same information for SEG by the NS-SEC. Once again the bold cells show those which would be assigned correctly if an operational NS-SEC sub-category is assigned to an SEG category based on the highest percentage of congruent cases. For SEG, 87.1 per cent of cases are correctly allocated. Further references will be made to extracts from these tables as we describe each of the NS-SEC operational categories. The NS-SEC operational categories 5.5 L1 Employers in large organisations Employer positions occupied by persons other than professionals where the incumbents employ others (and thus assume some degree of control over them), and delegate some part of their managerial and entrepreneurial functions onto salaried staff, in enterprises employing 25 or more persons. 23

32 Chapter 5 Social Class based on Occupation by NS-SEC operational version Col % * The National Statistics Socio-economic Classification: Origins, Development and Use 1.5 * Social NS-SEC Class Table 3 I 11 2, II 49 2, , , IV IIIN ,413 4,830 2, IIIM V * VI * 6.4 Col % Social NS-SEC Class I II 1, IIIN , * IIIM 2,009 3,129 1, , IV ,120 1, ,281 1, * * V , * * 72.8 VI Agreement 55305/63226=87.5% Social Class VI = Armed Forces. 24

33 25 Table 4 Socio-economic Group by NS-SEC operational version Col % Socio-economic NS-SEC group S * 1.2 2,500 1, , , , , * ,413 * ,830 2, * * * * 6.4 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 5

34 26 Table 4 (continued) Socio-economic Group by NS-SEC operational version Col % Socio-economic NS-SEC group * , , * , , , , , ,309 1, , * * , * * , * Agreement 55059/63226=87.1% Chapter 5 The National Statistics Socio-economic Classification: Origins, Development and Use

35 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 5 Conceptual and operational issues. As we have seen, a primary distinction in Goldthorpe s employment relations approach is that between employers, who buy the labour of others and thus assume some degree of authority and control over them; self employed (or own-account ) workers who neither buy labour nor sell their own; and employees, who sell their labour to employers. Goldthorpe (1997:41) suggests that employers are further divided into large and small, in order to reflect important differences between those who individually, or with the help only of family members, carry out all the entrepreneurial and managerial functions of their concerns ( small ) and employers who, while remaining in charge of unincorporated concerns, devolve some part of these functions onto salaried staff ( large employers, as described in this category of the NS-SEC). Higher professionals in L3 who are also large employers are not included in L1, however. This is because their status as professionals is more relevant in terms of employment relations than their position as an employer. Small employers (unless professionals) are in category L8. Those who are self-employed non-professionals without employees are referred to in the NS- SEC as own-account workers and are in L9. Operationalising the distinction between large and small employers has consisted, to date, of applying a size rule cut-off of 25 employees. Individual employers in organisations with 25 or more employees are deemed to own large organisations; those owning enterprises below this threshold are classified as small employers. While this pragmatic rule is not entirely satisfactory, there are good reasons for retaining it: analysis of LFS data suggests that it is a sensible cut-off for managers (O Reilly 1997b); and using the 25-employee rule retains continuity with SEG. How is the employing organisation defined? In both government social surveys and the Census, organisational or establishment size is related to the workplace, that is, the local unit of the establishment at which the respondent works (see GSS 1996:45). However, the Review Committee would prefer that organisation or establishment should refer to an enterprise as defined in the Inter-Departmental Business Register (IDBR) and not to a local unit (see ONS 1998:3). Thus, in our view, local unit or workplace should only be used faute de mieux, that is, if it is impossible or impractical to obtain information at the level of the enterprise. It should be noted that, for the most part, the category of large employers is not dealing with the leaders of industry or the Sunday Times Rich List. In fact according to our LFS data 62 per cent of respondents in this category own enterprises with less than 50 employees. And the most common occupations, accounting for almost 50 per cent of L1, are employers in marketing and sales, restaurant owners and other service industry proprietors. Once a business becomes incorporated it is often difficult to disentangle ownership and control. Directors of large public companies usually have shareholdings, and thus are part owners, but they will generally describe themselves as employees working in senior management or administrative positions and thus will be classified to L2. This is one reason why the inclusion of large employers and senior managers in the same basic class of collapsed versions of the classification makes some sociological as well as pragmatic sense (and see 5.24 and 5.26). Continuity issues. Table 1 shows that those in category L1 were in Social Classes II, IIIN, IIIM, IV and V. This is because SC did not recognise self-employment: the self-employed and employers were classified by SC as if they were employees. However, in terms of cases, 77 per cent of those in L1 are drawn from Social Class II managerial and technical occupations. Social Class II IIIN IIIM IV V Total L It might be expected that L1 would exactly match SEG 1.1 ( employers in large establishments ) and it can be seen that for the most part it does. However, while the NS-SEC consistently allocates all employers in large organisations (except professionals) to L1, SEG was not quite so consistent. Some large employers were placed in SEG 5.1 ( ancillary workers and artists ). SEG Total L L2 Higher managerial occupations Positions in which there is a service relationship with the employer, and which involve general, higher level or executive planning and supervision of operations on behalf of the employer. Conceptual and operational issues. In terms of an employment relations approach, higher managers (along with higher professionals) have a service relationship with their employer, as distinct from a labour contract. As we saw earlier, the service relationship is one in which employees are required to exercise delegated authority, specialisedknowledge or expertise in the interests of their employer. 27

36 Chapter 5 The National Statistics Socio-economic Classification: Origins, Development and Use The interim version of the NS-SEC retained the distinction between managers in large and small establishments which SEG applied but which SC did not recognise. In terms of an employment relations approach, initially in the interim NS-SEC we followed Goldthorpe in deeming all managers in large organisations to be equivalent to senior managers and administrators in Class 1. In fact what employment relations approaches (and we assume SEG) really wish to distinguish is higher from lower level managerial positions, not whether a manager is in a large or small organisation. This conceptual distinction between higher and lower level managers is operationalised more satisfactorily in the final version of NS- SEC. Because SOC2000 has a more refined and restricted definition of managerial occupations, we were able to identify some managerial occupational unit groups (OUGs) that are in effect wholly or mainly occupied by junior or middle managers. Hence, these OUGs are now allocated to L5 (lower managerial) regardless of organisation size. This is more in keeping with the underlying conception. It must be recognised that, as in the case of L1, the operational distinction by size is always faute de mieux. As Goldthorpe (1997:47) notes: while small enterprises may not have many higher level managers, large enterprises are of course likely to have many lower level managers. The NS-SEC is thus rather better operationalised for managers using the new method. Continuity issues. The NS-SEC attempts to place all higher managers in L2. SC operated in similar fashion, most managers being in Social Class II. Thus, 97 per cent of cases in L2 are common to Social Class II, managerial and technical occupations. However, some (very senior) managerial positions in the civil service were in Social Class I ( professional etc occupations ) and senior officers in the armed forces were separately treated and analysed in SC. Social Class I II Armed Total Forces L2 * In this and all subsequent tables * = Less than 1% L2 approximates but does not entirely match SEG 1.2 ( managers in large establishments ). Like SC, SEG had some managers in a special armed forces category (SEG 16), in order to separately identify this group. The NS-SEC has not followed this practice because of the small numbers involved (see ONS 2005). Members of the armed forces included in L2 are all officers in OUG The 3 per cent of L2 that were in SEG 2.2 ( managers in small establishments ) are accounted for by the changed operation of the organisation size rule for managers. SEG Total L L3 Higher professional occupations L3.1 Traditional professional employees that is, previously defined as professionals by social class and SEG L3.2 New professional employees that is, not previously defined as professionals by social class and SEG L3.3 Traditional self-employed professionals that is, previously defined as professionals by social class and SEG L3.4 New self-employed professionals that is, not previously defined as professionals by social class and SEG Positions, whether occupied by employers, the self-employed, managers or employees, covering all types of higher professional work. Employees in these groups have a service relationship with their employer. Conceptual and operational issues. Goldthorpe s schema does not distinguish between higher professionals and higher managers. Both categories are in one class in which employees are regulated by a service relationship rather than a labour contract. Thus much of what we have said about employment regulation for higher managers in L2 applies equally to higher professionals. However, the NS-SEC retains the SEG and SC distinctions between managers and professionals for reasons of continuity and flexibility. We are also aware that some users will wish to analyse managers and professionals separately. The issue as to whether, in fact, managers and professionals are in the same class position is an open one (see for example Savage et al, 1992, Butler (ed.) 1995 and Mills and Evans 2003). Purely for continuity reasons, we follow SEG in making a distinction in L3 between self-employed and salaried professionals. However, it should be noted that for professionals independent practice and salaried employment are often indistinguishable, and true self-employment is difficult to identify. Similarly, and as is currently the case with SC, an OUG which has been designated as professional in the NS-SEC is professional regardless of employment status. Thus, for example, a supervisor who is also a scientist is classified as a professional (in L3) and not as a supervisor in L6. Continuity issues. Category L3 is sub-divided for reasons of continuity with the former social classifications. L3.1 and L3.3 comprise those professional positions that have traditionally 28

37 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 5 been treated as such by SEG and SC. However, the NS-SEC recognises that other positions now share the employment relations of this group computing professionals and management accountants, for example. We have distinguished these new professionals from the traditional professionals by placing them in L3.2 or L3.4. The tables below show that category L3.1 is continuous with Social Class I ( professional occupations ) and SEG 4 ( professional employees ) and this is also true for 98 per cent of L3.3. Those in L3.2 and L3.4 were all in Social Class II ( managerial and technical occupations ). Social Class I II Total L L L L In terms of SEG, all of L3.1 were in SEG 4 and all of L3.2 were in SEG 5.1 ( ancillary workers and artists ). L3.3 was mainly in SEG 3 ( professional self-employed ) and L3.4 mainly in SEG 4. SEG Total L L L L3.4 * L4 Lower professional and higher technical occupations L4.1 Traditional lower professional employees that is, previously defined as technical occupations and ancillary workers by social class and SEG L4.2 New lower professional employees that is, not previously defined as technical occupations and ancillary workers by social class and SEG L4.3 Traditional self-employed lower professionals that is, previously defined as technical occupations and ancillary workers by social class and SEG L4.4 New self-employed lower professionals that is, not previously defined as technical occupations and ancillary workers by social class and SEG Positions, whether occupied by employers, the self-employed, managers or employees, and covering lower professional and higher technical occupations. Employees in these groups have an attenuated form of the service relationship. Conceptual and operational issues. Goldthorpe has suggested that the basic forms of employment regulation (the service relationship and the labour contract) may be actualised in differing degrees. Thus in his schema there is a distinction made between Service Class I (higher professionals, administrators and managers) and Service Class II (lower professionals, administrators and managers; higher-grade technicians; and supervisors of non-manual employees). The same holds for the NS-SEC. Employees in category L4 share fewer of the conditions associated with the service relationship when compared with L2 and L3. This is demonstrated both by their lower scores on LFS employment relations indicators and by multivariate analyses of the LFS data (see Chapter 6 and also Rose and Pevalin 2003a: Part II). The rules for allocating lower professional OUG/employment status combinations to the new schema are complicated. Small employers in lower professional occupations are in L4 rather than L8 (which is reserved for non-professional small employers and self-employed). However, lower professional employers in large organisations are in L1. This ensures that all large employers are allocated to Class 1 in analytic versions of the NS-SEC. Continuity issues. In similar fashion to L3, L4 is sub-divided for reasons of continuity with the former social classifications. L4.1 and L4.3 comprise those lower professional positions (whether employers, self-employed or employees) which have traditionally been treated respectively as technical occupations or ancillary workers by SC and SEG. The NS-SEC recognises that there are other positions that now share the employment conditions of this group. We have distinguished these new lower professionals by placing them in L4.2 or L4.4. Nearly all positions in L4.1 and 4.3 were also in Social Class II and SEG 5.1. The majority of those in L4.2 and L4.4 come from Social Class IIIN, skilled non-manual and in the case of L4.2 from SEG 6, junior non-manual. SEG 6 was a very heterogeneous category and so is predictably distributed across several categories of the NS-SEC. Those in L4.3 were mainly in SEG 5.1 and 89 per cent of L4.4 were in SEG 12 ( own-account workers ). Social Class I II IIIN Total L L L L

38 Chapter 5 The National Statistics Socio-economic Classification: Origins, Development and Use SEG Total L * * L L L * L5 Lower managerial occupations Positions in which there is an attenuated service relationship, and where those employed in these positions generally plan and supervise operations on behalf of the employer under the direction of senior managers. Conceptual and operational issues. As with lower professionals in relation to higher professionals, lower managers have an attenuated form of the service relationship when compared with senior managers. For example, they have fewer or less advantageous perks. As discussed under L2, the customary, if rather inadequate, organisation size rule, with a cut-off of 25 employees, is sometimes used as an indicator of the conceptual distinction between higher and lower level managerial positions, and thus offers some continuity with SEG. However, as we also saw, some SOC2000 OUGs are regarded as inherently or mainly middle and junior positions and thus are allocated to L5 regardless of organisation size. Continuity issues. The NS-SEC places all lower managers in L5 and they all derive from Social Class II. Social Class II Total L In terms of SEG, 60 per cent were in 2.2 ( managers in small establishments ) and 39 per cent were in 1.2 ( managers in large establishments ). The remainder in SEG 13 ( farmers ) is due to the agricultural sector distinction which SEG made, but which the NS-SEC has not retained for managers. SEG Total L * L6 Higher supervisory occupations Supervisory positions (other than managerial or lower professional) having an attenuated form of service relationship which cover intermediate occupations included in L7 and involve as their main task the formal and immediate supervision of others engaged in such occupations. Conceptual and operational issues. Employees in these positions have more of the range of service relationship conditions than those whom they supervise and are similar in employment relations terms to managers in L5. Typically, these higher supervisory positions are found in large bureaucratic organisations, however. Employees in these positions are supervising the work of others and thereby they exert a degree of authority over them. Continuity issues. All supervisors of the intermediate positions in L7 are in category L6, without any distinction between manual and non-manual work. All other supervisors are in L10. In 84 per cent of cases positions in L6 were in Social Class IIIN ( skilled non-manual ). Social Class II IIIN IIIM VI Total L * 100 In 84 per cent of cases higher supervisors were in SEG 5.2, foremen and supervisors, non-manual. Those from SEG 8, foremen and supervisors, manual, can be explained by reference to the occupations in SEG 9, skilled manual, which the NS-SEC has allocated to category L7.4 (see the next paragraph). SEG Total L * L7 Intermediate occupations Positions not involving general planning or supervisory powers, in certain clerical, administrative, services, technical and engineering occupations. Positions in this category are mixed in terms of employment regulation, that is, are intermediate with respect to the service relationship and the labour contract. L7.1 Intermediate clerical and administrative occupations L7.2 Intermediate service occupations L7.3 Intermediate technical and auxiliary occupations L7.4 Intermediate engineering occupations Conceptual and operational issues. These are intermediate positions in employment relations terms, that is, they have a mix of service relationship and labour contract features. L7 is divided for reasons of continuity. The similarity of the four sub-groups of occupations that make up this category was confirmed by LFS employment relations data analyses, as discussed in Chapter 6. It is precisely the fact that it is problematic to judge empirically the extent to which a service relationship can be said to prevail over a labour contract that distinguishes these positions operationally. 30

39 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 5 Continuity issues. Virtually all cases in L7.1 were in Social Class IIIN ( skilled non-manual ) and SEG 6, junior non-manual. The majority of cases in L7.2 were also to be found in Social Class IIIN (81 per cent) and SEG 6 (also 81 per cent). Similarly, L7.3 derives mainly from Social Class II, SEG 5.1. Cases in L7.4 are all found in Social Class IIIM ( skilled manual ), SEG 9 ( skilled manual workers ). This reinforces the point that the NS-SEC makes no distinction between manual and non-manual work. As has been discussed above, SEG 6 was a heterogeneous group that has been allocated across several categories of the NS-SEC according to the employment relations and conditions of the occupations within it. It may seem curious to see some occupations from SEG 9 allocated to L7 rather than L11.1. However, this particular group of occupations (for example, computer and telecommunications (non-professional) engineers) is clearly shown by LFS data to have better employment conditions compared with those in L11.1. Social Class II IIIN IIIM IV VI Total L L * L L SEG Total L L * L L onto them. Small employers remain essentially in direct control of their enterprises. As we have seen, operationalizing the distinction between large and small employers consists of applying a size rule cut-off of 25 employees, but in fact it is likely to be the case that the majority of small employers have only others or two, and at most 10 employees. For this reason, most are in many ways similar to self-employed or ownaccount workers (in L9). Continuity issues. Since there are sufficient cases for the NS- SEC to recognise them, L8 has been sub-divided into nonagricultural and agricultural employers to aid with continuity with SEG. SC did not, of course, separately recognise small employers. However, in the majority of cases they were allocated to Social Class II. Social Class II IIIN IIIM IV V Total L * 100 L Small employers in L8.1 were overwhelmingly in SEG 2.1, employers in small establishments, but small employers in agriculture (L8.2) were mainly in SEG 13, farmers employers and managers, and even SEG 15, agricultural workers, with only a few in SEG 2.1. SEG Total L L L8 Employers in small organisations L8.1 Employers in small organisations (fewer than 25 employees) in industry, commerce, services, etc L8.2 Employers in small organisations (fewer than 25 employees) in agriculture Employer positions (other than in higher and lower professional occupations) in which the incumbents employ others (and thus assume some degree of control over them) and carry out all or most of the entrepreneurial and managerial functions of the enterprise but employ fewer than 25 employees. Conceptual and operational issues. An employment relations approach distinguishes crucially between employers, the selfemployed (own-account workers) and employees; and, further, between employers in large and small organisations (see the discussion of L1 in paragraph 5.5). Employers in small organisations, although they do employ others, do not usually devolve most of their management or entrepreneurial functions 5.13 L9 Own-account workers L9.1 Own-account workers (non-professional) L9.2 Own-account workers in agriculture Self-employed positions in which the incumbents are engaged in agriculture or in any non-professional trade, personal service, semi-routine, routine or other occupation but have no employees other than family workers. Conceptual and operational issues. Own-account or selfemployed workers occupy one of the four basic class positions identified in our conceptual model. Own account workers neither sell their labour nor buy the labour of others. Continuity issues. As with L8, L9 is sub-divided to recognise the agricultural sector and thus to assist with continuity. Since SC did not recognise self-employment as a class dimension, cases in L9.1 are found in all SC categories except for Social Class I. For SEG, 90 per cent of those in L9.1 are drawn from 31

40 Chapter 5 The National Statistics Socio-economic Classification: Origins, Development and Use SEG 12, own-account workers ; and L9.2 is drawn mainly from the agricultural SEGs, 14 and 15. Social Class II IIIN IIIM IV V Total L L SEG Total L L L10 Lower supervisory occupations Supervisory positions having a modified form of labour contract, which cover occupations included in categories L11 L13 and involve as their main task formal and immediate supervision of others engaged in such occupations and thus the use of minor delegated authority. Conceptual and operational issues. In similar fashion to his treatment of the service relationship, Goldthorpe notes that the labour contract form of regulation is actualised to differing degrees. Thus positions in L10 have different employment relations and conditions from those in L12 and L13, but similar conditions to those in L11. Operationally these positions are distinguished most easily by job title ( foreman or supervisor ) in an OUG which, when combined with employee status, is allocated to L11, L12 or L13. Continuity issues. Supervisors of all those in L11, L12 and L13 are in L10. In most cases, supervisors in this group were located in Social Class IIIM (81 per cent). Those cases that were in Social Class IIIN cover non-manual occupations in NS-SEC L12. For SEG, 64 per cent of cases in L10 were in SEG 8 ( foremen and supervisors manual ). Those cases in L10 which were in SEG 7, personal service workers and SEG 5.2 ( non-manual supervisors ) are the result of the treatment the NS-SEC has given to certain non-manual occupations in these SEGs (see the discussion under L12, 5.16). Social Class II IIIN IIIM IV Total L * 100 SEG Total L10 * L11 Lower technical occupations L11.1 Lower technical craft occupations L11.2 Lower technical process operative occupations Positions in which employees are engaged in lower technical and related occupations and thereby have a modified form of the labour contract. Conceptual and operational issues. This category is distinguished by a modified form of labour contract that is very similar to that of supervisors. Employees in this category are more likely than those in L12 and L13 to be included in a craftspecific labour market and thus have some service elements in their employment relationship. Hence these positions are more likely than those in L12 and L13 to give their occupants opportunities for promotion, payment of a salary as opposed to a weekly or hourly wage, and greater autonomy, etc. Operationally job title does not help with the allocation of OUG/employment status combinations to this group since not all skilled OUGs as defined by SOC2000 are included here; some, as we have seen, are allocated to L7.4 and others to L12 and L13. It is the extent to which the labour contract is modified, as demonstrated by employment relations measures, which distinguishes this group. Continuity issues. Eighty-eight per cent of cases in L11.1 were found in social class IIIM and SEG 9. Those in L11.2 derive mainly (87 per cent) from social class IV ( partly skilled ) and SEG 10 ( semi-skilled manual ). Social Class II IIIN IIIM IV V Total L L SEG Total L * 100 L L12 Semi-routine occupations L12.1 Semi-routine sales occupations L12.2 Semi-routine service occupations L12.3 Semi-routine technical occupations L12.4 Semi-routine operative occupations L12.5 Semi-routine agricultural occupations L12.6 Semi-routine clerical occupations L12.7 Semi-routine childcare occupations 32

41 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 5 Positions in which employees are engaged in semi-routine occupations that have only a slightly modified labour contract. Social Class II IIIN IIIM IV V Total Conceptual and operational issues. Employees in these positions are regulated by an only slightly modified labour contract typified in a short term and direct exchange of money for effort. Goldthorpe makes no distinction at all between positions we have allocated to L12 and L13, all forming one class of semi- and unskilled workers. However, LFS data indicate that there are perhaps sufficient employment relations differences between L12 and L13 as to make them distinctive class positions even when the NS-SEC is collapsed into an analytic variable. Again operationalisation cannot rely at all on job title, but depends upon the measurement of employment relations. The category name of semi-routine employees is designed to indicate the fact that employers must perforce slightly improve on the basic labour contract for this group, that is, that the work involved requires at least some element of employee discretion. Continuity issues. L12 has been sub-divided to obtain maximum backwards continuity with SC and SEG, but in implementing this strategy it was important to us that the sub-groups had face validity (that is, that they made intuitive sense as subgroups). Continuity has therefore occasionally been sacrificed for the sake of face validity. Most cases in L12.1 were found in Social Class IIIN skilled nonmanual (87 per cent). The treatment of these non-manual occupations by the NS-SEC is the direct result of not making class distinctions between manual and non-manual work. Because of its conceptual base, the NS-SEC is able to recognise that some non-manual work is less secure, less autonomous, and has fewer prospects than some manual work. Sales and retail assistants is the most prominent example of a nonmanual OUG allocated to L12.1. In terms of SEG, nearly all cases in L12.1 were found in SEG 6, junior non-manual workers. Cases in L12.2 were mainly located in Social Class IV ( partly skilled occupations ); and 64 per cent were in SEG 10 ( semi-skilled manual workers ). However, 36 per cent were from (the non-manual) SEGs 5.1 ( ancillary workers ) and 7 ( personal service workers ) heterogeneous SEGs, which have perforce been allocated across several NS-SEC categories. Occupations in L12.3 were all in Social Class IIIM, SEG 9 (skilled occupations). L12.4 occupations were virtually all in Social Class IV and SEG 10. L12.5 cases were located only in Social Class IV and SEG 15 ( agricultural workers ). L12.6 derives mainly from Social Class IIIN and wholly from SEG 6 ( junior non-manual workers ). Finally, L12.7 cases were primarily in Social Class IV, SEG 7, but substantial minorities were in Social Class II and IIIN and SEG 6. L L * L L * 100 L L L SEG Total L * L * L L * L L L L13 Routine occupations L13.1 Routine sales and service occupations L13.2 Routine production occupations L13.3 Routine technical occupations L13.4 Routine operative occupations L13.5 Routine agricultural occupations Positions where employees are engaged in routine occupations which have a basic labour contract. Conceptual and operational issues. Employees in these positions are clearly regulated by a basic labour contract and are thus even less likely than those in L12 to have opportunities for promotion, autonomy over work, and so on. Here there is least need for employees to be allowed autonomy and discretion and (thus) external controls can be most fully relied on (Erikson and Goldthorpe 1992:43). The category name of routine employees is designed to indicate this fact. Once again, conceptually, operationalisation cannot rely on job title, but depends upon the measurement of employment relations. Continuity issues. L13 has been sub-divided to obtain maximum backward continuity with SC and SEG while retaining face validity. L13.1 occupations were mainly in Social Class IV and SEG 7. L13.2 cases were solely in Social Class IV and SEG 10. L13.3 comprises occupations in Social Class IIIM, and SEG 9. L13.4 is mainly drawn mainly from Social Class V ( unskilled occupations ), SEG 11 ( unskilled manual ); and L13.5 from Social Class IV, SEG 15 ( agricultural workers ). 33

42 Chapter 5 The National Statistics Socio-economic Classification: Origins, Development and Use Social Class IIIN IIIM IV V Total L L * 100 L * L L SEG Total L L * L * L L L14 Never worked and long-term unemployed L14.1 Never worked L14.2 Long-term unemployed Positions which entail exclusion from the labour market involving (a) those who have never been in paid employment but would wish to be; and (b) those who have been unemployed for an extended period while still seeking or wanting work. Conceptual and operational issues. Goldthorpe (1997:48) has suggested that both the long-term unemployed and those who have never been in paid employment (although available for work) could be treated in employment relations terms as a separate class the category of those who are excluded from employment relations of any kind, our fourth basic class position (see 4.12). Operationally, however, both the long-term unemployed and the never worked but available for work are difficult to define. And the problems here cannot be separated from the more general ones concerning the non-employed population. Dealing with the non-employed. In order to improve population coverage, we recommend that those who are not currently in paid employment be allocated to the class of their last main job. Thus, for most non-employed persons (the unemployed, the retired, those looking after a home, those on government employment or training schemes, the sick and disabled, etc), the normal procedure is to classify them according to their last main job. The main exception to this rule is for full-time students (see 5.19). Those who have never worked but are seeking, or would like paid work, should be allocated to L14.1. In the case of the long-term unemployed, there is an argument that they should not be classified according to their last job, but should be assigned to category 14.2 of the classification (on the grounds that they are excluded from employment relations) and included with the never worked when the NS-SEC is collapsed to an analytic variable. However, it is not possible to define the long-term unemployed in any hard and fast way. Essentially, analysts must make their own decisions here, according to their research purposes. Some might not want to implement L14 at all and thus will exclude the never worked from the classification and classify all unemployed persons in respect of their last main job. Others might want to implement the class and use a six-month unemployment rule related to the maximum length of time for which Jobseekers Allowance is paid, but others might prefer a one- or even two-year unemployment rule. The Review Committee s recommendation, in the absence of any strong analytic or theoretical preference, would be to employ a one-year rule. Of course, since we cannot prescribe on this matter, information on last main job should be collected for all unemployed persons. We are aware that it may not be possible to implement these rules for the allocation of the nonemployed on all datasets. However, we recommend that, other things being equal, all surveys conducted by the Office for National Statistics (ONS) and the Census collect data in a manner that would allow these rules to be implemented. We return to the issue of the non-employed in L15 Full-time students Persons over 16 years of age who are pursuing full-time courses of study in secondary, tertiary or higher education institutions. Conceptual and operational issues. Full-time students would not normally be allocated a class position, although they are recognised as a category in the full classification for reasons of completeness. However, since many students will have, or will have had, occupations, they could be classified by current or last main job if the analyst wished to do so. Normally, however, we would not expect students to be classified in this way. Conventionally, where full-time students are included in class analyses (for example, in research on education), they are given their class of origin. Nevertheless, data should be collected on the current or last main jobs of full-time students L16 Occupations not stated or inadequately described There are always some cases where the occupational data requested in response to surveys and censuses are not given or 34

43 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 5 are inadequate for classificatory purposes. This category exists for such situations L17 Not classifiable for other reasons Whatever rules we devise, some adults cannot be allocated to a class position within our schema. For example, if the design of a particular survey excluded (say) the elderly from being asked employment questions, then for the sake of completeness, such cases should be allocated to this category. The NS-SEC analytic classes 5.22 The operational classification discussed in the preceding paragraphs may be collapsed into a number of different analytic variables. We have termed these analytic versions. The principal one of these variables (the official NS-SEC) is depicted in Figure 3. It contains eight basic categories, one of which may be sub-divided, if analysts so choose, to produce a nine-class version. Figure 3 The NS-SEC analytic classes: nine- or eight-class versions 1 Higher managerial and professional occupations 1.1 Large employers and higher managerial occupations 1.2 Higher professional occupations 2 Lower managerial and professional occupations 3 Intermediate occupations 4 Small employers and own-account workers 5 Lower supervisory and technical occupations 6 Semi-routine occupations 7 Routine occupations 8 Never worked and long-term unemployed 5.23 NS-SEC data. Table 5 shows the seven-class NS-SEC by gender using our 1996/97 LFS data. However, a rather better picture is given by Table 6, which is calculated from 2001 Census data and includes Class 8, too. This table offers researchers the opportunity to compare their own NS-SEC data with national data for the UK and each of its constituent countries Issues in collapsing to analytic classes: (1) Employers. Employers in large organisations (L1) are combined with higher managerial occupations (L2) in Class 1.1. However, as Goldthorpe (1997:41) has noted, if it were possible to overcome the difficulties of operationalising the distinction between legal forms of incorporation, partnership, etc. in a sociologically meaningful way, there would be no obstacle in principle to elaborating the classification so as to remove the Table 5 NS-SEC seven-class by sex Sex NS-SEC Male Female Total 1 Higher managerial and 5,373 1,636 7,009 professional occupations Lower managerial and 7,371 7,529 14,900 professional occupations Intermediate occupations 2,452 6,473 8, Small employers and 4,619 1,703 6,322 own-account workers Lower supervisory and 4,685 1,572 6,257 technical occupations Semi-routine occupations 4,699 7,073 11, Routine occupations 4,452 3,596 8, Total 33,651 29,582 63, anomalies caused by including employers in a class which is largely composed of employees. Nevertheless, the small numbers in L1 make it unlikely that it could ever be separately analysed as a class in survey research. However we could have divided Class 1 into three components by giving large employers a sub-class of their own. Indeed we might have regarded large employers as being the whole of an elite Class 1, with higher managers and professionals in Class 2. This might have satisfied purists (see for example Scott 1996:212 and passim) but it would yield little in the way of analytic benefit and might even be misleading. Most of those in L1 could not be described as heroic capitalists, as we saw previously Issues in collapsing to analytic classes: (2) Small employers. Other than in the case of professionals and associate professionals, employers in small organisations, who generally have only one or two employees, are combined with ownaccount workers into a single self-employed class (Class 4) Issues in collapsing to analytic classes: (3) Higher managers and higher professionals. While it would be normal within an employment relations perspective to regard Class 1 as a single class for analytic purposes, we have preserved a distinction made by SC and SEG between senior managerial positions (1.1) and higher professional positions (1.2) so that those who wish to analyse these two elements of Class 1 separately may do so (see Mills and Evans 2003). Those who wish to create a separate managerial and technical class 35

44 36 Table 6 NS-SEC eight-class by sex and nation, aged (Census 2001) England Scotland Northern Ireland Wales UK Males Females All Males Females All Males Females All Males Females All Males Females All 1 Higher managerial and professional Lower managerial and professional Intermediate Small employers and own account Lower supervisory and technical Semi-routine occupations Routine occupations Never worked and long-term unemployed (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) Students are excluded from this table Figures calculated from Census Key Statistics Tables 14a 14c Chapter 5 The National Statistics Socio-economic Classification: Origins, Development and Use

45 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 5 similar to Social Class II would need to combine Class 1.1 with Class 2 in order to achieve this Issues in collapsing to analytic classes: (4) Lower supervisors and craft and related employees. In the Goldthorpe class schema supervisors are in a different class from craft and related workers. However, the LFS data discussed in Chapter 6 indicated that these two groups form one basic elite working class and so they are collapsed together. Erikson and Goldthorpe (1992:43) have accepted that this is a reasonable procedure Issues in collapsing to analytic classes: (5) Semi-routine and routine employees. To date, employment relations theory has made no distinction between what we have called semi-routine and routine occupational positions (or what have been conventionally known as semi- or partly-skilled and unskilled occupations) because a basic labour contract is assumed to exist for both positions. Hence, it would be normal to regard these positions as forming a unified class. However, SC and SEG did distinguish partly-skilled occupations (Social Class IV, SEG 10) from unskilled occupations (Social Class V, SEG 11), and LFS data lend some empirical support to a similar employment relations distinction. Hence we regard L12 and L13 as being separate classes which collapse into Classes 6 and 7 respectively (although those who wish to ignore this distinction will no doubt treat Classes 6 and 7 together for analytic purposes) The NS-SEC and the analytic class models. Figure 4 demonstrates the nested structure of the NS-SEC, the operational level collapsing into various analytic variables. We would expect that most former users of SC would wish to use the eight-class version of socio-economic classes. They may want to treat 1.1 and 1.2 as separate classes, especially when comparing current research using NS-SEC with past research using SC Five-class model. Employment relations theory does not assume that there are x and only x number of classes. Rather it argues that the number of classes to be recognised empirically depends upon the analytic purposes at hand. The class schema we propose is thus to be regarded as an instrument du travail (Erikson and Goldthorpe 1992:46). Hence, as Figure 4 shows, within the employment relations model it is also possible to have a five-category version of socio-economic classes; and if analysts wished to keep professionals and managers separate, a six-category model could be implemented The three-class model. In the past, analysts have divided SC into non-manual and manual groups. We have already seen that the manual/non-manual distinction no longer holds in any meaningful way. However, the new classification does allow for a three-category version of analytic classes as in Figure A caveat. However, we should also enter a cautionary note here concerning the three- and five-class models. As Figure 4 shows, each of these allocates the never worked and long-term unemployed to the working class. Thus, if performing health analyses, users would need to be very careful about how the long-term unemployed and the never worked were defined. Including the permanently sick would clearly not be sensible. They should be classified to last main job and the long-term unemployed should include only those who are seeking or available for work. Of course, this may still leave some people who are permanently sick or disabled in the never worked category, hence this warning. We make further comments on the treatment of the non-employed in analyses later (see 5.38), but again we would stress the point made in 5.18 concerning the need to collect data on last main job for all the non-employed, thus giving analysts maximum flexibility. Measurement issues 5.33 (1) Distributive scales or relational schemata? In measurement terms, all versions of the NS-SEC are strictly speaking nominal or categorial. Some might see this as a disadvantage, preferring continuous or ordered scales. SC was, of course, ordinal and many researchers found this property useful. However, employment relations theory necessarily involves nominal measurement and thus advocates the use of the appropriate (and powerful) associated analytic techniques (for example, logistic regression). Why is this? 5.34 Scales and classes. The Phase 1 report (Rose 1995:8) argued that occupation (usually combined with employment status) is a reasonable indicator of overall social position. This is because the life chances of individuals and families depend mainly on their position in the social division of labour, and thus on the material and symbolic advantages which derive from position in the labour market. The Phase 1 report also noted that there are broadly two different ways of creating occupationally-based SECs occupational scales and class schemata (Rose and 38 39; and Rose 1994). Occupational scales are hierarchically ordered strata, each of which comprises sets of occupations which are regarded as equivalent in terms of whatever the scale is measuring. Thus SC was an ordered scale in respect of (supposedly) skill or social standing. On the other hand, the Cambridge Scale is a continuous one, designed to measure generalised social advantage (see Stewart et al 1980). Class schemata, however, are designed to measure the relational, rather than the distributive aspects of social inequality. Hence our reliance on employment relations theory as the basis for the NS-SEC. Using this approach we have 37

46 38 Figure 4 NS-SEC operational categories and their relation to the main analytic class variables Operational categories Analytic variables Eight (Nine) classes Five classes Three classes L1 Employers in large Large employers and organisations 1.1 higher managerial L2 Higher managerial occupations occupations L3 Higher professional Higher professional 1.2 occupations occupations Managerial and Managerial and Lower professional and 1 professional 1 professional L4 higher technical occupations occupations occupations Lower managerial and L5 Lower managerial 2 professional occupations occupations L6 Higher supervisory occupations L7 Intermediate Intermediate Intermediate 3 2 occupations occupations occupations L8 Employers in small Intermediate 2 occupations organisations 4 Small employers and 3 Small employers and L9 Own-account own-account workers own - account workers workers Lower supervisory L10 occupations Lower supervisory and 5 4 Lower supervisory and L11 Lower technical technical occupations technical occupations occupations Routine and Semi-routine Semi-routine 3 manual L12 6 occupations occupations Semi-routine and occupations 5 L13 Routine routine occupations occupations 7 Routine occupations L14 Never worked and Never worked and Never worked and Never worked and 8 long-term unemployed long-term unemployed long-term unemployed long-term unemployed Chapter 5 The National Statistics Socio-economic Classification: Origins, Development and Use

47 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 5 constructed a class schema that (so far as is possible within the limitations of our LFS data discussed in the next chapter) minimises within-class and maximises between-class variation in terms of employment relations. That is, we have determined the work and market relations typical for each class. However, because they are based on social relations, class schemata are not hierarchically or linearly ordered. This is why we must collapse the NS-SEC in the manner indicated in Figure 4. For example, higher professionals and managers in large organisations are in broadly equal positions to one another, as are intermediate employees and the selfemployed (whether small employers or own-account workers). Of course, some classes are advantaged with respect to others; for example managers in large organisations vis-à-vis intermediate employees and all of the working class. This follows directly from the different modes of employment regulation discussed in Chapter 4. However, we cannot wholly order a class schema such as the NS-SEC. Because the NS-SEC aims to capture qualitative differences in employment relations, the classes are not consistently ordered according to any inherent hierarchical principle. The members of different classes may be relatively advantaged or disadvantaged in different ways. Nevertheless, class schemata do not attempt to describe societies on a layer-cake model but via more subtle, relational concepts. Finally, one of the great advantages of class schemata is that they permit us to study both the relational and the distributive aspects of social inequality, as demonstrated by the validation studies discussed in Chapter 6 (and see on all these issues Egidi and Schizzerotto 1996) A health warning on measurement issues. Returning now to the basic measurement issues relating to the NS-SEC, the three-class model may be assumed to involve some kind of hierarchy. However, neither the five-, six-, eight- nor nine-class versions can be regarded as ordinal scales, not least (but, as we have seen, not only) because of the recognition of selfemployment as a separate class category. However, we recognise that some researchers might wish to have an ordinal scale similar to SC. This could ostensibly be achieved, for example, by combining the self-employed in NS-SEC Class 4 with the intermediate Class 3. We do not advocate this, however, not least because the self-employed are distinctive in their life chances and behaviour. On the contrary, we recommend strongly that analysts accept the theoretical, and thus the measurement principles of the new class schema, take advantage of the conceptual base of the model for developing hypotheses linking class to outcomes of interest (see ) and use analytic techniques as appropriate (2) Population coverage. While experts were concerned with the conceptual poverty of the former classifications, users were often more worried about the practical problems they faced when they employed SC and SEG. Of most concern was the issue of population coverage. In many circumstances, occupational classifications only cover half the population. There are, of course, methods for avoiding this in data collection (for example, by using an earlier occupation or that of someone else in the household). However, this is not always possible when using administrative data sources or where classification is not seen as an objective in data collected for other purposes. On the basis of own occupation, classifications most frequently exclude children, housewives, the retired, the unemployed, and the never employed, and often understate the social position of those in temporary, post-retirement or part-time work. Many of these groups are vital to policy and research interests and it is a matter of concern that they so often slip through the classificatory net. Virtually every government department made this criticism of SC and SEG, often with the comment that the new, flexible labour market was exacerbating these problems (see 6.1). Of course, ONS provided recommendations in Standard Occupational Classification: Vol. 3 (OPCS 1991) designed to alleviate the difficulty, and, where it was practical to follow these, then only children and adults who have never worked were excluded (3) The disadvantaged. Academic off-the-peg users of SECs are similarly concerned about coverage, some noting that SC and SEG did not cover the most disadvantaged and precariously placed individuals. For example, child mortality is greatest among groups such as unemployed, lone parents. Similarly the mortality rates for the unemployed and disabled were higher than those for Social Class V; including these groups would significantly affect the overall results (4) Classifying the non-employed. In response to such criticism, and as we argued in 5.18, it is important to include within the NS-SEC as many as possible of those adults not in paid employment. To achieve this we saw that it is first necessary to create a special NS-SEC category for the never worked. For others who are non-employed, research by Marshall et al (1996) demonstrates that classifying individuals not currently in paid employment by their last main job is a satisfactory procedure, even for those who have been out of the workforce for many years. Moreover, research reported by Arber using General Household Survey data demonstrates strong class gradients (or, more precisely, monotonic changes) in ill-health for unemployed men and the retired (see Arber 1997b; Arber and Cooper 1998; 39

48 Chapter 5 The National Statistics Socio-economic Classification: Origins, Development and Use Cooper and Arber 2003; and c.f. Arber 1996a). For the retired, class (in terms of last main occupation) continues to be associated with health throughout retirement. It is for this reason that we recommend that both the Census and government surveys collect information on last main job for all those not in paid employment. Of course, this may seem to contradict our proposal for a class partly composed of the long-term unemployed. However, the creation of category L14 is for analysts to decide. This is why information on last main job is always required for those not in paid employment. To repeat, this strategy is one designed to create flexibility for analysts. Using these rules, only children are excluded from the NS-SEC. However, as with students, the normal practice is to classify children by reference to a parent. This raises the issue of which parent to choose and thus of how to classify households and/or families (5) Family/household measures of class. Many analysts only perceive SECs as individual measures of labour market position. Consequently they only use them as such. In fact, however, many analyses would be improved if, when appropriate, researchers employed the household rather than the individual as the unit of class composition. We have explored some of the reasons for this elsewhere (see Rose and Pevalin 2003d). It may be asked, however, how a measure such as the NS-SEC, based as it is on employment contracts, can be anything other than an individual measure. We shall try and explain (6) The family/household as the unit of class composition. Traditionally in sociology the unit of class composition (or unit of analysis) has not been the individual but the conjugal family/ household. That is, the (nuclear) family is given priority over the individual as the unit of class composition so that those living together in a family household are regarded as having the same class position. In other words, the family is the basic class structure element because of the inter-dependence and shared conditions of family members (see, for example, Goldthorpe 1983). After all, a family member s own class position may have less relevance to his/her life chances than the position of another family member (see, for example, Vagero 2000). It is the family that is the unit of class fate and the basic decisionmaking unit in terms of both consumption and labour market participation (see, for example, Erikson and Goldthorpe 1992: ). Hence, lines of division run between, but not through families. This does not assume or imply that the family is egalitarian, but only that family members living in the same household share the same class fate. Therefore, we need to be able to assign a household NS-SEC value to all household members. The simple practical solution to this problem has been to select one family or household member (usually the male breadwinner ) and take that person s class to stand for the whole household. Recently, however, especially because of the increased participation of married women in the labour market, there has been much discussion about whether this continues to be an appropriate strategy. Some have advocated that the individual should now be the unit of class composition. Without entering the details of this controversy (see Sobel et al 2004, Rose and Pevalin 2003d, Sørensen 1994 and Erikson and Goldthorpe 1992 ibid), here we discuss different ways in which the NS-SEC can be applied to households and families (7) Assigning household class: (1) highest income householder. Because of the overt sexism involved in the male breadwinner approach to the definition of the household reference person (HRP), a new method has been developed by official statisticians (see Martin 1995 and 1998, Martin and Barton 1996). ONS has decided that, in the final instance, the HRP should be the Highest Income Householder (HIH), thus removing sex as a criterion for determining head of household. Here the householder is regarded as the person responsible for owning or renting or who is otherwise responsible for the accommodation. Where this definition yields joint householders, the person with the highest income takes precedence and becomes the HRP. Where incomes are equal, the older is taken as the HRP. This procedure increases the likelihood both that a female will be the HRP and that the HRP better characterises the household s social position. Analysts will generally use this procedure for determining household class. When using most government datasets they will have no choice but to do this. However, it should be noted that any definition based on income is likely to reduce the number of HRPs classified as selfemployed, since they tend to have (or to declare) low incomes (8) Assigning household class: (2) the dominance approach. There is an alternative approach that regards the household reference person as the one who is dominant in the labour market, the so-called dominance approach (see Erikson 1984). From a social scientific perspective, this procedure is preferable to one that relies on income in the determination of household class, but it does require that NS- SEC values must first be established for all household members. The dominance approach advocates two class concepts. In the first, work-related concept, individuals are the unit of classification because work is uniquely related to individuals. Hence it does not matter whether the individuals are male or female; each can be assigned a work position. In the second, market-related concept, families are seen as the classification unit. This is called the class position. Everyone has a class position, whether or not they are in the labour market. 40

49 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 5 The problem is thus how to determine a class position for the family and then assign it to men and women alike. Erikson argues that class position may be derived as a function of individual family members work positions based on an order of dominance. At first sight, this may appear to contradict our earlier statement that the NS-SEC classes cannot be ordered. However, it should be recalled that the employment relation or contract only applies to individuals, that is, to the work position. Employment relations do not exist within families and so do not play a part in determining which family member s work position best represents the family s class position (9) Determining family class position. If only one household member is in paid employment, that person s work position becomes the family s (household s) class position. Similarly, if two generations are present in the household and each has a representative in employment, the person of the senior or primary generation takes precedence. However, where each of two or more members of this primary generation has work positions and these positions are different (i.e. place them in different individual-level class categories), we need another dominance rule to determine (household or family) class position. As with any other method for determining the HRP, ultimately we need an ordinal variable to make the final selection. If the work positions are the same (as they often will be) then this becomes the family class position. Otherwise, we need to decide for each possible pairing of different work positions, which is likely to have the the greatest impact upon ideology, attitudes, behaviour and consumption patterns of the family members (Erikson 1984:504). Note this ordering is not based on work position as determined by employment relations but on the basis of the life chances known to be associated with work positions. It is in this sense that Erikson assumes there are dominance relations on various dimensions in which work positions may differ. Thus, higher qualifications dominate lower ones; non-manual work dominates over manual work; selfemployment dominates over being employed; employers dominate over own-account workers; and managerial work dominates all other forms of work. Finally, the active are dominant over the inactive. All these assumptions flow from long-established results of research on the relationships between class position and life chances. Erikson then tested these assumptions using data from the Swedish Level of Living Survey (ibid: ) (10) Dominance method for the NS-SEC. On the basis of Erikson s research, where the NS-SEC work positions (that is, the individual class assignments) differ, the rules of precedence we suggest are as follows. First, individual work positions derived from full-time work are dominant over those from part-time work. Second, if each is in full-time work, or each is in part-time work something like the order of precedence in Figure 5 should prevail from highest to lowest. Note, however, that this order has not yet been validated, but could be by following similar procedures to Erikson s. Figure 5 Projected dominance rules for assigning household NS-SEC L2 L3 L1 L8 L4 L5 L9 L6 L7 L10 L11 L12 L13 L14 L15 Higher managerial occupations Higher professional occupations Employers in large organisations Employers in small organisations Lower professional occupations Lower managerial occupations Own-account workers Higher supervisory occupations Intermediate occupations Lower supervisory occupations Lower technical occupations Semi-routine occupations Routine occupations Never worked and long term unemployed Students 5.45 (11) Rules for operationalising the NS-SEC where elements of the algorithm are missing: (1) Reduced NS-SEC. The NS-SEC is derived from information on occupation coded to the OUG level of SOC2000 and information about employment status and size of organisation in the form of an employment status variable. Full details of the procedures required and of the questions that must be asked to elicit the necessary information are provided in the National Statistics Socioeconomic Classification User Manual (ONS 2005). However, some datasets do not have all the operational elements required for the full implementation of the NS-SEC, for example death registration data. Formerly ONS used a version of SEG (SEGLOW) that could be implemented without information on establishment size. As a further demonstration of the NS-SEC s flexibility, we have produced an equivalent of SEGLOW, Reduced NS-SEC, based on the probabilities of managers or employers being large or small within each OUG. When operationalised it accurately allocates 98 per cent of LFS cases in the seven-class version for those currently in paid employment. The following are the rules for allocating managers and employers to Reduced NS-SEC: 41

50 Chapter 5 The National Statistics Socio-economic Classification: Origins, Development and Use (a) in the case of managers, those in L3 are, of course, treated as professionals. For the remainder OUGs , 1121, , , 1181, 1184, 1212 and 1231 are allocated to L2. OUGs 1114, 1122, , 1174, , , and are allocated to L5. (b) in the case of employers, the probability for every OUG is that they are small employers and should thus be assigned to L8.1 or L8.2 (but L3 or L4 if higher or lower professional occupations) (12) Rules for operationalising the NS-SEC where elements of the algorithm are missing: (2) Simplified NS-SEC. The equivalent to SEGLOW for SC was Simplified Social Class and again we can produce a counterpart. This is used when only information on OUG is available. In such cases, we have decided to classify OUGs to the class that is allocated for the employment status of employees, except where employees are in a minority within an OUG or an OUG has no employee status. In these cases we take the class of the most frequently occurring OUG/employment status combination. The resulting measure, Simplified NS-SEC (or SSEC) correctly allocates 84 per cent of LFS cases in the seven-class version for those currently in paid employment. Tables 7 and 8 provide further details of the comparisons between the full, reduced and simplified versions for the seven-class NS-SEC and the operational version respectively. Appendix 4 contains the derivation matrices for the reduced and simplified NS-SEC (13) Self-coded NS-SEC. ONS has separately developed and reported on a version of NS-SEC for use in self-completion surveys (see Birch and Beerten 2002, Martin and Deacon 2000 and ONS 2005). Self-coded NS-SEC has five classes: (1) Managerial and professional occupations; (2) Intermediate occupations; (3) Small employers and own-account workers; (4) Lower supervisory and technical occupations; and (5) Semiroutine and routine occupations. In comparisons of self-coding and interviewer coding of this five-class NS-SEC, there was agreement in classifying 75 per cent of cases. Moreover, validation studies demonstrated that the self-coded and interviewer-coded five-class NS-SECs displayed similar patterns and strengths in their relationships with other variables of interest. The National Statistics Socio-economic Classification User Manual provides details of when and how to use selfcoded NS-SEC as well as its derivation (ONS 2005). Table 7 Frequencies and percentages of NS-SEC seven-class by different methods (LFS 1996/97) Full Method Reduced Method Simplified Method NS-SEC Number Col % Number Col % Number Col % 1 7, , , , , , , , , , , , , , , , , , , , , Total 63, , , Maintaining the NS-SEC 5.48 Maintaining the NS-SEC In the past, the maintenance of government SECs involved rather ad hoc procedures. As we saw in Chapter 3, this was a direct consequence of the lack of explicit conceptual rationales for SC and SEG. If we do not know what a classification is supposed to measure, we cannot easily decide how to maintain it in the face of change. By offering an SEC with a clear conceptual base, we can also be more precise on how it should be maintained essentially via the same ex ante procedures by which it was created. Ideally, employment relations data should be collected inter-censally in order to re-validate the whole schema and therefore to decide on the allocation of both existing and new occupations to it. This should be done immediately following the inter-censal review of SOC. This forms the substance of recommendation 7 in Chapter 2. Table 8 Frequencies and percentages of the operational version of NS-SEC by different methods (LFS 1996/97) Full Method Reduced Method Simplified Method NS-SEC Number Col % Number Col % Number Col % L * 0 * L2 2, , , L3 4, , , L4 8, , , L5 4, , , L6 1, , * L7 8, , , L8 1, , , L9 4, , , L10 3, , L11 2, , , L12 11, , , L13 8, , , Total 63, , , * Less than 0.1% 42

51 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter Maintenance issues. Because of the more rapid labour market changes of recent years, it is possible to imagine future difficulties in attempting to follow the precise ex ante maintenance procedures that were used to create the schema. As we discuss in Chapter 6, there are potential circumstances in which previously reliable indicators of employment relations might no longer be as discriminating between NS-SEC categories as they once were. Moreover, a procedure that relies on collecting data from individuals on their employment relations is not entirely reliable and might be supplemented by collecting information on employment contracts directly from employers (see O Reilly and Rose 1998c). Additionally, even with as large a survey as the LFS, some OUG/employment status combinations appear in so few cases that it is not always possible to decide to which class they should most appropriately be allocated. Again information collected from employers for these rare OUG/employment status combinations could fill this gap. It is possible that the Workplace Employee Relations Survey (formerly the Workplace Industrial Relations Survey) will in future be of assistance, since the latest in this series contains information on employment relations from both employees and their employers. However, it is inevitable that ONS will need to consult relevant experts before embarking on any re-validation of the NS-SEC or on the re-allocation of occupations to it Conclusion. This completes our discussion of the NS-SEC. In the following chapter we discuss the evidence which led us to our principal recommendations, that is, how the NS-SEC was created and validated. 43

52 Chapter 5 The National Statistics Socio-economic Classification: Origins, Development and Use 44

53 Creating and validating the NS-SEC Chapter 6

54 Chapter 6 The National Statistics Socio-economic Classification: Origins, Development and Use Introduction 6.0 We saw earlier that in Phase 2 of the Review we decided to adopt but adapt the Goldthorpe schema as the basis for the NS-SEC. Initially, we undertook some empirical investigations of the feasibility of measuring employment relations. For this purpose we used the Omnibus Survey from the Office for National Statistics (ONS). This exercise is briefly examined in the first part of this chapter. In Phase 3 we used the Labour Force Survey (LFS) to measure employment relations as the basis for the allocation of Standard Occupational Classification SOC90 occupational unit group (OUG)/employment status combinations to the classes of the new socio-economic classification, or SEC. At the same time we developed the operational version of the NS-SEC as the means of relating it to Social Class based on Occupation (SC) and Socio-economic Groups (SEG). Having created an interim version of the NS-SEC and an associated derivation matrix, we then undertook a series of validation studies designed to establish both that the NS-SEC adequately measured employment relations and that it was an effective classification for research purposes. Again we summarise the Phase 3 work here. Details of all this work may be found elsewhere (see Rose and O Reilly 1997a and b and 1998). Finally, in Phase 4 we rebased the interim NS-SEC on SOC2000. Most of this chapter will be concerned with recounting this final phase of our work. Measuring employment relations 6.1 A potential problem for the employment relations approach: the flexible labour market. Having decided to adopt an employment relations approach as the conceptual basis for a new SEC, our first concern was to ensure that recent labour market changes had not somehow overtaken the model. In particular, some critics had argued that the so-called flexible labour market might have reduced differences between employees to the extent that previously reliable indicators of employment relations and conditions might no longer be so discriminating between SEC categories as they once were. In short, it was claimed that a shift to more flexible working patterns might have blurred the lines of division among employees which we described in Chapter 4 and Figure 1. This was a new version of the oft-repeated claim that we are all working class now because employers increasingly opt for similar measures of employment regulation for all employees. Of especial concern was that the privileged contractual terms associated with managerial and professional employment were being whittled away by employers. This problem called for close empirical examination before we could proceed to finalise our recommended SEC. 6.2 National Statistics Omnibus analyses. In order to test the propositions about the potentially disruptive effects of a flexible labour market for operationalising employment relations-based approaches to class, in Phase 2 we undertook some pre-test work using the National Statistics Omnibus surveys for April, May and July 1996 (for more details see O Reilly and Rose 1997b and 1998c). We used a variety of questions largely taken from the Social Class in Modern Britain and Employment in Britain datasets. As we discuss later, although we required LFS data on employment relations and conditions at OUG level before we could finally operationalise and validate the NS-SEC, we were able to produce an interim version for the analysis of our data and hence for our Phase 2 validation exercises. 6.3 Measuring employment relations. In selecting appropriate questions to use as indicators of employment relations and conditions, we were by no means working in the dark. Recent research suggested that there were three conceptually separable, although empirically correlated, respects in which employment relations might continue to be differentiated according to whether a service relationship or labour contract exists: forms of remuneration; promotion opportunities; and autonomy, especially as regards time (see Goldthorpe 1997). 6.4 Conclusions of Omnibus analyses. Our analyses of the Omnibus data demonstrated that, notwithstanding labour market changes, it was still possible to distinguish empirically between classes, as relatively homogeneous positions in the labour market, based on a conceptual distinction between a service relationship and a labour contract (O Reilly and Rose 1997a and 1998c). Furthermore, changes in employment, at least in terms of those indicators germane to the employment relations concept, had not served to undermine this distinction as much as might have been supposed. The arguments that long-termism and security were becoming increasingly threatened for work traditionally associated with a stable career, that intermediate work was becoming more like routine work in terms of payment and promotion opportunities, and that professional and managerial employees were losing much of their autonomy and were therefore, in some respects, closer to intermediate workers, were not confirmed, prima facie, by the Omnibus data. Employment within a service relationship continued to be characterised in terms of the payment of a salary and the promise of long-term prospects, such as incremental wage rises and promotion, within a recognised career structure, in return for commitment to the employing organisation. The Omnibus data also showed that this was in contrast to work regulated by a labour contract, in which it was much more likely that payments were based weekly or hourly, and which 46

55 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 6 entailed closer supervision and fewer prospects than work in the service class. Subsequent, more detailed analyses of both British Household Panel Survey and New Earnings Survey data have confirmed these sorts of finding (see Goldthorpe and McKnight 2003). 6.5 Other work in Phase 2. Apart from the work described above, a number of other projects were conducted in Phase 2. These projects are more fully described elsewhere (see Rose and O Reilly 1997a and b). They included a number of validation studies using the interim SEC (Arber 1997b; Dale 1997; Fitzpatrick et al 1997; and Elias and McKnight 1997) and detailed examinations of conceptual and operational issues (Goldthorpe 1997; Elias 1997a; and Martin 1997). In addition a database on SOC OUGs was produced (McKnight and Elias 1997). 6.6 Phase 3. Here we discuss our two principal aims in Phase 3: (1) the analysis of LFS data on employment relations and conditions and (2) validation studies using the new SEC. In relation to the other aims of Phase 3, continued in Phase 4, we have already provided information in Chapter 5 on continuity and bridging between NS-SEC and both SC and SEG. 6.7 Analysis of LFS data on employment relations. The main objective of this exercise was to create NS-SEC categories so as to minimise within class and maximise between class variation in respect of employment relations. Operationally, this involved allocating all the SOC90 OUG/employment status combinations in the interim NS-SEC Derivation Matrix to class categories by reference to their employment relations. For this purpose, we selected seven of the employment relations indicators that had previously been tested in the Omnibus surveys those on incremental pay, form of payment, notice required, promotion and career opportunities, and autonomy (see Appendix 7). Taken together, salary payments, the presence of an incremental scale, a longer period of notice and a high degree of autonomy would indicate a service relationship. Their absence would suggest a labour contract. A mixture of positive and negative values on these items would indicate a mixed form of employment regulation. Only one of the three autonomy questions, that on time, was eventually used to construct the NS-SEC. These seven questions were then carried on the LFS for the November 1996 to January 1997 quarter. We also used other information on occupations to assist us in the allocation of OUG/employment status combinations to classes, especially SOC Volume 1 (OPCS 1990), the 371 database and Occupations 1996 (Leavesley 1996). 6.8 Procedures: the role of statistical analysis in the construction of the NS-SEC. Although our objective was thus clear, we could not allow our operational procedures to be wholly driven by statistical analysis, for four reasons. First, it would have resulted in a loss of continuity with SEG and SC. Second, the resulting classes would not necessarily have had any face validity. Third, it would have been dangerous to rely so heavily on the results of analyses from a single dataset, and for only five out of a far wider potential set of employment relations indicators. Finally, the numbers in some of the cells of the matrix were too small for any meaningful or significant results to be obtained from LFS analyses. As a result, allocation of SOC90 OUG/employment status combinations to classes depended on maintaining a delicate balance between interpreting the results from the LFS, maintaining continuity with former SECs, achieving face validity, and drawing on other sources of information when necessary. Details of the procedures used in Phase 3 have been reported previously (see Rose and O Reilly 1998: Appendix 7). These comments apply equally to the construction in Phase 4 of the final, SOC2000- based version of the NS-SEC, as discussed later. 6.9 The new classes. Following various iterations (described in Rose and O Reilly ibid: Appendix 7), we settled on a version of the NS-SEC and an associated matrix for validation analyses. The LFS data did yield distinct categories in employment relations terms. Moreover, the categories remained robust even for women in part-time employment (see Rose and O Reilly 1998: Section 5) Phase 3 and 4 validation studies. We undertook two forms of validation study in relation to the NS-SEC criterion validation and construct validation. Criterion validation is concerned with the extent to which the conceptual basis of a measure is sound, in this case that it is possible to distinguish between NS-SEC categories in terms of variations in employment relations and conditions as measured by our LFS indicators. Thus here we were investigating the validity of the NS-SEC by examining the consequences of the allocation of SOC OUG/employment status combinations to NS-SEC categories. However, because the NS-SEC classes were constructed on the basis of information provided by LFS respondents on their employment contracts, criterion validation was built in to the procedures we used. It is a procedure that Goldthorpe (1997) has referred to as ex ante validation. Hence, what we have here called criterion validation studies might better be regarded as tests of the adequacy with which NS- SEC classes have been constructed in relation to the underlying concept of employment relations and our LFS data. Construct validation relates to how well the NS-SEC explains variance in theoretically relevant dependent variables of importance to government researchers, social scientists and other academics. Together the two types of validation study thus fulfilled the main assessment criteria for classifications advocated by Fox 47

56 Chapter 6 The National Statistics Socio-economic Classification: Origins, Development and Use and Goldthorpe (see ; and for more detail on validation as discussed here see Appendix 8) Phase 3 studies. The details of the criterion validation studies conducted in Phase 3 need not concern us since we have discussed them elsewhere (see Rose and O Reilly 1998: ). All we need to say here is that these validation studies demonstrated that the interim NS-SEC captured satisfactorily differences between categories (that is, classes) in terms of our LFS measures. The NS-SEC also satisfactorily captured employment relations for both males and females and for full-time and part-time employees within the same occupation and employment status combinations The service relationship score. In both Phases 3 and 4 we used an index (the service relationship score (SRS) constructed as an additive scale of the binary values assigned to each employment relations variable to indicate the presence (1) or absence (0) of a service relationship) for some of our analyses. Thus the SRS was a derived employment regulation variable. Its value was calculated for each OUG/employment status combination. The reliability of the SRS scale was assessed and proven satisfactory, that is, it was demonstrated that the linear combination of the employment relations variables formed an internally consistent scale and that no item was redundant (see McKnight 1997a; McKnight and Elias 2003). Each item thus captured a related but different aspect of employment relations. An NS-SEC derivation matrix was then constructed in which each cell was as internally homogeneous as possible with respect to employment relations. The SRS was also employed for validation analysis using both correlation matrices and Ordinary Least Squares regression (see McKnight and Elias ibid) Other techniques used. It was important to explore the internal homogeneity of, and the heterogeneity between, NS- SEC classes using a variety of other sophisticated multivariate techniques. Although Ordinary Least Squares regression work is useful in this respect, it was agreed that we should also examine the homogeneity/heterogeneity issue using both logistic regression and hierarchical clustering methods. Again these techniques were used in both Phases 3 and 4. They tended to confirm the Ordinary Least Squares regression analyses in terms of the adequacy of the NS-SEC as a measure. That is the NS-SEC has substantial effects on the probability of respondents to the LFS reporting employment relations consistent with either service or labour contracts Construct validation. A number of projects in Phase 3 examined the construct validity of the interim NS-SEC (see Rose and O Reilly 1998: ). These studies demonstrated the discriminatory power of the NS-SEC as an analytic tool and showed its superiority over SC and SEG. As we shall see, the Phase 3 construct validation studies were repeated in Phase 4 in respect of the final version of the NS-SEC and produced similar results. Creating SOC2000 NS-SEC 6.15 Phase 4. As we noted previously, Phase 4 was largely concerned with rebasing the NS-SEC on the new Standard Occupational Classification, SOC2000, and then validating the resulting final version of the NS-SEC described in Chapter 5. In terms of the difficulties of the re-basing, SOC2000 departed further than we had originally expected on the basis of the main relationships between SOC90 and SOC2000 indicated in the Framework of SOC2000 provided to us by ONS s Census Division. Staff on Census Division used a draft of the SOC2000 job title coding index to code the 1996/97 LFS data to SOC2000. When we compared this coding with the SOC90 coding originally produced by the LFS interviewers we discovered differences beyond those indicated in the Framework of SOC2000. This is not surprising given both that (a) the Framework only showed the movements of large parts of SOC90 unit groups and (b) the well-known problem of inter-coder reliability on occupation data The process of creating SOC2000 NS-SEC. In considering the allocation of OUG/employment status combinations to SOC2000 NS-SEC, we followed the same basic procedures as those used to create the interim, SOC90 NS-SEC. That is, we examined SRSs derived from the employment relations questions on the 1996/97 LFS. In addition, other sources of relevant information were considered. These included: occupational (employment relations and conditions) information obtained from employers organisations and trades unions; careers databases; Occupations 2000, also produced for careers guidance purposes; academic books and papers; Incomes Data Services reports (for example, IDS 1999); New Earnings Survey data; and new analyses of LFS occupational text data. Sometimes we changed NS-SEC allocations of occupations from their previous position after a consideration of some or all of these sources Changes induced by SOC2000. Equally, however, the structure of SOC2000 itself induced changes from the interim NS-SEC, especially with regard to managers. Allocation to a managerial NS-SEC category is now necessarily restricted to OUGs in SOC2000 Major Group 1. This reduced the proportion of managers in large enterprises by approximately 33 per cent and those in small enterprises by 20 per cent. Also, as explained in Chapter 5, we took advantage of the more refined nature of OUGs in Major Group 1 in relation to the conceptual basis of the NS-SEC and its operationalisation. Thus, as we 48

57 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 6 indicated in Chapter 5, size of establishment is no longer always the means for determining allocation to either L2 or L5, the higher and lower managerial categories in the operational version of NS-SEC Creating the SOC2000 NS-SEC matrix. We first examined each SOC2000 OUG in terms of its relation to SOC90 OUGs. In most cases there appeared to be no major problems in allocating an operational version NS-SEC category to an SOC2000 OUG/employment status combination. Only 110 SOC2000 OUGs (31 per cent of OUGs) seemed at all problematic and thus requiring further examination. Once again we used service relationship scores to determine the allocation of OUG/employment status combinations to NS-SEC categories. However, the rebasing exercise also allowed us to reconsider some of the tentative decisions made when we created the interim, SOC90 NS-SEC. Thus, some occupations were re-allocated in the light of both re-analysis of LFS data using SOC2000 and new information on occupations, which was not previously either considered or available. Consequently, some of the changes we made between the interim and final versions of NS-SEC were over and above what was strictly required by the rebasing exercise. For example, we made some changes to the allocations of professionals between L3 higher professionals and L4 lower professionals (Classes 1 and 2). In addition, we reallocated some small employers and selfemployed from L4 to either L8 Small employers or L9 Ownaccount workers, Class 2 to Class 4. Above all, we re-examined the way in which lower sales, services and clerical occupations are allocated. This required us to create three versions of SOC2000 NS-SEC for testing. Each version employed a different method for allocating these occupations to NS-SEC categories. Following various validation exercises on the three versions, we elected to leave lower sales, etc, occupations in their original position, L12, Class 6. The alternative would have been a separate class for these occupations (see Rose and Pevalin 2003d). However, some similar occupations previously in L7 are also now in L12. Finally, re-analysis of LFS data using SOC2000 suggested various reallocations of OUGs between L11, L12 and L13. At the same time, we took the opportunity to create new sub-categories of the operational version and to revise category names so that they were more in line with the underlying concept of the NS- SEC New sub-categories of the operational version (1). To improve the coverage of self-employment, we created new sub-categories for professionals in L3 and L4. These are for traditional professional small employers and self-employed (L3.3 and L4.3) and the equivalents among new professionals (L3.4 and L4.4) New sub-categories of the operational version (2). To improve bridging between SC, SEG and NS-SEC, we created L7.4 for skilled workers in certain engineering occupations; L7.3 is now used for intermediate technicians and auxiliaries. L11, lower technical occupations, has been divided between former skilled or craft workers ( lower technical craft occupations 11.1), and process workers in lower technical process operative occupations (11.2). L12 has new subcategories for clerical occupations (12.6) and for childcare occupations (12.7). L13 also has new categories for technical occupations (13.3) and for agricultural occupations (13.5). Compared with the interim NS-SEC, the ordering of subcategories has been altered in L12 and L13. This re-ordering allows sub-categories in L12 and L13 of the final version (roughly) to correspond New names of operational version categories (1): managers. To accord with the changes to the allocation of managers between L2 and L5, discussed earlier, we have renamed L2 as higher managerial occupations and L5 as lower managerial occupations. Previously L2 was managers in large organisations and L5 was managers in small organisations. However, since organisations size is no longer the wholly determining factor in allocating managers between these categories, we need to change the names New names of operational version categories (2): professionals. As previously noted, we also believe that both the conceptual base of the NS-SEC and the face validity of categories is made clearer for professionals by changing the name of L3 from professionals to higher professional occupations and of L4 from associate professionals to lower professional and higher technical occupations. This also allows us to place occupations such as teachers and librarians in L4, Class 2 when previously they were in L3, Class 1 of the interim version. While such occupations could not have been regarded as associate professionals, they can properly be categorised as lower professionals New names of operational version categories (3): skilled workers. L11 was formerly called craft and related occupations. This name had two problems. First, and inappropriately, it introduced ideas of skill into the NS-SEC. Secondly, not all the OUGs in L11 are craft or skilled manual occupations in the traditional sense, as now indicated by the sub-category divisions. We have thus changed the name of this category to lower technical occupations. Hence, we have higher technicians in L4, intermediate technicians in L7 and lower technicians in L New names of operational version categories (4). All category names have been changed where necessary to 49

58 Chapter 6 The National Statistics Socio-economic Classification: Origins, Development and Use include the word occupations rather than employees or to qualify a name (for example, higher managers becomes higher managerial occupations to emphasise that we are dealing with positions and not people) New names of official NS-SEC categories. The changes to operational version category names have repercussions for NS- SEC category names. Class 1.1 becomes large employers and higher managerial occupations and 1.2 is now higher professional occupations. Class 1 overall is now described as higher managerial and professional occupations ; Class 2 is lower managerial and professional occupations ; and Class 5 is lower supervisory and technical occupations. The phrase employees in is dropped from Classes 6 and 7. Continuity issues 6.26 Bridging and continuity between NS-SEC, SC and SEG (1). Some of the above changes facilitated bridging and continuity between NS-SEC and the old classifications. However, there was a further problem we had to overcome in this area. A comparison between SOC90 SC and SEG and SOC2000 NS-SEC would hardly have been helpful in judging continuity and bridging issues. In order to examine these relationships properly, it was first necessary for us to create SOC2000 versions of both SC and SEG. This was achieved by assuming that all SOC2000 OUGs that corresponded to SOC90 OUGs would be given the same SC and SEG values. Each new SOC2000 OUG was given the values of the most frequently occurring SOC90 OUG(s) within it. This allowed us to construct tables showing the relationships between SOC90 and SOC2000 versions of SC and SEG respectively. They showed by approximately how much each would have changed due solely to SOC changes (5.2 per cent and 8.3 per cent respectively). We did not make any other changes to SC and SEG allocations that we believe would have necessarily been undertaken by ONS simply in order to catch up with SOC90 and other secular changes. For example, in the case of the former, we might have expected the reallocation of auxiliary nurses from Social Class II to Social Class IIIN (see Elias 1997). Of course, the SOC2000 matrices for SC and SEG are unofficial and thus are not reproduced in this report. However, the matrices may be obtained from the authors for those who wish to derive SC and SEG for SOC2000 to aid in both time series and comparisons between NS-SEC, SC and SEG Bridging and continuity (2). As noted, we have created a few new sub-categories of the operational version in order to improve bridging between the NS-SEC, SC and SEG. Once this was done, continuity was improved to the levels shown previously in Chapter 5, Tables 1 and 2: 87 per cent with both SC and SEG. The levels of continuity here compare with 91 per cent for SC and 88 per cent for SEG with the interim NS-SEC. We have also created SOC90 matrix for the final SOC2000 based NS-SEC (see Appendices 5 and 6). This was used in some of the validation studies and is 95+ per cent accurate. Hence users may create the NS-SEC from existing SOC90 occupational data. Phase 4 validation studies 6.28 Phase 4 validation studies Finally we turn to the validation studies undertaken on the SOC2000version of NS-SEC. Since these studies have been extensively reported elsewhere (see Rose and Pevalin 2003a), here we simply summarise the results, beginning with the criterion validation projects Criterion validation. A measuring instrument is valid if it does what it is intended to do. An indicator of some abstract concept is valid to the extent that it measures what it purports to measure Validity concerns the crucial relationship between concept and indicator (Carmines and Zeller, 1979:12). In the case of the NS-SEC, therefore, we need to know that it is a reasonably adequate measure of the conceptualisation of the social structure set out in Chapter 4. The Review team chose a method of ex ante validation that involved a special data collection exercise in the 1997 LFS. The LFS data were analysed along lines described already (and see O Reilly and Rose 1997 and 1998c; Rose and O Reilly 1998). As we have seen, the NS-SEC classes have been constructed on the basis of information provided by individuals on their employment relations. Each class has been designed to be as internally homogeneous in these terms as possible. Thus, as we noted previously, criterion validation is built into the procedures we used. It is therefore somewhat tautological to refer to the analyses discussed below as being criterion validation studies equivalent to those used for ex post validation studies along the lines of those previously undertaken by Evans, Mills and others in relation to the Goldthorpe schema. Rather, the NS-SEC studies relate to the adequacy with which we have constructed classes in relation to the underlying employment relations concept using our LFS data and other information we collected about occupations. Partly for this reason, the Review team deliberately chose to employ a variety of different methods to assess the NS-SEC. Fuller accounts of the Phase 4 validation studies have been given elsewhere (Rose and Pevalin 2003a). Here we simply summarise the key findings Validation studies (1). McKnight and Elias (2003) used multivariate Ordinary Least Squares regression models to assess variations in employment relations and conditions, as measured by a five-item SRS, across SOC90 and SOC2000 and five 50

59 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 6 measures of social class that included two versions of the NS- SEC. They concluded that the seven-class version of the NS- SEC was characterised by a strong gradient in the SRS. Nevertheless, two classes (lower supervisory and technical occupations and semi-routine occupations [Classes 5 and 6]) cannot be distinguished in terms of average adjusted SRSs (p.66). This finding reflects the fact that these two classes do indeed have similar SRS scores. However, what distinguishes them from one another is the actual items on which they scored. This is discussed by Rose and Pevalin (2003d) in their analysis of the least satisfactory of all the NS-SEC classes Class Validation studies (2). Mills and Evans (2003) utilised a series of RC(M) log-multiplicative models to investigate variations in employment relations items across 26 employee groups drawn from the operational categories and subcategories of the NS-SEC. While noting that they did not conduct a validation exercise in the conventional sense they do confirm that the constructors of the NS-SEC seem to have done a reasonable job of allocating occupations to NS-SEC categories so as to minimise within-group variation (p.102). However, they also raise the same issue as McKnight and Elias concerning the placement of at least some occupations in Class 6. This class includes some low-grade sales, services and clerical occupations, as we saw in Chapter 5. Mills and Evans conclude that some of these occupations appear to be located equidistant from Classes 3 and 7, but are not quite similar to the rest of Class 6. They also note, however, that a schema such as the NS-SEC will always find it more difficult to allocate occupations with mixed forms of employment regulation than those with service relationship or labour contract forms (ibid: 101). The operational sub-categories of most concern in relation to Class 6 L12.1, L12.2, L12.6 and L12.7 have thereby been fully identified. This means that analysts may take advantage of the nested structure of the NS-SEC to look inside Class 6 and further investigate it. Similarly, Evans and Mills noted some differences between the higher managerial and higher professional occupations in Class 1. We have commented on this before. Once again, the structure of the NS-SEC gives analysts the flexibility to investigate whether any differences between the two main elements of Class 1 are significant to the problems they are confronting Validation studies (3). Coxon and Fisher (2003) used cluster analysis at the individual level and correspondence analysis at the occupational unit group level to further examine the adequacy of allocations within the NS-SEC. Their analysis did generally support the validity of the NS-SEC but, in similar fashion to Evans and Mills, they found that NS-SEC allocations were better for some occupational groupings (for example, managers, clerks and craft workers) than for others Validation studies (4). Fisher (2003) had a rather different focus and explored Goldthorpe s (1997) recommendation to consider creating a special employment status category for part-time employment. Fisher found that there were differences between full and part-time employees within the same class and that this difference existed for both men and women. She concluded that researchers using the NS-SEC for individual-level analysis would be wise to control for both sex and full-time or part-time status in order to prevent effects related to these employment condition gaps from colouring the subsequent analysis (Fisher 2003:146). This is sensible advice, of course. Nevertheless, the creation of an additional dimension of the derivation matrix relating to part-time working would not have been justified. The fact is that parttime employment is highly concentrated in a relatively small number of OUGs and is best dealt with by the method Fisher recommends Construct validation. The main issue here is whether the NS-SEC adds value to the explanation of life chances. Is it a better measure to use than, say, SOC2000 major groups? Does it compare well with or improve upon the current instantiation of the Goldthorpe schema? How does it compare with the previous government classifications SC and SEG? How useful is it for the investigation of relevant problems? These are issues of construct validation. That is, judging a concept and its measurement in terms of empirical consequences and analytic transparency. Most of the construct validation studies focus on how the NS-SEC relates to various dimensions of health inequalities with one exception. We should also note that the final version of the NS-SEC, as based on SOC2000, had to be validated in these studies using a SOC90-based approximation to it (SEC90) SEC90. The derivation matrices for SEC90 are given in appendices 5 and 6. As is evident from Table 9, the level of agreement on the LFS between the SOC2000 and SOC90 versions of NS-SEC varies from per cent for Class 1 to 96 per cent from Class 4. The overall agreement is almost 90 per cent. We therefore regard SEC90 as a reliable measure for those who wish to apply the NS-SEC to data coded to SOC90 and thus create time-series data for it. An example of this type of analysis is provided in a recent article by Rowan (2003). Rowan examines the implications of changes for SC/SEG to NS-SEC for infant mortality statistics. When comparing NS-SEC and SEC90 for the eight-class version, he finds an overall agreement of 85 per cent. This increased to 90 per cent and 92 per cent for the five- and three-class versions of NS-SEC. Once 51

60 Chapter 6 The National Statistics Socio-economic Classification: Origins, Development and Use Table 9 SOC2000 NS-SEC by SOC90 NS-SEC (SEC90) seven-class SEC Total SOC2000 NS-SEC HMP LMP Int SE&OAW LS&TO S-RO RO 1 Higher managerial and professional occupations 5, , (76.67) (6.25) (2.51) (0.64) (1.09) (0.21) (0.29) (11.08) 2 Lower managerial and professional occupations 1,274 12, , (17.07) (83.86) (5.53) (1.75) (5.23) (2.35) (0.80) (23.69) 3 Intermediate occupations , , (3.72) (4.08) (85.10) (0) (2.41) (1.99) (0.96) (14.12) 4 Small employers and own-account workers , , (0.75) (1.21) (0) (97.61) (0) (0) (0) (10.00) 5 Lower supervisory and technical occupations , , (0.74) (2.39) (0.52) (0) (85.58) (1.27) (1.18) (9.90) 6 Semi-routine occupations , , (0.94) (1.97) (5.88) (0) (3.26) (90.86) (6.40) (18.62) 7 Routine occupations ,434 8, (*) (0.24) (0.46) (0) (2.43) (3.31) (90.57) (12.73) Total 7,464 14,723 8,916 6,237 6,503 11,171 8,208 63, (100) (100) (100) (100) (100) (100) (100) (100) again, level of agreement was lowest for managers, mainly due to changes in the treatment of managerial occupations in SOC2000, a matter on which we have already commented. Donkin and her colleagues (2002) produced similar results to Rowan s when examining mortality data in relation to SEC Validation studies (5). Elias and McKnight (2003) used data from both the LFS and the British Household Panel Survey to assess how the NS-SEC classes relate to earnings and prospective experiences of unemployment. They hypothesised a direct link between the NS-SEC and risk of unemployment in that those in occupations with a labour contract are more likely (and easily) to be made redundant and more likely to leave their current employer without first securing other employment. Using longitudinal data, they then demonstrated the prospective effect of class on experiences of unemployment in that those in NS-SEC Classes 6 and 7 are significantly more likely to experience unemployment than those in Classes 1 to Validation studies (6). Fitzpatrick (2003) used death registration data to examine differences in mortality rates. Her analysis brings out a number of issues worth highlighting. First is the appropriate use of Census data to form the population denominators. Fitzpatrick details the differing distributions obtained by two methods of deriving the NS-SEC: one with full employment status information and the other using the reduced method, where size of organisation information is missing. From this Fitzpatrick advises that as the reduced method has to be used to derive the NS-SEC on the death registration data, the same derivation method should be used on the Census data when Census data is taken as the denominator in mortality analysis. She also draws attention to the potential differences between occupational information coded from relatively brief information, such as on the Census and death registers, and that coded using much more detailed information, such as in the LFS. 52

61 The National Statistics Socio-economic Classification: Origins, Development and Use Chapter 6 A further point brought out in Fitzpatrick s study is the distinctive mortality patterns of the non-professional selfemployed in NS-SEC Class 4. Previously the people in this class would have been distributed across multiple SC classes, so that such differences could not be identified. While a distinctive pattern for the self-employed holds for adult and infant mortality the reasons for this remain to be fully uncovered Validation studies (7). Pevalin (2003) used birth registration data to investigate social class differentials in low weight births. He hypothesised an indirect relationship from the NS-SEC to the outcome of his study low weight births. In this case what the NS-SEC directly measures, employment relations and conditions, had no direct bearing on his hypotheses. This is for two reasons. First, the father s NS-SEC class is used as a crude measure of household class. Second, the concept of employment relations is seen as central to defining socio-economic position and it is these positions, which exist independently of the individuals who happen to occupy them at any particular time, that determine material and symbolic advantages. It is from these advantages that processes, such as maternal nutrition and smoking, may link class with low-weight births. Thus, Pevalin s study provides an example of the type of approach to specifying causal effects that we discussed in Chapter Validation studies (8). Cooper and Arber (2003) analysed data from the General Household Survey to examine gender and age differences in self-reported health and limiting longterm illness in relation to the NS-SEC, with a special focus on allocation to Class 8. They detail the operational and analytical issues and expand on these initial problems to include a discussion of how gender and age are particularly relevant to the analysis of Class 8. Indeed, more generally, the changes in and the nature of female participation in the labour market over time and how these are adequately captured in occupational and socio-economic classifications remains an active debate (for example, Crompton et al., 2000; Evans, 1996) Validation studies (9). Although Heath, Martin and Beerten (2003) use three distinct outcomes smoking, housing tenure and voting intention in their analysis of British Household Panel Survey data, their main concern is to offer a guide to researchers on continuity issues between SC and the NS-SEC. While they warn that continuity between SC and NS- SEC will never be exact, they conclude that approximations of SC from the NS-SEC operational version should not cause any problems to former users of the SC. They also conclude that the eight-class version of NS-SEC represents an improvement over SC in terms of greater discriminatory power in respect of the outcome variables they investigated. 53

62 Chapter 6 The National Statistics Socio-economic Classification: Origins, Development and Use 54

63 Conclusions Chapter 7

64 Chapter 7 The National Statistics Socio-economic Classification: Origins, Development and Use 7. Conclusions 7.0 What have we achieved? In both this and our previous reports on the Review, we have demonstrated that government socio-economic classifications (SECs) are still required for policy purposes and for policy-related and academic research. However, we have also seen in Chapter 3 that the former classifications were inadequate to the tasks demanded of them. We have examined alternative, occupationally-based SECs and we have concluded that adopting (but also adapting) the Goldthorpe class schema offered the best and most efficient means to the end of producing a new government SEC (see also Rose 1996; Rose and O Reilly 1997a and b; Rose, O Reilly and Martin 1997). We have conducted the necessary theoretical, methodological and empirical research to produce, assess and validate the NS-SEC (Chapters 4, 5 and 6). And we have consulted widely in the process. 7.1 The NS-SEC. The National Statistics Socio-economic Classification has the following features to commend it: (a) it is conceptually clear and rigorous; (b) it is simple to operationalise; (c) through both its hierarchical properties and its variants full, reduced, simplified and self-coded it is very flexible in use; (d) it offers a high degree of continuity and thus comparability with both Social Class based on Occupation (SC) and Socio-economic Groups (SEG); (e) it provides an improved classification of women s employment positions; 7.2 Review procedures. Of course, we do not claim to have resolved all the problems posed by our work. However, we have published and attempted to explain our procedures, both here and elsewhere, so that others may follow them and, if so moved, criticise them. Within this report, we have given a full account of the conceptual, operational and continuity issues in relation to each of the categories of the operational version of the NS-SEC; and we have shown the various ways in which it may be collapsed for analysis. We have also discussed our validation methods, studies and procedures. 7.3 A final commendation. In creating SC, T H C Stevenson produced a classification which, remarkably, was used for nearly a century and which was directly responsible for much of our appreciation of the link between socio-economic factors and the distribution of life chances. Given that Stevenson s work pre-dated serious social science in this country, his achievement must be seen as all the more exceptional. However, compared with the best of contemporary, sociologically informed classifications, SC cannot as fully comprehend the nature of modern inequalities of reward and condition, their causes and consequences. The Office for National Statistics (ONS) realised this, which is why it requested the Economic and Social Research Council (ESRC) to organise the Review. We now offer in this report our conclusions and recommendations relating to a new SEC for the 21st century. We hope the NS-SEC will prove to be as significant for an understanding of our society, and its more opaque and subtle stratification processes, as Stevenson s social class schema was for a world where socio-economic classes were both more sharply differentiated and manifest. (f) when fully operationalised, it enables improved population coverage; (g) it has clearer maintenance procedures than those that pertained to the former SECs; (h) it provides the possibility of a standardised tool for use in government, academia and the private sector; and (i) above all, it provides both government and academic users with a tool which lends itself to the explanation of relationships, and thus to both more lucid policy recommendations and a better understanding of social processes. We have no doubt that the NS-SEC will set new puzzles for analysts and will uncover fresh avenues of exploration. 56

65 Review Committee membership Appendix 1

66 Appendix 1 The National Statistics Socio-economic Classification: Origins, Development and Use The Review Committee s membership was as follows: Professor David Lockwood University of Essex Chairperson Professor David Rose University of Essex Academic Convenor Dr Karen O Reilly University of Essex Assistant Academic Convenor (resigned 1999) Dr David J Pevalin University of Essex Assistant Academic Convenor ( ) Professor Sara Arber University of Surrey Richard Bland University of Stirling Professor Rosemary Crompton University of Leicester (now City University) (resigned 1997) Professor Angela Dale University of Manchester Professor Peter Elias University of Warwick Professor Ray Fitzpatrick Nuffield College, Oxford Professor Roderick Floud London Guildhall University Dr Peter Goldblatt Home Office/ONS Professor Gordon Marshall Nuffield College, Oxford (now University of Reading) Professor Jean Martin ONS Dr Catrin Roberts ESRC 1994/95 and 1999 Kevin Hamilton ESRC 1995/97 Martin Kender ESRC 1997/98 Roger Thomas Joint Centre for Survey Methods, SCPR Margaret Gutteridge University of Essex Committee Secretary 1994/95 Janice Webb University of Essex Committee Secretary

67 Continuity issues: SC, SEG and NS-SEC Appendix 2

68 Appendix 2 The National Statistics Socio-economic Classification: Origins, Development and Use The operational categories of the NS-SEC can be aggregated to produce approximated Social Class based on Occupation (SC) and approximated Socio-economic Group (SEG), as shown in Tables A2.A, B and C. These approximations achieve a continuity level of 87 per cent for both SC and SEG. In the course of re-basing the NS-SEC on SOC2000, we produced a derivation of SC and SEG based on SOC2000 by making certain assumptions on changes over time and assessments of the relationship between SOC90 and SOC2000 unit groups. This is available from the website of the Institute for Social and Economic Research at the University of Essex ( Additionally, the NS-SEC based on SOC90 has been developed and is given in Appendices 5 and 6. Table A2.A: Operational categories of the NS-SEC linked to Social Class Social Class NS-SEC operational categories I Professional, etc. occupations 3.1, 3.3 II Managerial and technical occupations 1, 2, 3.2, 3.4, 4.1, 4.3, 5, 7.3, 8.1, 8.2, 9.2 III N Skilled occupations non-manual 4.2, 4.4, 6, 7.1, 7.2, 12.1, 12.6 III M Skilled occupations manual 7.4, 9.1, 10, 11.1, 12.3, 13.3 IV Partly skilled occupations 11.2, 12.2, 12.4, 12.5, 12.7, 13.1, 13.2, 13.5 V Unskilled occupations 13.4 Table A2.B: Operational categories of the NS-SEC linked to Socio-economic Groups Socio-economic Group NS-SEC operational categories 1 Employers and managers in central and local government, industry, commerce, etc. large establishments 1.1 Employers in industry, commerce, etc. large establishments Managers in central and local government, industry, commerce, etc. large establishments 2 2 Employers and managers, industry, commerce, etc. small establishments 2.1 Employers in industry, commerce, etc. small establishments Managers in industry, commerce, etc. small establishments 5 3 Professional workers self-employed Professional workers employees Intermediate non-manual workers 5.1 Ancillary workers and artists 3.2, 3.4, 4.1, 4.3, Foremen and supervisors non-manual 6 6 Junior non-manual workers 4.2, 7.1, 7.2, 12.1, 12.6, 7 Personal service workers 12.7, Foremen and supervisors manual 10 9 Skilled manual workers 7.4, 11.1, 12.3, Semi-skilled manual workers 11.2, 12.2, 12.4, Unskilled manual workers Own-account workers (other than professional) 4.4, Farmers employers and managers Farmers own account Agricultural workers 12.5, Members of the armed forces - 17 Inadequately described and not stated occupations 16 60

69 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 2 Table A2.C: Social Class and Socio-economic Group linked to operational categories of the NS-SEC National Statistics Socio-economic Classification operational categories Approx. Social Class Approx. SEG L1 Employers in large organisations II 1.1 L2 Higher managerial II 1.2 L3.1 Higher professionals (traditional) employees I 4 L3.2 Higher professionals (new) employees II 5.1 L3.3 Higher professionals (traditional) self-employed I 3 L3.4 Higher professionals (new) self-employed II 5.1 L4.1 Lower professionals and higher technical (traditional) employees II 5.1 L4.2 Lower professionals and higher technical (new) employees IIIN 6 L4.3 Lower professionals and higher technical (traditional) self-employed II 5.1 L4.4 Lower professionals and higher technical (new) self-employed IIIN 12 L5 Lower managerial II 2.2 L6 Higher supervisory IIIN 5.2 L7.1 Intermediate clerical and administrative IIIN 6 L7.2 Intermediate sales and service IIIN 6 L7.3 Intermediate technical and auxiliary II 5.1 L7.4 Intermediate engineering IIIM 9 L8.1 Employers in small organisations (non-professional) II 2.1 L8.2 Employers in small organisations (agriculture) II 13 L9.1 Own-account workers (non- professional) IIIM 12 L9.2 Own-account workers (agriculture) II 14 L10 Lower supervisory IIIM 8 L11.1 Lower technical craft IIIM 9 L11.2 Lower technical process operative IV 10 L12.1 Semi-routine sales IIIN 6 L12.2 Semi-routine service IV 10 L12.3 Semi-routine technical IIIM 9 L12.4 Semi-routine operative IV 10 L12.5 Semi-routine agriculture IV 15 L12.6 Semi-routine clerical IIIN 6 L12.7 Semi-routine childcare IV 7 L13.1 Routine sales and service IV 7 L13.2 Routine production IV 10 L13.3 Routine technical IIIM 9 L13.4 Routine operative V 11 L13.5 Routine agricultural IV 15 L14.1 Never worked - - L14.2 Long-term unemployed - - L15 Full-time students - - L16 Occupations not stated or inadequately described - 17 L17 Not classifiable for other reasons

70 Appendix 2 The National Statistics Socio-economic Classification: Origins, Development and Use 62

71 The SOC2000 NS-SEC derivation table: simplified and full methods, operational categories Appendix 3

72 Appendix 3 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 3 continued Appendix 3 Standard Occupational Classification 2000 Unit Group Simplified Employment status/size of organisation NS-SEC 1 Employers 2 Employers 3 Self- 4 Managers 5 Managers 6 Supervisors 7 Other - large - small employed, - large - small employees organisations organisations no employees organisations organisations The SOC2000 NS-SEC derivation table: simplified and full method, operational categories Standard Occupational Classification 2000 Unit Group Simplified Employment status/size of of organisation NS-SEC 1 Employers 2 Employers 3 Self- 4 Managers 5 Managers 6 Supervisors 7 Other - large - small employed, - large - small employees organisations organisations no employees organisations organisations 1111 Senior officials in national government Directors and chief executives of major organisations Senior officials in local government Senior officials of special interest organisations Production, works and maintenance managers Managers in construction Managers in mining and energy Financial managers and chartered secretaries Marketing and sales managers Purchasing managers Advertising and public relations managers Personnel, training and industrial relations managers Information and communication technology managers Research and development managers Quality assurance managers Customer care managers Financial institution managers Office managers Transport and distribution managers Storage and warehouse managers Retail and wholesale managers Officers in armed forces Police officers (inspectors and above) Senior officers in fire, ambulance, prison and related services Security managers Hospital and health service managers Pharmacy managers Healthcare practice managers Social services managers Residential and day care managers Farm managers Natural environment and conservation managers Managers in animal husbandry, forestry and fishing n.e.c Hotel and accommodation managers Conference and exhibition managers Restaurant and catering managers Publicans and managers of licensed premises Leisure and sports managers Travel agency managers Property, housing and land managers Garage managers and proprietors Hairdressing and beauty salon managers and proprietors Shopkeepers and wholesale/retail dealers Recycling and refuse disposal managers Managers and proprietors in other services n.e.c Chemists Biological scientists and biochemists Physicists, geologists and meteorologists

73 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 3 Appendix 3 continued Standard Occupational Classification 2000 Unit Group Simplified Employment status/size of organisation NS-SEC 1 Employers 2 Employers 3 Self- 4 Managers 5 Managers 6 Supervisors 7 Other - large - small employed, - large - small employees organisations organisations no employees organisations organisations 2121 Civil engineers Mechanical engineers Electrical engineers Electronics engineers Chemical engineers Design and development engineers Production and process engineers Planning and quality control engineers Engineering professionals n.e.c IT strategy and planning professionals Software professionals Medical practitioners Psychologists Pharmacists/pharmacologists Ophthalmic opticians Dental practitioners Veterinarians Higher education teaching professionals Further education teaching professionals Education officers, school inspectors Secondary education teaching professionals Primary and nursery education teaching professionals Special needs education teaching professionals Registrars and senior administrators of educational establishments Teaching professionals n.e.c Scientific researchers Social science researchers Researchers n.e.c Solicitors and lawyers, judges and coroners Legal professionals n.e.c Chartered and certified accountants Management accountants Management consultants, actuaries, economists and statisticians Architects Town planners Quantity surveyors Chartered surveyors (not quantity surveyors) Public service administrative professionals Social workers Probation officers Clergy Librarians Archivists and curators Laboratory technicians Electrical/electronics technicians Engineering technicians Building and civil engineering technicians Quality assurance technicians Science and engineering technicians n.e.c Architectural technologists and town planning technicians Draughtspersons Building inspectors IT operations technicians IT user support technicians Nurses Midwives Paramedics Medical radiographers Chiropodists Dispensing opticians

74 Appendix 3 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 3 continued Standard Occupational Classification 2000 Unit Group Simplified Employment status/size of organisation NS-SEC 1 Employers 2 Employers 3 Self- 4 Managers 5 Managers 6 Supervisors 7 Other - large - small employed, - large - small employees organisations organisations no employees organisations organisations 3217 Pharmaceutical dispensers Medical and dental technicians Physiotherapists Occupational therapists Speech and language therapists Therapists n.e.c Youth and community workers Housing and welfare officers NCOs and other ranks Police officers (sergeant and below) Fire service officers (leading fire officer and below) Prison service officers (below principal officer) Protective service associate professionals n.e.c Artists Authors, writers Actors, entertainers Dancers and choreographers Musicians Arts officers, producers and directors Graphic designers Product, clothing and related designers Journalists, newspaper and periodical editors Broadcasting associate professionals Public relations officers Photographers and audio-visual equipment operators Sports players Sports coaches, instructors and officials Fitness instructors Sports and fitness occupations n.e.c Air traffic controllers Aircraft pilots and flight engineers Ship and hovercraft officers Train drivers Legal associate professionals Estimators, valuers and assessors Brokers Insurance underwriters Finance and investment analysts/advisers Taxation experts Importers, exporters Financial and accounting technicians Business and related associate professionals n.e.c Buyers and purchasing officers Sales representatives Marketing associate professionals Estate agents, auctioneers Conservation and environmental protection officers Countryside and park rangers Public service associate professionals Personnel and industrial relations officers Vocational and industrial trainers and instructors Careers advisers and vocational guidance specialists Inspectors of factories, utilities and trading standards Statutory examiners Occupational hygienists and safety officers (health and safety) Environmental health officers Civil Service executive officers Civil Service administrative officers and assistants

75 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 3 Appendix 3 continued Standard Occupational Classification 2000 Unit Group Simplified Employment status/size of organisation NS-SEC 1 Employers 2 Employers 3 Self- 4 Managers 5 Managers 6 Supervisors 7 Other - large - small employed, - large - small employees organisations organisations no employees organisations organisations 4113 Local government clerical officers and assistants Officers of non-governmental organisations Credit controllers Accounts and wages clerks, book-keepers, other financial clerks Counter clerks Filing and other records assistants/clerks Pensions and insurance clerks Stock control clerks Transport and distribution clerks Library assistants/clerks Database assistants/clerks Market research interviewers Telephonists Communication operators General office assistants/clerks Medical secretaries Legal secretaries School secretaries Company secretaries Personal assistants and other secretaries Receptionists Typists Farmers Horticultural trades Gardeners and groundsmen/ groundswomen Agricultural and fishing trades n.e.c Smiths and forge workers Moulders, core makers, die casters Sheet metal workers Metal plate workers, shipwrights, riveters Welding trades Pipe fitters Metal machining setters and setter-operators Tool makers, tool fitters and markers-out Metal working production and maintenance fitters Precision instrument makers and repairers Motor mechanics, auto engineers Vehicle body builders and repairers Auto electricians Vehicle spray painters Electricians, electrical fitters Telecommunications engineers Lines repairers and cable jointers TV, video and audio engineers Computer engineers, installation and maintenance Electrical/electronics engineers n.e.c Steel erectors Bricklayers, masons Roofers, roof tilers and slaters Plumbers, heating and ventilating engineers Carpenters and joiners Glaziers, window fabricators and fitters Construction trades n.e.c Plasterers Floorers and wall tilers Painters and decorators Weavers and knitters Upholsterers Leather and related trades Tailors and dressmakers

76 Appendix 3 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 3 continued Standard Occupational Classification 2000 Unit Group Simplified Employment status/size of organisation NS-SEC 1 Employers 2 Employers 3 Self- 4 Managers 5 Managers 6 Supervisors 7 Other - large - small employed, - large - small employees organisations organisations no employees organisations organisations 5419 Textiles, garments and related trades n.e.c Originators, compositors and print preparers Printers Bookbinders and print finishers Screen printers Butchers, meat cutters Bakers, flour confectioners Fishmongers, poultry dressers Chefs, cooks Glass and ceramics makers, decorators and finishers Furniture makers, other craft woodworkers Pattern makers (moulds) Musical instrument makers and tuners Goldsmiths, silversmiths, precious stone workers Floral arrangers, florists Hand craft occupations n.e.c Nursing auxiliaries and assistants Ambulance staff (excluding paramedics) Dental nurses Houseparents and residential wardens Care assistants and home carers Nursery nurses Childminders and related occupations Playgroup leaders/assistants Educational assistants Veterinary nurses and assistants Animal care occupations n.e.c Sports and leisure assistants Travel agents Travel and tour guides Air travel assistants Rail travel assistants Leisure and travel service occupations n.e.c Hairdressers, barbers Beauticians and related occupations Housekeepers and related occupations Caretakers Undertakers and mortuary assistants Pest control officers Sales and retail assistants Retail cashiers and check-out operators Telephone salespersons Collector salespersons and credit agents Debt, rent and other cash collectors Roundsmen/women and van salespersons Market and street traders and assistants Merchandisers and window dressers Sales related occupations n.e.c Call centre agents/operators Customer care occupations Food, drink and tobacco process operatives Glass and ceramics process operatives Textile process operatives Chemical and related process operatives Rubber process operatives Plastics process operatives Metal making and treating process operatives Electroplaters

77 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 3 Appendix 3 continued Standard Occupational Classification 2000 Unit Group Simplified Employment status/size of organisation NS-SEC 1 Employers 2 Employers 3 Self- 4 Managers 5 Managers 6 Supervisors 7 Other - large - small employed, - large - small employees organisations organisations no employees organisations organisations 8119 Process operatives n.e.c Paper and wood machine operatives Coal mine operatives Quarry workers and related operatives Energy plant operatives Metal working machine operatives Water and sewerage plant operatives Plant and machine operatives n.e.c Assemblers (electrical products) Assemblers (vehicles and metal goods) Routine inspectors and testers Weighers, graders, sorters Tyre, exhaust and windscreen fitters Clothing cutters Sewing machinists Routine laboratory testers Assemblers and routine operatives n.e.c Scaffolders, stagers, riggers Road construction operatives Rail construction and maintenance operatives Construction operatives n.e.c Heavy goods vehicle drivers Van drivers Bus and coach drivers Taxi, cab drivers and chauffeurs Driving instructors Rail transport operatives Seafarers (merchant navy); barge, lighter and boat operatives Air transport operatives Transport operatives n.e.c Crane drivers Fork-lift truck drivers Agricultural machinery drivers Mobile machine drivers and operatives n.e.c Farm workers Forestry workers Fishing and agriculture related occupations n.e.c Labourers in building and woodworking trades Labourers in other construction trades n.e.c Labourers in foundries Industrial cleaning process occupations Printing machine minders and assistants Packers, bottlers, canners, fillers Labourers in process and plant operations n.e.c Stevedores, dockers and slingers Other goods handling and storage occupations n.e.c Postal workers, mail sorters, messengers, couriers Elementary office occupations n.e.c Hospital porters Hotel porters Kitchen and catering assistants Waiters, waitresses Bar staff Leisure and theme park attendants Elementary personal services occupations n.e.c Window cleaners Road sweepers Cleaners, domestics Launderers, dry cleaners, pressers Refuse and salvage occupations

78 Appendix 3 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 3 continued Standard Occupational Classification 2000 Unit Group Simplified Employment status/size of organisation NS-SEC 1 Employers 2 Employers 3 Self- 4 Managers 5 Managers 6 Supervisors 7 Other - large - small employed, - large - small employees organisations organisations no employees organisations organisations 9239 Elementary cleaning occupations n.e.c Security guards and related occupations Traffic wardens School crossing patrol attendants School mid-day assistants Car park attendants Elementary security occupations n.e.c Shelf fillers Elementary sales occupations n.e.c Please note: This derivation table has no empty cells - see paragraph

79 The SOC2000 NS-SEC derivation table: simplified and reduced methods, operational categories Appendix 4

80 Appendix 4 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 4 continued Appendix 4 Standard Occupational Classification 2000 Simplified Employment status Unit Group NS-SEC The SOC2000 NS-SEC derivation table: simplified and 1 Employers reduced 2 Self-employed methods, operational 3 Managers 4 categories Supervisors 5 Other - no employees employees Standard Occupational Classification 2000 Unit Group Simplified NS-SEC Employment status 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 1111 Senior officials in national government Directors and chief executives of major organisations Senior officials in local government Senior officials of special interest organisations Production, works and maintenance managers Managers in construction Managers in mining and energy Financial managers and chartered secretaries Marketing and sales managers Purchasing managers Advertising and public relations managers Personnel, training and industrial relations managers Information and communication technology managers Research and development managers Quality assurance managers Customer care managers Financial institution managers Office managers Transport and distribution managers Storage and warehouse managers Retail and wholesale managers Officers in armed forces Police officers (inspectors and above) Senior officers in fire, ambulance, prison and related services Security managers Hospital and health service managers Pharmacy managers Healthcare practice managers Social services managers Residential and day care managers Farm managers Natural environment and conservation managers Managers in animal husbandry, forestry and fishing n.e.c Hotel and accommodation managers Conference and exhibition managers Restaurant and catering managers Publicans and managers of licensed premises Leisure and sports managers Travel agency managers Property, housing and land managers Garage managers and proprietors Hairdressing and beauty salon managers and proprietors Shopkeepers and wholesale/retail dealers Recycling and refuse disposal managers Managers and proprietors in other services n.e.c Chemists Biological scientists and biochemists Physicists, geologists and meteorologists Civil engineers Mechanical engineers Electrical engineers Electronics engineers Chemical engineers Design and development engineers Production and process engineers Planning and quality control engineers Engineering professionals n.e.c IT strategy and planning professionals

81 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 4 Appendix 4 continued Standard Occupational Classification 2000 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 2132 Software professionals Medical practitioners Psychologists Pharmacists/pharmacologists Ophthalmic opticians Dental practitioners Veterinarians Higher education teaching professionals Further education teaching professionals Education officers, school inspectors Secondary education teaching professionals Primary and nursery education teaching professionals Special needs education teaching professionals Registrars and senior administrators of educational establishments Teaching professionals n.e.c Scientific researchers Social science researchers Researchers n.e.c Solicitors and lawyers, judges and coroners Legal professionals n.e.c Chartered and certified accountants Management accountants Management consultants, actuaries, economists and statisticians Architects Town planners Quantity surveyors Chartered surveyors (not quantity surveyors) Public service administrative professionals Social workers Probation officers Clergy Librarians Archivists and curators Laboratory technicians Electrical/electronics technicians Engineering technicians Building and civil engineering technicians Quality assurance technicians Science and engineering technicians n.e.c Architectural technologists and town planning technicians Draughtspersons Building inspectors IT operations technicians IT user support technicians Nurses Midwives Paramedics Medical radiographers Chiropodists Dispensing opticians Pharmaceutical dispensers Medical and dental technicians Physiotherapists Occupational therapists Speech and language therapists Therapists n.e.c Youth and community workers Housing and welfare officers NCOs and other ranks Police officers (sergeant and below) Fire service officers (leading fire officer and below) Prison service officers (below principal officer) Protective service associate professionals n.e.c Artists Authors, writers Actors, entertainers Dancers and choreographers Musicians

82 Appendix 4 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 4 continued Standard Occupational Classification 2000 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 3416 Arts officers, producers and directors Graphic designers Product, clothing and related designers Journalists, newspaper and periodical editors Broadcasting associate professionals Public relations officers Photographers and audio-visual equipment operators Sports players Sports coaches, instructors and officials Fitness instructors Sports and fitness occupations n.e.c Air traffic controllers Aircraft pilots and flight engineers Ship and hovercraft officers Train drivers Legal associate professionals Estimators, valuers and assessors Brokers Insurance underwriters Finance and investment analysts/advisers Taxation experts Importers, exporters Financial and accounting technicians Business and related associate professionals n.e.c Buyers and purchasing officers Sales representatives Marketing associate professionals Estate agents, auctioneers Conservation and environmental protection officers Countryside and park rangers Public service associate professionals Personnel and industrial relations officers Vocational and industrial trainers and instructors Careers advisers and vocational guidance specialists Inspectors of factories, utilities and trading standards Statutory examiners Occupational hygienists and safety officers (health and safety) Environmental health officers Civil Service executive officers Civil Service administrative officers and assistants Local government clerical officers and assistants Officers of non-governmental organisations Credit controllers Accounts and wages clerks, book-keepers, other financial clerks Counter clerks Filing and other records assistants/clerks Pensions and insurance clerks Stock control clerks Transport and distribution clerks Library assistants/clerks Database assistants/clerks Market research interviewers Telephonists Communication operators General office assistants/clerks Medical secretaries Legal secretaries School secretaries Company secretaries Personal assistants and other secretaries Receptionists Typists Farmers Horticultural trades

83 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 4 Appendix 4 continued Standard Occupational Classification 2000 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 5113 Gardeners and groundsmen/groundswomen Agricultural and fishing trades n.e.c Smiths and forge workers Moulders, core makers, die casters Sheet metal workers Metal plate workers, shipwrights, riveters Welding trades Pipe fitters Metal machining setters and setter-operators Tool makers, tool fitters and markers-out Metal working production and maintenance fitters Precision instrument makers and repairers Motor mechanics, auto engineers Vehicle body builders and repairers Auto electricians Vehicle spray painters Electricians, electrical fitters Telecommunications engineers Lines repairers and cable jointers TV, video and audio engineers Computer engineers, installation and maintenance Electrical/electronics engineers n.e.c Steel erectors Bricklayers, masons Roofers, roof tilers and slaters Plumbers, heating and ventilating engineers Carpenters and joiners Glaziers, window fabricators and fitters Construction trades n.e.c Plasterers Floorers and wall tilers Painters and decorators Weavers and knitters Upholsterers Leather and related trades Tailors and dressmakers Textiles, garments and related trades n.e.c Originators, compositors and print preparers Printers Bookbinders and print finishers Screen printers Butchers, meat cutters Bakers, flour confectioners Fishmongers, poultry dressers Chefs, cooks Glass and ceramics makers, decorators and finishers Furniture makers, other craft woodworkers Pattern makers (moulds) Musical instrument makers and tuners Goldsmiths, silversmiths, precious stone workers Floral arrangers, florists Hand craft occupations n.e.c Nursing auxiliaries and assistants Ambulance staff (excluding paramedics) Dental nurses Houseparents and residential wardens Care assistants and home carers Nursery nurses Childminders and related occupations Playgroup leaders/assistants Educational assistants Veterinary nurses and assistants Animal care occupations n.e.c Sports and leisure assistants Travel agents Travel and tour guides Air travel assistants Rail travel assistants Leisure and travel service occupations n.e.c Hairdressers, barbers

84 Appendix 4 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 4 continued Standard Occupational Classification 2000 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 6222 Beauticians and related occupations Housekeepers and related occupations Caretakers Undertakers and mortuary assistants Pest control officers Sales and retail assistants Retail cashiers and check-out operators Telephone salespersons Collector salespersons and credit agents Debt, rent and other cash collectors Roundsmen/women and van salespersons Market and street traders and assistants Merchandisers and window dressers Sales related occupations n.e.c Call centre agents/operators Customer care occupations Food, drink and tobacco process operatives Glass and ceramics process operatives Textile process operatives Chemical and related process operatives Rubber process operatives Plastics process operatives Metal making and treating process operatives Electroplaters Process operatives n.e.c Paper and wood machine operatives Coal mine operatives Quarry workers and related operatives Energy plant operatives Metal working machine operatives Water and sewerage plant operatives Plant and machine operatives n.e.c Assemblers (electrical products) Assemblers (vehicles and metal goods) Routine inspectors and testers Weighers, graders, sorters Tyre, exhaust and windscreen fitters Clothing cutters Sewing machinists Routine laboratory testers Assemblers and routine operatives n.e.c Scaffolders, stagers, riggers Road construction operatives Rail construction and maintenance operatives Construction operatives n.e.c Heavy goods vehicle drivers Van drivers Bus and coach drivers Taxi, cab drivers and chauffeurs Driving instructors Rail transport operatives Seafarers (merchant navy); barge, lighter and boat operatives Air transport operatives Transport operatives n.e.c Crane drivers Fork-lift truck drivers Agricultural machinery drivers Mobile machine drivers and operatives n.e.c Farm workers Forestry workers Fishing and agriculture related occupations n.e.c Labourers in building and woodworking trades Labourers in other construction trades n.e.c Labourers in foundries Industrial cleaning process occupations Printing machine minders and assistants Packers, bottlers, canners, fillers Labourers in process and plant operations n.e.c Stevedores, dockers and slingers Other goods handling and storage occupations n.e.c

85 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 4 Appendix 4 continued Standard Occupational Classification 2000 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 9211 Postal workers, mail sorters, messengers, couriers Elementary office occupations n.e.c Hospital porters Hotel porters Kitchen and catering assistants Waiters, waitresses Bar staff Leisure and theme park attendants Elementary personal services occupations n.e.c Window cleaners Road sweepers Cleaners, domestics Launderers, dry cleaners, pressers Refuse and salvage occupations Elementary cleaning occupations n.e.c Security guards and related occupations Traffic wardens School crossing patrol attendants School mid-day assistants Car park attendants Elementary security occupations n.e.c Shelf fillers Elementary sales occupations n.e.c Please note: This derivation table has no empty cells - see Para

86 Appendix 4 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 4 continued Standard Occupational Classification 2000 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 78

87 The SOC90 NS-SEC derivation table: simplified and full methods, operational categories Appendix 5

88 Appendix 5 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 5 continued Appendix 5 Standard Occupational Classification 1990 Simplified Employment status/size of organisation Unit Group NS-SEC The SOC90 NS-SEC derivation table: simplified 1 Employers and 2 Employers full method, 3 Self-employed operational 4 Managers categories 5 Managers 6 Supervisors 7 Other - large - small - no employees - large - small employees organisations organisations organisations organisations Standard Occupational Classification 1990 Unit Group Simplified Employment status/size of organisation NS-SEC 1 Employers 2 Employers 3 Self-employed 4 Managers 5 Managers 6 Supervisors 7 Other - large - small - no employees - large - small employees organisations organisations organisations organisations 100 General administrators; national government (Assistant Secretary/ Grade 5 and above) General managers; large companies and organisations Local government officers (administrative and executive functions) General administrators; national government (HEO to Senior Principal/Grade 6) Production, works and maintenance managers Managers in building and contracting Clerks of works Managers in mining and energy industries Treasurers and company financial managers Marketing and sales managers Purchasing managers Advertising and public relations managers Personnel, training and industrial relations managers Organisation and methods and work study managers Computer systems and data processing managers Company secretaries Credit controllers Bank, Building Society and Post Office managers (except selfemployed) Civil Service executive officers Other financial institution and office managers n.e.c Transport managers Stores controllers Managers in warehousing and other materials handling Officers in UK armed forces Officers in foreign and Commonwealth armed forces Police officers (inspector and above) Fire service officers (station officer and above) Prison officers (principal officer and above) Customs and excise, immigration service officers (customs: chief preventive officer and above; excise: surveyor and above) Farm owners and managers, horticulturists Other managers in farming, horticulture, forestry and fishing n.e.c Property and estate managers Garage managers and proprietors Hairdressers and barbers managers and proprietors Hotel and accommodation managers Restaurant and catering managers Publicans, innkeepers and club stewards

89 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 5 Appendix 5 continued Standard Occupational Classification 1990 Simplified Employment status/size of organisation Unit Group NS-SEC 1 Employers 2 Employers 3 Self-employed 4 Managers 5 Managers 6 Supervisors 7 Other - large - small - no employees - large - small employees organisations organisations organisations organisations 176 Entertainment and sports managers Travel agency managers Managers and proprietors of butchers and fishmongers Managers and proprietors in service industries n.e.c Officials of trade associations, trade unions, professional bodies and charities Registrars and administrators of educational establishments Other managers and administrators n.e.c Chemists Biological scientists and biochemists Physicists, geologists and meteorologists Other natural scientists n.e.c Civil, structural, municipal, mining and quarrying engineers Mechanical engineers Electrical engineers Electronic engineers Software engineers Chemical engineers Design and development engineers Process and production engineers Planning and quality control engineers Other engineers and technologists n.e.c Medical practitioners Pharmacists/pharmacologists Ophthalmic opticians Dental practitioners Veterinarians University and polytechnic teaching professionals Higher and further education teaching professionals Education officers, school inspectors Secondary (and middle school deemed secondary) education teaching professionals Primary (and middle school deemed primary) and nursery education teaching professionals Special education teaching professionals Other teaching professionals n.e.c Judges and officers of the Court Barristers and advocates Solicitors Chartered and certified accountants Management accountants Actuaries, economists and statisticians Management consultants, business analysts Architects Town planners Building, land, mining and general practice surveyors Librarians Archivists and curators Psychologists Other social and behavioural scientists Clergy Social workers, probation officers Laboratory technicians Engineering technicians Electrical/electronic technicians Architectural and town planning technicians

90 Appendix 5 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 5 continued Standard Occupational Classification 1990 Simplified Employment status/size of organisation Unit Group NS-SEC 1 Employers 2 Employers 3 Self-employed 4 Managers 5 Managers 6 Supervisors 7 Other - large - small - no employees - large - small employees organisations organisations organisations organisations 304 Building and civil engineering technicians Other scientific technicians n.e.c Draughtspersons Building inspectors Quantity surveyors Marine, insurance and other surveyors Computer analyst/programmers Air traffic planners and controllers Aircraft flight deck officers Ship and hovercraft officers Nurses Midwives Medical radiographers Physiotherapists Chiropodists Dispensing opticians Medical technicians, dental auxiliaries Occupational and speech therapists, psychotherapists, therapists n.e.c Environmental health officers Other health associate professionals n.e.c Legal service and related occupations Estimators, valuers Underwriters, claims assessors, brokers, investment analysts Taxation experts Personnel and industrial relations officers Organisation and methods and work study officers Matrons, houseparents Welfare, community and youth workers Authors, writers, journalists Artists, commercial artists, graphic designers Industrial designers Clothing designers Actors, entertainers, stage managers, producers and directors Musicians Photographers, camera, sound and video equipment operators Professional athletes, sports officials Information officers Vocational and industrial trainers Careers advisers and vocational guidance specialists Driving instructors (excluding HGV) Inspectors of factories, utilities and trading standards Other statutory and similar inspectors n.e.c Occupational hygienists and safety officers (health and safety) Other associate professional and technical occupations n.e.c Civil Service administrative officers and assistants Local government clerical officers and assistants Accounts and wages clerks, bookkeepers, other financial clerks Counter clerks and cashiers Debt, rent and other cash collectors Filing, computer and other records clerks (including legal conveyancing) Library assistants/clerks Clerks (n.o.s.) Stores, despatch and production control clerks

91 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 5 Appendix 5 continued Standard Occupational Classification 1990 Simplified Employment status/size of organisation Unit Group NS-SEC 1 Employers 2 Employers 3 Self-employed 4 Managers 5 Managers 6 Supervisors 7 Other - large - small - no employees - large - small employees organisations organisations organisations organisations 441 Storekeepers and warehousemen/ women Medical secretaries Legal secretaries Typists and word processor operators Other secretaries, personal assistants, typists, word processor operators n.e.c Receptionists Receptionist/telephonists Telephone operators Radio and telegraph operators, other office communication system operators Computer operators, data processing operators, other office machine operators Tracers, drawing office assistants Bricklayers, masons Roofers, slaters, tilers, sheeters, cladders Plasterers Glaziers Builders, building contractors Scaffolders, stagers, steeplejacks, riggers Floorers, floor coverers, carpet fitters and planners, floor and wall tilers Painters and decorators Other construction trades n.e.c Centre, capstan, turret and other lathe setters and setter-operators Boring and drilling machine setters and setter-operators Grinding machine setters and setteroperators Milling machine setters and setteroperators Press setters and setter-operators Tool makers, tool fitters and markers-out Metal working production and maintenance fitters Precision instrument makers and repairers Goldsmiths, silversmiths, precious stone workers Other machine tool setters and setteroperators n.e.c. (including CNC setter-operators) Production fitters (electrical/ electronic) Electricians, electrical maintenance fitters Electrical engineers (not professional) Telephone fitters Cable jointers, lines repairers Radio, TV and video engineers Computer engineers, installation and maintenance Other electrical/electronic trades n.e.c Smiths and forge workers Moulders, core makers, die casters Plumbers, heating and ventilating engineers and related trades Sheet metal workers Metal plate workers, shipwrights, riveters Steel erectors Barbenders, steel fixers Welding trades Motor mechanics, auto engineers (including road patrol engineers) Coach and vehicle body builders

92 Appendix 5 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 5 continued Standard Occupational Classification 1990 Simplified Employment status/size of organisation Unit Group NS-SEC 1 Employers 2 Employers 3 Self-employed 4 Managers 5 Managers 6 Supervisors 7 Other - large - small - no employees - large - small employees organisations organisations organisations organisations 542 Vehicle body repairers, panel beaters Auto electricians Tyre and exhaust fitters Weavers Knitters Warp preparers, bleachers, dyers and finishers Sewing machinists, menders, darners and embroiderers Coach trimmers, upholsterers and mattress makers Shoe repairers, leather cutters and sewers, footwear lasters, makers and finishers, other leather making and repairing Tailors and dressmakers Clothing cutters, milliners, furriers Other textiles, garments and related trades n.e.c Originators, compositors and print preparers Printers Bookbinders and print finishers Screen printers Other printing and related trades n.e.c Carpenters and joiners Cabinet makers Case and box makers Pattern makers (moulds) Other woodworking trades n.e.c Bakers, flour confectioners Butchers, meat cutters Fishmongers, poultry dressers Glass product and ceramics makers Glass product and ceramics finishers and decorators Dental technicians Musical instrument makers, piano tuners Gardeners, groundsmen/ groundswomen Horticultural trades Coach painters, other spray painters Face trained coalmining workers, shotfirers and deputies Office machinery mechanics Other craft and related occupations n.e.c NCOs and other ranks, UK armed forces NCOs and other ranks, foreign and Commonwealth armed forces Police officers (sergeant and below) Fire service officers (leading fire officer and below) Prison service officers (below principal officer) Customs and excise officers, immigration officers (customs: below chief preventive officer; excise: below surveyor) Traffic wardens Security guards and related occupations Other security and protective service occupations n.e.c Chefs, cooks Waiters, waitresses Bar staff Travel and flight attendants Railway station staff Assistant nurses, nursing auxiliaries Hospital ward assistants Ambulance staff

93 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 5 Appendix 5 continued Standard Occupational Classification 1990 Simplified Employment status/size of organisation Unit Group NS-SEC 1 Employers 2 Employers 3 Self-employed 4 Managers 5 Managers 6 Supervisors 7 Other - large - small - no employees - large - small employees organisations organisations organisations organisations 643 Dental nurses Care assistants and attendants Nursery nurses Playgroup leaders Educational assistants Other childcare and related occupations n.e.c Hairdressers, barbers Beauticians and related occupations Domestic housekeepers and related occupations Housekeepers (non-domestic) Caretakers Launderers, dry cleaners, pressers Undertakers Bookmakers Other personal and protective service occupations n.e.c Buyers (retail trade) Buyers and purchasing officers (not retail) Importers and exporters Air, commodity and ship brokers Technical and wholesale sales representatives Other sales representatives n.e.c Sales assistants Retail cash desk and check-out operators Petrol pump forecourt attendants Collector salespersons and credit agents Roundsmen/women and van salespersons Market and street traders and assistants Scrap dealers, scrap metal merchants Merchandisers Window dressers, floral arrangers Telephone salespersons Bakery and confectionery process operatives Brewery and vinery process operatives Tobacco process operatives Other food, drink and tobacco process operatives n.e.c Tannery production operatives Preparatory fibre processors Spinners, doublers, twisters Winders, reelers Other textiles processing operatives Chemical, gas and petroleum process plant operatives Paper, wood and related process plant operatives Cutting and slitting machine operatives (paper products etc) Glass and ceramics furnace operatives, kilnsetters Rubber process operatives, moulding machine operatives, tyre builders Plastics process operatives, moulders and extruders Synthetic fibre makers Other chemicals, paper, plastics and related process operatives n.e.c Furnace operatives (metal) Metal drawers Rollers Annealers, hardeners, temperers (metal) Electroplaters, galvanisers, colour coaters

94 Appendix 5 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 5 continued Standard Occupational Classification 1990 Simplified Employment status/size of organisation Unit Group NS-SEC 1 Employers 2 Employers 3 Self-employed 4 Managers 5 Managers 6 Supervisors 7 Other - large - small - no employees - large - small employees organisations organisations organisations organisations 839 Other metal making and treating process operatives n.e.c Machine tool operatives (including CNC machine tool operatives) Press stamping and automatic machine operatives Metal polishers Metal dressing operatives Shot blasters Assemblers/lineworkers (electrical/ electronic goods) Assemblers/lineworkers (vehicles and other metal goods) Other assemblers/lineworkers n.e.c Inspectors, viewers and testers (metal and electrical goods) Inspectors, viewers, testers and examiners (other manufactured goods) Packers, bottlers, canners, fillers Weighers, graders, sorters Routine laboratory testers Other routine process operatives n.e.c Bus inspectors Road transport depot inspectors and related occupations Drivers of road goods vehicles Bus and coach drivers Taxi, cab drivers and chauffeurs Bus conductors Seafarers (merchant navy); barge, lighter and boat operatives Rail transport inspectors, supervisors and guards Rail engine drivers and assistants Rail signal operatives and crossing keepers Shunters and points operatives Mechanical plant drivers and operatives (earth moving and civil engineering) Crane drivers Fork lift and mechanical truck drivers Other transport and machinery operatives n.e.c Washers, screeners and crushers in mines and quarries Printing machine minders and assistants Water and sewerage plant attendants Electrical, energy, boiler and related plant operatives and attendants Oilers, greasers, lubricators Mains and service pipe layers, pipe jointers Construction and related operatives Woodworking machine operatives Mine (excluding coal) and quarry workers Other plant and machine operatives n.e.c Farm workers Agricultural machinery drivers and operatives All other occupations in farming and related Fishing and related workers Forestry workers Coal mine labourers Labourers in foundries Labourers in engineering and allied trades Mates to metal/electrical and related fitters

95 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 5 Appendix 5 continued Standard Occupational Classification 1990 Simplified Employment status/size of organisation Unit Group NS-SEC 1 Employers 2 Employers 3 Self-employed 4 Managers 5 Managers 6 Supervisors 7 Other - large - small - no employees - large - small employees organisations organisations organisations organisations 919 Other labourers in making and processing industries n.e.c Mates to woodworking trades workers Mates to building trades workers Rail construction and maintenance workers Road construction and maintenance workers Paviors, kerb layers Other building and civil engineering labourers n.e.c Stevedores, dockers Goods porters Slingers Refuse and salvage collectors Drivers mates Postal workers, mail sorters Messengers, couriers Hospital porters Hotel porters Kitchen porters, hands Counterhands, catering assistants Shelf fillers Lift and car park attendants Window cleaners Road sweepers Cleaners, domestics Other occupations in sales and services n.e.c All other labourers and related workers All others in miscellaneous occupations n.e.c Please note: This derivation table has no empty cells - see Para

96 Appendix 5 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 5 continued Standard Occupational Classification 1990 Simplified Employment status/size of organisation Unit Group NS-SEC 1 Employers 2 Employers 3 Self-employed 4 Managers 5 Managers 6 Supervisors 7 Other - large - small - no employees - large - small employees organisations organisations organisations organisations 88

97 The SOC90 NS-SEC derivation table: simplified and reduced methods, operational categories Appendix 6

98 Appendix 6 The SOC90 NS-SEC derivation table: simplified and reduced methods, operational categories Standard Occupational Classification 1990 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 100 General administrators; national government (Assistant Secretary/Grade 5 and above) General managers; large companies and organisations Local government officers (administrative and executive functions) General administrators; national government (HEO to Senior Principal/Grade 6) Production, works and maintenance managers Managers in building and contracting Clerks of works Managers in mining and energy industries Treasurers and company financial managers Marketing and sales managers Purchasing managers Advertising and public relations managers Personnel, training and industrial relations managers Organisation and methods and work study managers Computer systems and data processing managers Company secretaries Credit controllers Bank, Building Society and Post Office managers (except self-employed) Civil Service executive officers Other financial institution and office managers n.e.c Transport managers Stores controllers Managers in warehousing and other materials handling Officers in UK armed forces Officers in foreign and Commonwealth armed forces Police officers (inspector and above) Fire service officers (station officer and above) Prison officers (principal officer and above) Customs and excise, immigration service officers (customs: chief preventive officer and above; excise: surveyor and above) Farm owners and managers, horticulturists Other managers in farming, horticulture, forestry and fishing n.e.c Property and estate managers Garage managers and proprietors Hairdressers and barbers managers and proprietors Hotel and accommodation managers Restaurant and catering managers Publicans, innkeepers and club stewards Entertainment and sports managers Travel agency managers Managers and proprietors of butchers and fishmongers Managers and proprietors in service industries n.e.c Officials of trade associations, trade unions, professional bodies and charities Registrars and administrators of educational establishments Other managers and administrators n.e.c Chemists Biological scientists and biochemists Physicists, geologists and meteorologists Other natural scientists n.e.c

99 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 6 Appendix 6 continued Standard Occupational Classification 1990 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 210 Civil, structural, municipal, mining and quarrying engineers Mechanical engineers Electrical engineers Electronic engineers Software engineers Chemical engineers Design and development engineers Process and production engineers Planning and quality control engineers Other engineers and technologists n.e.c Medical practitioners Pharmacists/pharmacologists Ophthalmic opticians Dental practitioners Veterinarians University and polytechnic teaching professionals Higher and further education teaching professionals Education officers, school inspectors Secondary (and middle school deemed secondary) education teaching professionals Primary (and middle school deemed primary) and nursery education teaching professionals Special education teaching professionals Other teaching professionals n.e.c Judges and officers of the Court Barristers and advocates Solicitors Chartered and certified accountants Management accountants Actuaries, economists and statisticians Management consultants, business analysts Architects Town planners Building, land, mining and general practice surveyors Librarians Archivists and curators Psychologists Other social and behavioural scientists Clergy Social workers, probation officers Laboratory technicians Engineering technicians Electrical/electronic technicians Architectural and town planning technicians Building and civil engineering technicians Other scientific technicians n.e.c Draughtspersons Building inspectors Quantity surveyors Marine, insurance and other surveyors Computer analyst/programmers Air traffic planners and controllers Aircraft flight deck officers Ship and hovercraft officers Nurses Midwives Medical radiographers Physiotherapists Chiropodists Dispensing opticians Medical technicians, dental auxiliaries Occupational and speech therapists, psychotherapists, therapists n.e.c Environmental health officers Other health associate professionals n.e.c Legal service and related occupations Estimators, valuers Underwriters, claims assessors, brokers, investment analysts

100 Appendix 6 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 6 continued Standard Occupational Classification 1990 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 362 Taxation experts Personnel and industrial relations officers Organisation and methods and work study officers Matrons, houseparents Welfare, community and youth workers Authors, writers, journalists Artists, commercial artists, graphic designers Industrial designers Clothing designers Actors, entertainers, stage managers, producers and directors Musicians Photographers, camera, sound and video equipment operators Professional athletes, sports officials Information officers Vocational and industrial trainers Careers advisers and vocational guidance specialists Driving instructors (excluding HGV) Inspectors of factories, utilities and trading standards Other statutory and similar inspectors n.e.c Occupational hygienists and safety officers (health and safety) Other associate professional and technical occupations n.e.c Civil Service administrative officers and assistants Local government clerical officers and assistants Accounts and wages clerks, book-keepers, other financial clerks Counter clerks and cashiers Debt, rent and other cash collectors Filing, computer and other records clerks (including legal conveyancing) Library assistants/clerks Clerks (n.o.s.) Stores, despatch and production control clerks Storekeepers and warehousemen/women Medical secretaries Legal secretaries Typists and word processor operators Other secretaries, personal assistants, typists, word processor operators n.e.c Receptionists Receptionist/telephonists Telephone operators Radio and telegraph operators, other office communication system operators Computer operators, data processing operators, other office machine operators Tracers, drawing office assistants Bricklayers, masons Roofers, slaters, tilers, sheeters, cladders Plasterers Glaziers Builders, building contractors Scaffolders, stagers, steeplejacks, riggers Floorers, floor coverers, carpet fitters and planners, floor and wall tilers Painters and decorators Other construction trades n.e.c Centre, capstan, turret and other lathe setters and setter-operators Boring and drilling machine setters and setter-operators Grinding machine setters and setter-operators Milling machine setters and setter-operators Press setters and setter-operators Tool makers, tool fitters and markers-out Metal working production and maintenance fitters

101 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 6 Appendix 6 continued Standard Occupational Classification 1990 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 517 Precision instrument makers and repairers Goldsmiths, silversmiths, precious stone workers Other machine tool setters and setter-operators n.e.c. (including CNC setter-operators) Production fitters (electrical/electronic) Electricians, electrical maintenance fitters Electrical engineers (not professional) Telephone fitters Cable jointers, lines repairers Radio, TV and video engineers Computer engineers, installation and maintenance Other electrical/electronic trades n.e.c Smiths and forge workers Moulders, core makers, die casters Plumbers, heating and ventilating engineers and related trades Sheet metal workers Metal plate workers, shipwrights, riveters Steel erectors Barbenders, steel fixers Welding trades Motor mechanics, auto engineers (including road patrol engineers) Coach and vehicle body builders Vehicle body repairers, panel beaters Auto electricians Tyre and exhaust fitters Weavers Knitters Warp preparers, bleachers, dyers and finishers Sewing machinists, menders, darners and embroiderers Coach trimmers, upholsterers and mattress makers Shoe repairers, leather cutters and sewers, footwear lasters, makers and finishers, other leather making and repairing Tailors and dressmakers Clothing cutters, milliners, furriers Other textiles, garments and related trades n.e.c Originators, compositors and print preparers Printers Bookbinders and print finishers Screen printers Other printing and related trades n.e.c Carpenters and joiners Cabinet makers Case and box makers Pattern makers (moulds) Other woodworking trades n.e.c Bakers, flour confectioners Butchers, meat cutters Fishmongers, poultry dressers Glass product and ceramics makers Glass product and ceramics finishers and decorators Dental technicians Musical instrument makers, piano tuners Gardeners, groundsmen/groundswomen Horticultural trades Coach painters, other spray painters Face trained coalmining workers, shotfirers and deputies Office machinery mechanics Other craft and related occupations n.e.c NCOs and other ranks, UK armed forces NCOs and other ranks, foreign and Commonwealth armed forces Police officers (sergeant and below) Fire service officers (leading fire officer and below) Prison service officers (below principal officer)

102 Appendix 6 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 6 continued Standard Occupational Classification 1990 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 613 Customs and excise officers, immigration officers (customs: below chief preventive officer; excise: below surveyor) Traffic wardens Security guards and related occupations Other security and protective service occupations n.e.c Chefs, cooks Waiters, waitresses Bar staff Travel and flight attendants Railway station staff Assistant nurses, nursing auxiliaries Hospital ward assistants Ambulance staff Dental nurses Care assistants and attendants Nursery nurses Playgroup leaders Educational assistants Other childcare and related occupations n.e.c Hairdressers, barbers Beauticians and related occupations Domestic housekeepers and related occupations Housekeepers (non-domestic) Caretakers Launderers, dry cleaners, pressers Undertakers Bookmakers Other personal and protective service occupations n.e.c Buyers (retail trade) Buyers and purchasing officers (not retail) Importers and exporters Air, commodity and ship brokers Technical and wholesale sales representatives Other sales representatives n.e.c Sales assistants Retail cash desk and check-out operators Petrol pump forecourt attendants Collector salespersons and credit agents Roundsmen/women and van salespersons Market and street traders and assistants Scrap dealers, scrap metal merchants Merchandisers Window dressers, floral arrangers Telephone salespersons Bakery and confectionery process operatives Brewery and vinery process operatives Tobacco process operatives Other food, drink and tobacco process operatives n.e.c Tannery production operatives Preparatory fibre processors Spinners, doublers, twisters Winders, reelers Other textiles processing operatives Chemical, gas and petroleum process plant operatives Paper, wood and related process plant operatives Cutting and slitting machine operatives (paper products etc) Glass and ceramics furnace operatives, kilnsetters Rubber process operatives, moulding machine operatives, tyre builders Plastics process operatives, moulders and extruders Synthetic fibre makers Other chemicals, paper, plastics and related process operatives n.e.c Furnace operatives (metal) Metal drawers Rollers

103 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 6 Appendix 6 continued Standard Occupational Classification 1990 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 833 Annealers, hardeners, temperers (metal) Electroplaters, galvanisers, colour coaters Other metal making and treating process operatives n.e.c Machine tool operatives (including CNC machine tool operatives) Press stamping and automatic machine operatives Metal polishers Metal dressing operatives Shot blasters Assemblers/lineworkers (electrical/electronic goods) Assemblers/lineworkers (vehicles and other metal goods) Other assemblers/lineworkers n.e.c Inspectors, viewers and testers (metal and electrical goods) Inspectors, viewers, testers and examiners (other manufactured goods) Packers, bottlers, canners, fillers Weighers, graders, sorters Routine laboratory testers Other routine process operatives n.e.c Bus inspectors Road transport depot inspectors and related occupations Drivers of road goods vehicles Bus and coach drivers Taxi, cab drivers and chauffeurs Bus conductors Seafarers (merchant navy); barge, lighter and boat operatives Rail transport inspectors, supervisors and guards Rail engine drivers and assistants Rail signal operatives and crossing keepers Shunters and points operatives Mechanical plant drivers and operatives (earth moving and civil engineering) Crane drivers Fork lift and mechanical truck drivers Other transport and machinery operatives n.e.c Washers, screeners and crushers in mines and quarries Printing machine minders and assistants Water and sewerage plant attendants Electrical, energy, boiler and related plant operatives and attendants Oilers, greasers, lubricators Mains and service pipe layers, pipe jointers Construction and related operatives Woodworking machine operatives Mine (excluding coal) and quarry workers Other plant and machine operatives n.e.c Farm workers Agricultural machinery drivers and operatives All other occupations in farming and related Fishing and related workers Forestry workers Coal mine labourers Labourers in foundries Labourers in engineering and allied trades Mates to metal/electrical and related fitters Other labourers in making and processing industries n.e.c Mates to woodworking trades workers Mates to building trades workers Rail construction and maintenance workers Road construction and maintenance workers Paviors, kerb layers Other building and civil engineering labourers n.e.c Stevedores, dockers Goods porters

104 Appendix 6 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 6 continued Standard Occupational Classification 1990 Simplified Employment status Unit Group NS-SEC 1 Employers 2 Self-employed 3 Managers 4 Supervisors 5 Other - no employees employees 932 Slingers Refuse and salvage collectors Drivers mates Postal workers, mail sorters Messengers, couriers Hospital porters Hotel porters Kitchen porters, hands Counterhands, catering assistants Shelf fillers Lift and car park attendants Window cleaners Road sweepers Cleaners, domestics Other occupations in sales and services n.e.c All other labourers and related workers All others in miscellaneous occupations n.e.c Please note: This derivation table has no empty cells - see paragraph

105 Employment relations questions on the LFS Appendix 7

106 Appendix 7 The National Statistics Socio-economic Classification: Origins, Development and Use Following analyses of Omnibus data, it was agreed that the following questions be added to the December 1996 February 1997 LFS quarter: (1) Which of the following best describes how you are paid in your present job? Monthly salary plus performance Monthly salary only Weekly wage Hourly paid Piecework Other (2) Are you on a recognised pay scale with increments, either automatic or performance related? Yes No Don t know (3) If you decided to leave your job, how much notice are you officially required to give? (6) Does your job require you to design and plan important aspects of your own work, or is your work largely specified for you? I am required to design/plan my work Work is largely specified by others Other (7) How much influence do you personally have in deciding what tasks you are to do? A great deal A fair amount Not much Or none at all (8) Does your sort of work have a recognised career or promotion ladder, even if it means changing employers to go up it? Yes No Don t know Less than one week One week but less than one month One month but less than three months Three months or more Don t know (4) In your sort of work, are there opportunities for promotion, either in your current organisation or by changing employers? Yes No Don t know (5) Who decides what time you start and leave work? Flexitime system Employer decides I decide within certain limits Negotiated with employer 98

107 The concept of validity in relation to the Review Karen O Reilly Appendix 8

108 Appendix 8 The National Statistics Socio-economic Classification: Origins, Development and Use Introduction 1. We have seen in Chapter 4 of this report that the Review Committee decided to adopt the Goldthorpe class schema as the basis for the NS-SEC. However, we have also seen that the Goldthorpe schema is a concept and not an operationalisation (Goldthorpe 1997). Goldthorpe s schema is clearly defined in order that it may be operationalised using a variety of different datasets, and for different countries. The effectiveness with which this can be achieved depends on the information available relevant to its construction, and on the suitability of the occupational classification on which it is based for this kind of conceptualisation. Hence, each separate operationalisation of the schema should therefore be validated as a measure of the concept (c.f. Nunnally and Bernstein 1994). 2. We saw earlier that the Review Committee s decision to adopt but adapt the Goldthorpe schema, while retaining maximum continuity with Social Class based on Occupation (SC) and Socio-economic Group (SEG), therefore involved validating the NS-SEC as an instrument du travail (c.f. Rose and O Reilly 1997). In the main body of the report we have discussed the various forms of validation we have employed in the Review. Since the issue of validation will arise for any subsequent revision of the NS-SEC, this appendix provides an overview of various types of validity: face validity, content validity, criterion validity and construct validity. Validation of a measure 3. The problem of validation can be approached in two main ways: the validation of a study, and the validation of a measure. The validation aspect of the Review was concerned with the latter. Here validity testing involves ensuring that in the construction of the NS-SEC we have measured what we intended to measure. This in turn involves enquiring into the nature and meaning of the new classification as a variable for use in various datasets (c.f. Kerlinger 1986:416). However, validation of a measure can itself be approached in a variety of ways. A great deal of confusion surrounds the concept of validity: much of the discussion and examples come from within psychology, where the construction of tests, scales or instruments is much more common than within sociology and where such scales are often deemed to measure the quantity of some clearly-defined attribute held by one person as opposed to another; and, furthermore, different terms are used by different authors in various different ways (Bailey 1988). Common examples of measurements validated are Intelligence Quotient (IQ) tests, mathematics tests, measurements of psychological phenomena such as self-esteem (psychometric tests) and so on. It is difficult to use the same notions when thinking about a sociological concept such as alienation (an example used by Zeller and Carmines 1980) or class, as in our case. 4. In order to validate a measure of a concept, as was required for the NS-SEC, it is possible to perform four main types of validation: face, content, criterion and construct. These four types of validation are difficult to understand conceptually because, as discussed above, they have been designed for the validation of psychology tests, which are often much less abstract than sociological ones, or at least have some more clearly-defined use or purpose (for example, assessment or prediction). The four types are more or less useful for our purposes as the following discussion explains. Face validity 5. Face validity involves a simple assessment of whether, on the face of it, a measure appears to measure what it is supposed to (Nunnally 1959). For the NS-SEC this has involved ensuring that the categories constructed make some meaningful sense in terms of the underlying concept of class (see Chapter 5). At a very basic level, we would expect the NS- SEC to distinguish employers, the self-employed and employees, so that no single socio-economic classification (SEC) category combined these basic groups. This practice is continuous with SEG, which had categories of employers in large and small establishments, SEGs 1.1 and 2.1; a category of self-employed, SEG 12; and several categories of employees. 6. We would also expect to find that the NS-SEC further distinguishes employees in terms of the service relationship and labour contract. This is not so easy since the language of contracts is not common parlance and the common-sense view of what constitutes occupational groupings is not likely to be expressed in these terms. How would we know, on the face of it, whether an employee category is different from another category in terms of the employment conditions associated with different forms of regulation? One way is to look for categories that Goldthorpe has said typify these different forms. The NS-SEC could only be said to have face validity if there were categories containing senior managerial, professional and administrative positions and distinct categories for employees, with no supervisory role, working in routine occupations. 7. Thus, if the NS-SEC has categories of employers, selfemployed and employees; and if the employees are further sub-divided into those regulated by a service relationship, a labour contract and intermediate forms of regulation; and if the two basic forms of regulation are shown through the 100

109 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 8 categories to exist in varying degrees of actualisation, then the NS-SEC can be said to exhibit face validity. However, face validity is difficult either to contest or prove. It is a first basic step in the validation procedure, providing weak evidence of validity, and little more than that. One means of ensuring that face validation is rather more than merely subjective judgement would be to send the measure to a panel of experts (on employment contracts, for example) and to ask them for their informed opinions on its validity. In fact we did do this for the NS-SEC. While this may make the judgement more convincing to others, it is still a somewhat unsatisfactory procedure. Content validity 8. Content validity is tied to the nominal definition of the concept being measured. The concept must be clearly defined and validation must involve testing that the different aspects of the concept are all measured. Content validity is thus an assessment of the representativeness or sampling adequacy of the content (Kerlinger 1986). To give an example, if some students have attended a mathematics course and at the end of it the tutor wants to know that the students have understood all that has been taught, a test or assessment could be devised. The test would necessarily need to cover the content of the course, so the tutor might ask questions which tested the students ability in multiplication and division, algebra, fractions and decimals, and so on. The tutor would need to think carefully about the content of the course and ensure that all of it was covered in the test. Of course, this does not mean that everything that was taught must be tested; this would take far too long. It is therefore a sample of the content that is tested or measured (Nunnally 1959). Content validation requires that all the separate and relevant elements that make up the content are covered by the measure (Moser and Kalton 1971). 9. Content validation, therefore, first demands that we decide what our concept contains, that is, its constituent parts. This might be quite straightforward for assessment or achievement measures, where content validity is typically used (c.f. Nunnally 1959; Anastasi 1990) but for other constructs such as self-esteem or, as in our case, class, it will not be so easy to determine the criteria that constitute the domain or universe of content. Could it be argued, for example, that class contains employment relationships and associated conditions of employment? Certainly, class as operationalised using occupation and employment status information does not overtly contain these elements, though it is hoped that it serves to indicate them. Perhaps one could argue that the concept of class being applied in the NS-SEC consists of employment relationships but, if this is the case, then content validity tests would look much the same as face validity tests, discussed above. 10. Content validity is widely used in psychology and education but less in political science and sociology (Zeller and Carmines 1980). It is difficult or impossible to gain consensus as to the universe of content (Cronbach and Meehl 1955) and depends on subjective judgements with regard to how adequately the content has been defined and sampled (Nunnally 1959). However, I will return to the issue of content validity when I discuss criterion-related validity, below. Criterion validity 11. Criterion-related validity involves determining criterions (sic) which relate to the concept being measured, but which have not been measured directly, and testing whether these correlate with the new measure. The distinction between construct and criterion-related validity is not immediately apparent, and in fact William Trochim s work (1998) uses construct validity as a general term covering criterion, content and face validity, as well as what this appendix refers to separately as construct validity. The difficulty is partly exacerbated by the fact that Trochim and others use the term construct for the idea or theoretical landscape of the measure, test, assessment or variable being subjected to validation. Therefore all validation of a measure can be seen as construct validation, that is, validation of how well the construct has been measured (c.f. Trochim 1998; Henerson et al 1987). However, I hope to make it clear that criterion-related and construct (for want of a better word) validation are conceptually very different. 12. According to Zeller and Carmines (1980:79), criterionrelated validity concerns the correlation between a measure and some criterion variable on (sic) interest. As such, it is usually associated with practical problems and outcomes. Common examples are: a written driving test: one would expect pass rates to correlate with ability to drive (op.cit.); a mechanical aptitude test and subsequent performance in a related job (Anastasi 1990); a measure of conservatism and its ability to predict membership of the Conservative party (de Vaus 1996). The idea is that the measure can be used to predict behaviour or outcome in a related variable or variables which may either not be so readily available for measure, or may be less comprehensive. As used in psychological testing, criterion-related validity is less concerned with what the measure (or even the construct) is actually measuring than with its ability to predict outcomes. It is important to note that the prediction may not actually be of something expected to happen in the future but may be concurrent (Kerlinger 1986). To clarify this, some authors distinguish between concurrent 101

110 Appendix 8 The National Statistics Socio-economic Classification: Origins, Development and Use and predictive validity tests, which test the measure s ability to predict or correlate with other, independent and external, variables. 13. It may not be immediately apparent how criterion-related validity could be relevant to the NS-SEC, but Evans (1992 and 1996), Evans and Mills (1996, 1997, 1998a and b) and Birkelund et al (1996) have done much to clarify this in their work on the validation of the current instantiation of the Goldthorpe schema. Like the NS-SEC, the Goldthorpe schema is operationalised using information on occupation and employment status. It therefore acts as a proxy for the underlying concept of social class, without directly indexing the characteristics identified as part of the concept. That is to say, while the distinction between employers, employees and the self-employed can be directly measured using information on employment status, the distinctions between employees based on the service relationship and labour contract cannot be so measured because occupations are not overtly classified in this way. Occupation and employment status are therefore used to indicate differences based on forms of remuneration, opportunities for promotion, and so on, as discussed elsewhere in this report. Criterion-related validity, in this case, involves measuring directly those characteristics we are trying to index through indirect means and then testing how satisfactory the construct (the NS-SEC or the Goldthorpe schema) is as a measure of these characteristics. In other words, the new class schema is a proxy for the concept of social class and as such it should predict a certain set of employment conditions, those associated with forms of remuneration, promotion prospects and autonomy in particular, which should vary according to whether a labour contract or a service relationship prevails (c.f. Evans 1992, Goldthorpe 1997; Evans and Mills 1998a; Mills and Evans 2003; Coxan and Fisher 2003). In criterion-related validity it is this set of conditions with which we should be ultimately concerned. 14. In order to validate the NS-SEC we therefore examined the relationship between the measure and sets of criterionrelated variables, using a variety of different datasets and various statistical techniques. The number of potential criterion-related variables is almost endless and the specific set used at any given time should be examined for content validity (see discussion above), that is for their adequacy in sampling the characteristics associated with Goldthorpe s concept of class. We also ensured that the effectiveness of the operationalisation did not vary systematically when controlling for sex and for part-time work. If there had been serious variation, then the new measure could not have been considered valid for these groups. 15. There are criteria other than those associated with the service relationship/labour contract distinction with which the schema could be validated, but Goldthorpe does not spell these out. When discussing where to locate large proprietors, for example, Erikson and Goldthorpe (1992) suggest that they share an affinity with salaried managers since they are involved as much in managerial as entrepreneurial activities. An implicit distinction, then, is between these types of activity, and those shared by small employers in Goldthorpe Class IVa (see the discussion in Chapter 5). What does this say about employment relations? And on what basis does Goldthorpe, in the current instantiation of his schema, allow professional status to override self-employed status? If the basic distinction is between employers, the self-employed and employees, but Class I includes managers, professionals and employers, what are the criteria being used to say these share an affinity, or the same structural position? These questions had to be addressed before full validation of the NS-SEC and its operationalisations was possible. 16. Zeller and Carmines argue strongly that criterion-related validity has very limited usefulness in the social sciences, for the simple reason that with respect to many variables, there are no criteria against which the measure can be reasonably evaluated. Moreover, it is clear that the more abstract the concept, the less likely one is to be able to discover appropriate criteria for assessing a measure of it (1980:81). We could note that, not withstanding Evans and Mills essential work, it might seem strange to think of the NS-SEC as a predictor of employment conditions. However, as Bailey argues (1988), the many types of validity discussed by authors in different ways are not essentially distinct; they are all in fact part of the same concept. But while statistical techniques have been developed and have advanced in rigorous and sophisticated ways, the concept of validity has not been awarded the same treatment. What we need to think about, says Bailey, is whether what we are trying to measure (class) is (1) a theoretical concept rather than an empirical reality, or (2) an unmeasured empirical entity. It is probable that it is both at different times. It is likely that we think of class as (1) a sociological concept; (2) an actually occurring phenomenon, which is difficult to measure directly; and (3) a measure or scale that yields a value for members of the population. A given concept, its empirical occurrence, and the corresponding measurement are therefore separate and distinct elements (Bailey 1988:24). When it comes to validating a measure we will be confused unless we separate out these three levels. 102

111 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 8 Validity, then, involves validating the relationship between the concept and its empirical occurrence, between the concept and the measure, and between the empirical occurrence and the measure. If the different employment relations and conditions experienced by holders of different positions within the service relationship/intermediate/labour contract distinction constitute the empirically occurring entity, then the relationship between this entity and the measure of social class must be validated. This is what Evans and Mills have been doing when validating the Goldthorpe class schema. It is perhaps an easier way of understanding what is being done than using the term criterion validity but, whatever term is used, this type of validation work has certainly been important, necessary and relevant to the assessment of the proposed NS-SEC. Construct validity 17. Conceptually, construct validity is less problematic than criterion-related validity. It can be used when it is unclear whether a measurement is an assessment or a predictor, that is, whether it directly measures the sum of a set of acquisitions, skills, or attributes, or whether it serves as a proxy measure for something else concurrent or predicted (c.f. Nunnally 1959). Construct validity involves assessing how a measure relates to other variables in ways predicted by theory (but do not be confused, this is not what is termed predictive validity!) For Zeller and Carmines (1980), both criterion and content validity have limited usefulness for the social sciences, where it is often difficult to determine adequate criterion-related variables, and impossible to define a universe of content for the quality to be measured. Construct validity is far more appropriate. If the variable is intended to reflect a particular construct, to which attach certain meanings, then hypotheses can be constructed and tested based on what we understand about the construct. In other words, construct validity focuses on the assessment of whether a particular measure relates to other measures consistent with theoretically derived hypotheses concerning the concepts (or constructs) that are being measured (ibid:81). A common example is validation of IQ measures. It is expected, for example, that IQ will increase with age during childhood, and so the relationship of the devised measure to age can be used as a construct validity test (Anastasi 1990). 18. Goldthorpe has stated unequivocally that concepts such as his class schema should be judged by their consequences, not by their antecedents (Erikson and Goldthorpe 1992:35), and has confirmed more recently that class analysis does not entail a commitment to any particular theory of class but, rather, to a research programme (Goldthorpe and Marshall 1996). Since construct validity involves defining a measure in terms of what it does, it was appropriate to test the construct validity of his concept of social class and its operationalisation into the NS-SEC. 19. There are three steps to construct validity (Zeller and Carmines 1980): we should first specify the theoretical relationship between the measure and other variables; then measure the empirical relationship between them; and finally, and essentially, interpret the findings. To take the first step, specifying the theoretical relationship, years of research will hopefully have taught us what to expect in terms of the relationships between variables. We can draw on this experience in a construct validation exercise. For a variable measuring social class there is a mass of literature to draw on, much of it concerned with the relationship between class and social inequalities. As Egidi and Schizzerotto eloquently state, a valid measure of social class based on occupation should reveal relevant variance in the population: [It] should be able to reveal real similarities of lifeconditions among the incumbents of occupations belonging to the same stratum, or class, and likewise real differences in life chances among individuals with occupations belonging to distinct strata or classes. In other words, within each context of social inequality, the variance in the degree to which a given attribute is possessed within a stratum or class must always be less than the variance among diverse strata or classes. (1996: 252) 20. To address the second step, measuring the empirical relationship, in order to test the validity of a class-based measure it is advisable to examine the relationship between the measure and various other measures associated with inequality, while also controlling for factors such as gender, generation, ethnicity, and residential area, that is, other aspects of social difference or division. Areas of social life in which one may hypothesise the existence of inequality tied to occupational position include the distribution of wealth, income and consumption; educational achievements; and mortality and morbidity (c.f. Egidi and Schizzerotto 1996). 21. Finally, the results need to be interpreted. There are at least three possible interpretations when weak links are revealed to exist between hypothetically closely related variables in the construct validation exercise. However, there are ways of dealing with each in order to continue with the exercise (Zeller and Carmines 1980). It is possible that the measure is not valid, that it does not measure (in our example) social class as we conceive it and thus does not relate in expected ways to other variables. However, before we would draw that harsh conclusion, we would need to consider other 103

112 Appendix 8 The National Statistics Socio-economic Classification: Origins, Development and Use possibilities, for example that (1) the theory which predicts that two variables will be related in certain ways is wrong, for example, class may not actually relate to voting behaviour in ways we expected; (2) inappropriate statistical techniques may have been used in testing the hypothesis; and (3) the other variables used in the analyses may themselves lack construct validity and may need to be measured in different ways. Construct validity exercises, therefore, should always be theoretically driven, use appropriate methodological procedures, and ensure that the other variables used have been properly validated. Only under such conditions can we conclude that negative evidence is due to the absence of construct validity of the measure (ibid:83). Conclusion 22. The Review Committee decided to construct a single new SEC based conceptually on the Goldthorpe schema. This new SEC was to be operationalised using information on occupation and employment status, combining these units into clusters which attain maximum between-class and minimum withinclass heterogeneity with respect to employment relations and conditions. However, the new SEC was also required to be as continuous with SC and SEG as possible. This new SEC then had to be validated as an operationalisation of Goldthorpe s concept of class. Although there are four main types of validity relevant to the assessment of the validity of a measure (face, content, criterion and construct), for a sociological measure such as the NS-SEC, the most appropriate are face, criterion and construct validity. 23. Face validity involved ensuring that the NS-SEC distinguished employers, the self-employed and employees, and that no single SEC category combined these basic groups. We would also expect to find that the NS-SEC further distinguished employees in terms of the service relationship and labour contract. The NS-SEC could only be said to have face validity if there were categories containing senior managerial, professional and administrative positions and distinct categories for employees, with no supervisory role, working in routine occupations. Face validity may appear somewhat superficial and unconvincing, but it is an essential first step. Any measure or indicator of a sociological construct should have face validity at the very least. 24. Content validity would involve much the same as face validity, tied as it is to the nominal definition of the concept being measured. However, it is difficult, if not impossible, to gain consensus as to the universe of content of sociological variables and content validation depends on subjective judgements with regard to how adequately the content has been defined and sampled. 25. Criterion-related validity involves determining criterionrelated variables which relate to the concept being measured, but which have not been measured directly, and testing whether these correlate with the new measure. As discussed above, the NS-SEC operationalises Goldthorpe s concept of class using information on occupation and employment status. It therefore acts as a proxy for the underlying concept of social class, without directly indexing the characteristics identified as part of the concept. In order to validate the NS-SEC, we examined the relationship between the measure and sets of criterion-related variables that more directly measure the elements of the concept, especially variables measuring differences in forms of remuneration, prospects and autonomy. 26. Construct validity involves assessing how a measure relates to other variables in ways predicted by theory. For example, it is expected that a valid measure of social class will correlate with educational attainment in certain specifiable ways. If it does not then there is a chance that it is not a valid measure. Construct validity should take place in three clear phases: hypotheses should be constructed specifying the theoretical relationship between the construct or measure and other variables; the empirical relationship between them should be measured; and the findings interpreted. When the measured empirical relationship does not coincide with the expected theoretical relationship, this can be interpreted in several ways: the theoretical relationship being specified could be wrong; the other variables used could be poorly measured; the statistical procedures may be inappropriate to the task; or, of course, the measure being validated could be invalid. Construct validation of the NS-SEC employed a variety of different datasets to examine various sets of theoretical relationships. 27. The NS-SEC should look, on the face of it, as if it is a measure of Goldthorpe s concept of social class and it does. More importantly, it should (and does) have both criterion and construct validity. This involves ensuring that it is measuring what it is intended and purported to measure; and that, as a measure of social class, it behaves in ways predicted by theory. In short, before we could claim validity for the NS-SEC, we had to ensure that observed patterns how things operate in reality corresponded with theoretical patterns how we think the world works (Trochim 1998). 104

113 The National Statistics Socio-economic Classification: Origins, Development and Use Appendix 8 Appendix 8 References Anastasi, A. (1990) Psychological Testing. New York: Maxwell. Bailey, K.D. (1988) The Conceptualization of Validity: Current Perspectives, Social Science Research, 17: Birkelund, G., Goodman, L. and Rose, D. (1996) The Latent Structure of Job Characteristics for Men and Women, American Journal of Sociology, 102, 1: Carmines, E.G. and Zeller, R.A. (1979) Reliability and Validity Assessment. Beverley Hills: Sage. Cronbach, L. and Meehl, P. (1955) Construct Validity in Psychological Tests, Psychological Bulletin, 52, 4: Egidi, V. and Schizzerotto, A. (1996) Social Stratification and Mobility. Concepts, Indicators and Examples of Application, Proceedings of the Siena Group Meeting June Paris: INSEE. Erikson, R. and Goldthorpe, J.H. (1992) The Constant Flux: A Study of Class Mobility in Modern Britain. Oxford: Clarendon Press. Evans, G. (1992) Testing the Validity of the Goldthorpe Class Schema, European Sociological Review, 8: Evans, G. (1996) Putting men and women into classes: an assessment of the cross-sex validity of the Goldthorpe class schema, Sociology, 30, Evans, G. and Mills, C. (1996) Assessing the criterion-related validity of the Goldthorpe class schema among men and women: A latent log-linear model approach. Mimeo. Oxford: Nuffield College. Evans, G. and Mills, C (1997) In Search of the Wage Labour/ Service Contract. Paper prepared for the Spring meeting of the ISA RC28 (Social Stratification) Tel Aviv, May Evans, G. and Mills, C (1998a) A Validation of the New SEC. Mimeo. Oxford: Nuffield College. Evans, G. and Mills, C (1998b) Identifying Class Structure: A Latent Class Analysis of the Criterion-Related and Construct Validity of the Goldthorpe Class Schema, The European Sociological Review, 14, 1: Goldthorpe, J.H. (with C Llewellyn) (1980) Social Mobility and Class Structure in Industrial Societies. Oxford: Clarendon Press. Goldthorpe, J.H. (1997) The Goldthorpe Class Schema: some observations on conceptual and operational issues in relation to the ESRC review of government social classifications in D. Rose and K.O Reilly (eds.) Constructing Classes: Towards a New Social Classification for the UK. Swindon: ESRC/ONS. Goldthorpe, J.H. and Marshall, G (1996) The promising future of class analysis in D. Lee and B. Turner Conflicts About Class. Debating Inequality in Late Industrialism. London: Longman. Henerson, M., Morris, L.L., Fitz-Gibbon, C.T. (1987) How to Measure Attitudes. Newbury Park: Sage. Kerlinger, F.N. (1986) Foundations of Behavioral Research. CBS Publishing Japan Ltd. Marshall, G., Rose, D., Newby, H., and Vogler, C. (1988) Social Class in Modern Britain. London: Hutchinson. Moser, C.A. and Kalton, G. (1971) Survey Methods in Social Investigation. London: Heinemann. Nunnally, J. Jr. (1959) Tests and Measurements. Assessment and Prediction. New York: McGraw Hill. Nunnally, J.C. and Bernstein, I.H. (1994) Psychometric Theory. New York: McGraw-Hill. Rose, D (1995) A Report on Phase 1 of the ESRC Review of OPCS Social Classifications, reproduced as Appendix 1 in D. Rose and K. O Reilly (eds.) Constructing Classes: Towards a New Social Classification for the UK. Swindon: ESRC/ONS. Rose, D. and O Reilly, K. (1997) The ESRC Review of Government Social Classifications. Report on Phase 2 to the Office for National Statistics. Colchester: ESRC Research Centre on Micro-Social Change, University of Essex. Trochim, W. (1998) The Knowledge Base. An Online Research Methods Textbook. URL kbhome.htm. de Vaus, D.A. (1996) Surveys in Social Research. London: UCL Press. Zeller R.A. and Carmines, E.G. (1980) Measurement in the Social Sciences. Cambridge: Cambridge University Press. 105

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