SOC 2020 Volume 3: the National Statistics Socio-economic Classification (NS-SEC rebased on the SOC 2020)

1.1 Before 2001, two socio-economic classifications (SECs) were widely used in the UK in both official statistics and academic research: Social Class based on Occupation (SC, formerly Registrar General’s Social Class) and Socio-economic Groups (SEGs).

1.2 In 1994, the Office of Population Censuses and Surveys, now part of the Office for National Statistics (ONS), commissioned the Economic and Social Research Council (ESRC) to undertake a review of government social classifications.

1.3 As a result of the review, the ESRC recommended that a new SEC, the National Statistics Socio-economic Classification (NS-SEC), replace both SC and SEGs. You can find full details of the review and its conclusions in Rose and Pevalin with O’Reilly 2005. A researcher’s guide to the classification has also been produced (see Rose and Pevalin 2003).

1.4 The NS-SEC was developed from a sociological classification that has been widely used in pure and applied research, known as the Goldthorpe Schema (see Goldthorpe 1980 and 1987, 1997, 2007; Erikson and Goldthorpe 1992). The decision to adopt the Goldthorpe Schema as the basis for the NS-SEC was made because it is accepted internationally and is conceptually clear. It has also been reasonably validated both as a measure and as a good predictor of health, educational and many other outcomes. However, the NS-SEC improves on the Goldthorpe Schema as a result of its more thorough validation.

1.5 The final phase of the review involved rebasing the NS-SEC on the new Standard Occupational Classification 2000 (SOC 2000) published in June of that year. Since 2001, the NS-SEC has been available for use in all official statistics and surveys.

1.6 The NS-SEC was subsequently rebased on SOC 2010 by Rose and Pevalin and published in SOC 2010 Volume 3. This volume presents the NS-SEC as rebased on SOC 2020.

2.1 The National Statistics Socio-economic Classification (NS-SEC) has been constructed to measure the employment relations and conditions of occupations (see Goldthorpe 2007). Conceptually, these are central to showing the structure of socio-economic positions in modern societies and helping to explain variations in social behaviour and other social phenomena.

2.2 It is important that all of us who use the NS-SEC understand its conceptual basis and what it is measuring so that we can use it correctly, improve our explanation of results and investigate whether the classification continues to be valid.

2.3 A clear conceptual basis does not remove all barriers to explaining what socio-economic differences mean; employment is not the only determinant of life chances and not everything can be explained by what a classification directly measures. However, a properly constructed and validated classification such as the NS-SEC removes at least one barrier to explanation. It was not designed to offer better statistical associations than Social Class based on Occupation (SC) and Socio-economic Groups (SEGs) but to improve the possibility of explaining them. As it measures employment relations (that is, aspects of work and market situations and of the labour contract), it enables us to more readily construct causal narratives that specify how the NS-SEC links to a range of outcomes via a variety of intervening variables (see Rose and Pevalin with O’Reilly 2005:16 to 19).

2.4 The NS-SEC is an occupationally based classification, but it has rules to provide coverage of the whole adult population. The information required to create the NS-SEC is occupation coded to the unit groups (OUG) of the Standard Occupational Classification 2020 (SOC 2020) and details of employment status: whether an employer, self-employed or employee; whether a supervisor; and the number of employees at a workplace. Similar information was required for SC and SEGs.

2.5 The NS-SEC aims to differentiate positions within labour markets and production units in terms of their typical “employment relations”. Among employees, there are diverse employment relations and conditions (that is, they occupy different labour market situations and work situations).

2.6 Labour market situation equates to 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.

2.7 The NS-SEC categories distinguish different positions (not people) as defined by social relationships in the workplace (that is, by how employees are regulated by employers through employment contracts).

2.8 The NS-SEC distinguishes three forms of employment regulation:

• service relationship: the employee renders service to the employer in return for compensation, which can be both immediate rewards (for example, salary) and long-term or prospective benefits (for example, assurances of security and career opportunities); the service relationship typifies Class 1 and is present in a weaker form in Class 2
• labour contract: the employee gives discrete amounts of labour in return for a wage calculated on the amount of work done or time worked; the labour contract is typical in Class 7 and, in weaker forms, in Classes 5 and 6
• intermediate: these forms of employment regulation combine aspects from both the service relationship and labour contract, and they are typical in Class 3

2.9 The classification also separately identifies categories for large employers in its operational version and for small employers and the self-employed with no employees in both the operational and analytic versions. For more information, see Section 5: Category descriptions and operational issues.

2.10 The version of the classification that will be used for most analyses has eight classes, shown in Table 1, the first of which can be subdivided.

3.1 Traditionally, the unit of analysis or class composition has been the family or household rather than the individual. The nuclear family is seen as the basic structural element because of the inter-dependence and shared conditions of family members. A family member’s own position may have less relevance to their life chances than those of another family member. A practical solution to this problem has been to select one family or household member as a reference person and take that person’s position to stand for the whole household.

3.2 Essentially, assigning a National Statistics Socio-economic Classification (NS-SEC) category to a household involves deciding which household member best defines that household’s position. This person is called the household reference person (HRP).

3.3 From 2001, the HRP has been defined as the person responsible for owning or renting or who is otherwise responsible for the accommodation. In the case of joint householders, the person with the highest income takes precedence and becomes the HRP. Where incomes are equal, the oldest person is taken as the HRP. This procedure increases the likelihood both that a woman will be the HRP and that the HRP better characterises the household’s social position.

3.4 The availability of information on household composition and other household members will determine exactly how the HRP is identified in each dataset. The definition in 3.3 is used in the Labour Force Survey (LFS). Also see our article, Families and households statistics explained.

4.1 The National Statistics Socio-economic Classification (NS-SEC) is nested so that the operational categories offer maximum flexibility in terms of the different collapses possible (within the underlying conceptual model of employment relations) to eight, five or three analytic classes. Table 1 presents the 14 functional and three residual operational categories of the NS-SEC and how they collapse into the eight-, five-, and three-class versions. The functional categories represent a variety of labour market positions and employment statuses.

4.2 L14 is an optional category while L15, L16 and L17 are the residual categories that are excluded when the classification is collapsed into classes.

4.3 See Section 5: Category descriptions and operational issues for detailed descriptions of the operational categories and Section 7: Continuity with Social Class and Socio-economic Group for more information about continuity with Social Class based on Occupation (SC) and Socio-economic Groups (SEGs).

4.4 The categories describe different forms of employment relations, not skill levels, so the category names deliberately do not refer to “skill”.

4.5 Figure 1 shows how to assign the operational categories of the NS-SEC to respondents.

Figure 1: Assigning functional and residual categories of the NS-SEC to respondents

Download this image Figure 1: Assigning functional and residual categories of the NS-SEC to respondents

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5.1 In an employment relations approach, the important distinctions are those between:

• employers: who buy the labour of others and assume some degree of authority and control over them
• self-employed (or “own account”) workers: who neither buy labour nor sell their labour to others
• employees: who sell their labour to employers

Employees are further differentiated according to the employment relations of their occupation. See 2.8 for descriptions of the main forms of employment regulation distinguished by the National Statistics Socio-economic Classification (NS-SEC).

5.2 The NS-SEC has two types of operational category: functional and residual. Residual category L14 (Never worked and long-term unemployed) can be considered optional. In the NS-SEC derived from both the Standard Occupational Classification 2000 (SOC 2000) and SOC 2010, eight of the categories had sub-categories (that is, L3.1 “Traditional” professional employees, L7.2 Intermediate sales and service occupations, and L12.4 Semi-routine operative occupations). During the rebasing project, it was noted that many of these sub-categories were difficult to maintain and their primary purpose of continuity with former classifications (Social Class based on Occupation (SC) and Socio-economic Groups (SEGs)) had been superseded (see Section 7: Continuity with Social Class and Socio-economic Group). It was therefore decided to remove the sub-categories in the functional operational categories.

5.2.1 Functional operational categories

L1 Employers in large organisations

These are people who employ others (and so assume some degree of control over them) in enterprises employing 25 or more people and who delegate some part of their managerial and entrepreneurial functions to salaried staff.

Higher professionals who are also large employers are not allocated to L1 but to L3. This is because their status as professionals is more relevant in terms of employment relations than their position as an employer.

L2 Higher managerial and administrative occupations

These are positions in which there is a service relationship with the employer and that involve general planning and supervision of operations on behalf of the employer.

For certain managerial unit groups of SOC 2020, the number of employees in an organisation can help to distinguish between higher managerial occupations in L2 and lower managerial occupations in L5. However, some managerial occupations coded to the unit groups (OUGs) are wholly or primarily occupied by higher or lower managers, so this does not always apply.

L3 Higher professional occupations

These are positions, whether occupied by employers, the self-employed or employees, that cover all types of higher professional work. As with L2, employees in these groups have a service relationship with their employer.

It is important to note that for professionals, independent practice and salaried employment are often indistinguishable and that true self-employment is difficult to identify.

An occupation that has been designated as professional is professional regardless of employment status. For example, a supervisor who is also a scientist is classified as a professional (in L3) and not as a supervisor (L6).

L4 Lower professional and higher technical occupations

These are positions, whether occupied by employers, the self-employed or employees, that cover lower professional and higher technical occupations. Employees in these groups have an attenuated form of the service relationship.

Employees in category L4 share fewer of the conditions associated with the service relationship than those in L3.

The rules for allocating lower professional OUG or employment status combinations to the NS-SEC are complicated. The employee relations approach holds that lower professional status takes precedence over small employer status but not over large employer status. Employers in small organisations who are in lower professional occupations are allocated to L4 rather than L8. But lower professionals who are also large employers are allocated to L1.

L5 Lower managerial and administrative occupations

These are positions that have an attenuated form of service relationship. Employees in these groups generally plan and supervise operations on behalf of the employer under the direction of senior managers.

These occupations share fewer of the conditions associated with the service relationship than those in L2.

As discussed under L2, the size rule is sometimes used as an indicator of the conceptual distinction between higher and lower managerial occupations. However, some OUGs are regarded as inherently lower managerial and allocated to L5 regardless of organisation size.

L6 Higher supervisory occupations

These are positions (other than managerial) that have an attenuated form of the service relationship. These positions involve formal and immediate supervision of others, and they primarily cover intermediate occupations in L7, but also some occupations in L11 to L13, classes 6 and 7.

Typically, these higher supervisory positions are found in large bureaucratic organisations. Employees in these positions are supervising the work of others and so exert a degree of authority over them.

L7 Intermediate occupations

These are positions in clerical, sales, service and intermediate technical occupations that do not involve general planning or supervisory powers. Positions in this group are intermediate in terms of employment regulation in that they combine elements of both the service relationship and the labour contract.

Although positions in L7 have some features of the service relationship, they do not usually involve any exercise of authority (other than in applying standardised rules and procedures where discretion is minimal) and are subject to detailed bureaucratic regulation.

L8 Employers in small organisations

These are people, other than higher or lower professionals, who employ others and so assume some degree of control over them. These employers carry out all or most of the entrepreneurial and managerial functions of the enterprise and have fewer than 25 employees.

Employers in small establishments, although they employ others, do not usually delegate most of their managerial or entrepreneurial functions to them. Small employers remain essentially in direct control of their enterprises.

The distinction between large and small employers is made by applying a size rule of 25 employees. It is likely that the majority of small employers have only one or two, or at most 10 employees. Most people in this group are similar in many ways to the self-employed or own account workers in L9.

L9 Own account workers

These are self-employed positions in which people are engaged in any (non-professional) trade, personal service or semi-routine, routine or other occupation but have no employees other than family workers.

Own account workers neither sell their labour to an employer nor buy the labour of others.

L10 Lower supervisory occupations

These are positions with a modified form of labour contract that cover occupations included in groups L11, L12 and L13, and involve formal and immediate supervision of others engaged in such occupations.

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 sometimes distinguished by having a job title (“foreman” or “supervisor”) from an OUG, which, when combined with employee status, is allocated to L11, L12 or L13.

L11 Lower technical occupations

These are positions with a modified labour contract, in which employees are engaged in lower technical and related occupations.

Positions in this category are distinguished by having a modified labour contract. Employees are more likely than those in L12 or L13 to have some service elements in their employment relationship (for example, work autonomy). Operationally, job title does not help with the allocation of occupation to L11 as not all “skilled” OUGs are included. Some are in L7 and others in L12 and L13.

L12 Semi-routine occupations

These are positions with a slightly modified labour contract, in which employees are engaged in semi-routine occupations.

Employees in these positions are regulated by an only slightly modified labour contract typified by a short term and the direct exchange of money for effort. The category name “semi-routine” is designed to indicate that, in employing this group, employers must slightly improve on the basic labour contract. The work involved requires at least some element of employee discretion.

L13 Routine occupations

These are positions with a basic labour contract, in which employees are engaged in routine occupations.

These positions have the least need for employee discretion, and employees are regulated by a basic labour contract.

5.2.2 Residual operational categories

L14 Never worked and long-term unemployed

These are positions that involve involuntary exclusion from the labour market, specifically (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.

L14.1 Never worked

L14.2 Long-term unemployed

Both those who have never been in paid employment (although available for work) and the long-term unemployed could be treated in employment relations terms as a separate category of those who are excluded from employment relations of any kind. Operationally, however, both these groups (those who have never worked, although available for work, and the long-term unemployed) are difficult to define. The problems here cannot be separated from the more general ones concerning the non-employed population.

Those who have never worked but are seeking or would like paid work are allocated to operational sub-category L14.1. There is an argument that the long-term unemployed should not be classified according to their last job but should be assigned to sub-category L14.2 on the grounds that they are excluded from employment relations. Therefore, when the NS-SEC is collapsed to an analytic variable, you should include the long-term unemployed with those who have never worked.

It is not possible to define the long-term unemployed in any hard and fast way. You will have to make your own decisions, depending on the purpose of your research. You may not want to implement L14 at all so that you exclude the “never worked” from the analytic versions and classify all unemployed people according to their last main jobs. Alternatively, you may want to implement the class and use a six-month unemployment rule. Or, you might prefer to use a one- or even two-year unemployment rule. See Section 10: The questions to ask.

L15 Full-time students

These are people aged over 16 years who are engaged in full-time courses of study in secondary, tertiary or higher education institutions.

Full-time students are recognised as a category in the full classification for reasons of completeness. Since many students will have had or still have paid occupations, you could classify them by current or last main job, although we would not usually expect them to be classified in this way. Conventionally, where full-time students are included in analyses (for example, in research on education), they are normally allocated a position through their family household. See Section 10: The questions to ask.

L16 Occupations not stated or inadequately described

This category is for cases where the occupational data requested in surveys and censuses are not given or are inadequate for classification purposes.

L17 Not classifiable for other reasons

No matter what rules are devised, there will be some adults who cannot be allocated to an NS-SEC category. For example, the research may have been designed to exclude older people from employment questions. For completeness, you should include in L17 any people who cannot be allocated to another category.

5.3 The non-employed

This term includes unemployed people (except the long-term unemployed and those who have never worked); retired people; those looking after a home; those on government employment or training schemes; and people who are sick or disabled. To improve population coverage, in most cases, the normal procedure is to classify these people according to their last main job. The chief exceptions to this rule are full-time students, the long-term unemployed and people who have never worked (see L14 and L15).

5.4 The armed forces

Armed forces personnel are allocated to operational categories L2 Higher managerial occupations for SOC 2020 OUG 1161 (officers); L6 Higher supervisory occupations for supervisors in OUG 3311 (NCOs and other ranks), and L7 Intermediate occupations for employees in OUG 3311.

Depending on the focus of your research and any comparability issues with the previous Socio-economic Classifications (SECs), you can choose to exclude armed forces personnel from your analyses. If you decide to exclude them, we recommend that you perform selection commands at the OUG level rather than on NS-SEC categories as other occupations are included in those operational categories.

6.1 The number of classes you use will depend on both your analytic purposes and the quality of available data. Within the conceptual model, it is possible to have eight-, five- and three-class versions of the National Statistics Socio-economic Classification (NS-SEC). Table 1 shows the nested relationship between the different versions.

6.2 Because it effectively eliminates a separate class of self-employed, the three-class version may be assumed to involve a form of hierarchy, but none of the other versions can be regarded as ordinal scales. However, it would be possible (and in some ways preferable) to retain this class by creating a four-class model. It is not desirable to create an ordinal scale by combining the self-employed in Class 4 with the intermediate Class 3 because the self-employed are distinctive in their life chances and behaviour, but users of the old Socio-economic Classifications (SECs) wanted something similar to the old “manual–non-manual” divide and so the three-class model was created as an approximation. Users should note that the meaning of “intermediate occupations” is not therefore the same in the three-class model as in the others. Nevertheless, we strongly recommend that you accept the theoretical and measurement principles of the NS-SEC, take advantage of the conceptual base of the model for developing hypotheses linking it to outcomes of interest and use appropriate analytic techniques for nominal data.

6.3 You should also consider carefully whether to allocate those who have never worked and the long-term unemployed to semi-routine or routine and manual occupations respectively or keep them separate. For example, if you are doing health analyses, you would need to be very careful about how you define the long-term unemployed and those who have never worked, as including the permanently sick would clearly not be sensible. They should be classified on the basis of 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.

6.4 Although the name of the third class in the three-class version of the NS-SEC is “routine and manual occupations”, the NS-SEC does not perpetuate the manual–non-manual divide. Changes in the nature and structure of both industry and occupations have rendered this distinction outmoded and misleading.

7.1 In the Standard Occupational Classification 2000 (SOC 2000) version of the National Statistics Socio-economic Classification (NS-SEC), the operational categories and sub-categories could be aggregated to produce approximated Social Class based on Occupation (SC) and approximated Socio-economic Group (SEG). These approximations achieved a continuity level of 87% for both SC and SEG.

7.2 In the course of rebasing the NS-SEC on SOC 2000, the developers produced a derivation of SC and SEG by making certain assumptions on changes over time and assessments of the relationship between SOC 90 and SOC 2000 unit groups. You can find these derivation matrices on the website of the Institute for Social and Economic Research at the University of Essex and in the UK Data Archive.

7.3 This exercise was replicated for the SOC 2010 rebasing funded by a grant from the British Academy and the Leverhulme Trust. The British Academy and the Leverhulme Trust are currently funding a new exercise of this kind for SOC 2020 which should be completed by autumn 2021. The results will appear online as in paragraph 7.2.

8.1 There are three methods to derive the operational categories L1 to L13 of the National Statistics Socio-economic Classification (NS-SEC): full, reduced and simplified. All three methods require Standard Occupational Classification 2020 (SOC 2020) unit group, so the method you choose depends on the information you gather about employment status.

8.2 The different methods allow you to apply the NS-SEC to registration and other administrative data, census and survey data, and to data of varying robustness. The reduced method was developed for sources unable to collect information on size of organisation, including the 2011 and 2021 Censuses; the simplified method provides a last resort solution. See Section 12: Deriving the NS-SEC: full, reduced and simplified methods and Section 13: Deriving the NS-SEC: self-coded method for fuller descriptions of the three methods and how to derive the NS-SEC using each one.

8.3 Although occupationally based, there are procedures for classifying non-employed people to the NS-SEC (see 5.3).

8.4 Office for National Statistics (ONS) researchers have also developed a self-coded version of the NS-SEC, which is suitable for use in situations such as postal surveys where the collection and coding of detailed occupation information is not justified. See Section 13: Deriving the NS-SEC: self-coded method.

8.5 Full method

Information required: SOC 2020 unit group, employment status and size of organisation.

The full method achieves the best quality derivation by using all three items of information, as you can see in Figure 2.

8.6 Reduced method

Information required: SOC 2020 unit group and employment status.

The reduced method was developed for sources unable to collect information on size of organisation such as birth registration data and the 2011 and 2021 Censuses. See Figure 3.

8.7 Simplified method

Information required: SOC 2020 unit group.

The simplified method provides a last resort solution when there is no information on employment status. If used, no records should be allocated to the first operational category (L1) of the classification.

8.8 In Tables 2 to 6, data come from a special dual SOCcoded (2010 and 2020) version of Quarter 1 (Jan to Mar) of the 2019 Labour Force Survey (LFS). Table 2 presents the distributions of the seven-class NS-SEC from each of the derivation methods, and Table 3 compares the seven-class NS-SEC distributions from the full derivation method based on SOC 2010 and SOC 2020.

8.8 Tables 4 and 5 show the performance of the reduced and simplified derivation methods compared with the full method. Using seven classes, the reduced method correctly allocates 98.0% of cases compared with the full method. The simplified method correctly allocates 86.7% of cases compared with the full method.

8.9 Table 6 presents the correct allocation percentages across SOC 2010, SOC 2020, operational categories and analytic classes, and derivation method.

9.1 To apply the National Statistics Socio-economic Classification (NS-SEC) to the census and social surveys, you need data on occupation and employment status. You can allocate an NS-SEC category by using a combination of occupation coded to the unit groups (OUG) of Standard Occupational Classification 2020 (SOC 2020) and employment status and size of organisation, in the form of an employment status variable.

9.2 The employment status variable is created by combining data on whether an individual is an employer, self-employed or an employee; size of organisation (where collected); managerial status (for some OUGs); and supervisory status.

9.2.1 Employer, self-employed or employee

You must distinguish between employers (those who employ others); the self-employed (who work on their own account with no employees); and employees (who are employed by an individual or organisation).

9.2.2 Size of organisation

You must distinguish between employers in large and small establishments and, for some occupations, between higher and lower managers. To do this, you need information on the number of employees in the workplace.

You make the distinction between large and small employers by applying a size rule cut-off of 25 employees. Individual employers with 25 or more employees are deemed to own “large” organisations; those owning enterprises below this threshold are classified as “small” employers. You use a similar threshold to distinguish between managers in large organisations (25 or more employees) and managers in small organisations (less than 25 employees).

In government social surveys, size of organisation has been related to the workplace (that is, the local unit of the establishment at which the respondent works). When size of organisation is used, it should refer to an “enterprise” as defined in the Inter-Departmental Business Register (IDBR) (Council Regulation (EEC) No 696/93) and not to a local unit. Local unit or workplace should be used only if it is impossible or impractical to obtain information at the enterprise level.

9.2.3 Managerial or supervisory status

Managerial status is required when some OUGs allow for both managers and supervisors. For three of these OUGs, “other employees” are also allowed so you need to distinguish between managers, supervisors and other employees (see question 5(b) in 10.4). “Other employees” are not allowed for 6240 (Cleaning and housekeeping managers and supervisors). These OUGs are:

3319 Protective service associate professionals n.e.c.
3582 Health and safety managers and officers
6240 Cleaning and housekeeping managers and supervisors
7131 Shopkeepers and owners – retail and wholesale

Supervisors are employees who are not managers but who are responsible for supervising the work of other employees. In SOC 2020, there are supervisor-only unit groups where the role of supervisor is distinct and is generally regarded as separate from the type of work that is being supervised. The eight OUGs are:

4142 Office supervisors
5250 Skilled metal, electrical and electronic trades supervisors
5330 Construction and building trades supervisors
7132 Sales supervisors – retail and wholesale
7220 Customer service supervisors
8160 Production, factory and assembly supervisors
9251 Elementary storage supervisors
9261 Bar and catering supervisors

10.1 Two series of questions are needed in order to derive the National Statistics Socio-economic Classification (NS-SEC): three on occupation and five on employment status or size of organisation. These are designed to harmonise the collection of data across interview surveys.

10.2 The three questions needed for coding occupation and the five for deriving employment status or size of organisation are shown here with instructions for interviewers.

10.3 Occupation

Questions one to three collect information for coding to the Standard Occupational Classification 2020 (SOC 2020). They ask about current job for those in paid work and about last main job for those who have ever had paid work. The exceptions are full-time students and those who have been unemployed for more than a year, who you should allocate to residual categories (L14 and L15, see Figure 1).

Question one: Industry description

“What did the firm or organisation you worked for mainly make or do (at the place where you worked)?”

(Open)

Note: You need a full description. Probe for, for example, “manufacturing”, “processing” and “distributing” and, for example, main goods produced, materials used and wholesale or retail.

Question two: Occupation title, current or last main job

“What was your (main) job?”

(Open)

Question three: Occupation description, current or last main job

“What did you mainly do in your job?”

(Open)

Note: Check for any special qualifications or training, for example, needed to do the job.

10.4 Employment status or size of organisation

Questions 4 to 8 collect information for deriving the employment status or size of organisation variable. If the respondent answers “Employee” to question 4, you should ask questions 5 and 6. If the respondent answers “Self-employed” to question 4, you should ask question 7. And, if the respondent answers “With employees” to question 7, you should ask question 8.

Question 4: Employee or self-employed

“Were you working as an employee or were you self-employed?”

1. Employee

   Go to question 5

2. Self-employed

   Go to question 7

Note: The distinction between employee and self-employed is based on the respondents’ own assessment of their employment status in their main job.

Question 5: Managerial or supervisory status

(a) “In your job, did you have any formal responsibility for supervising the work of other employees?”

1. Yes

   Go to question 6

2. No

   Go to question 6

Note: Do not include supervisors of children (for example, teachers, nannies childminders); supervisors of animals; or people who supervise security or buildings only, like caretakers and security guards.

As described in 9.2.3, there are some occupations coded to the unit groups (OUGs) that need information on managerial or supervisory status. Generally, self-reported managerial responsibilities are not required for deriving the employment status variable except for these four OUGs.

(b) “Do you have any managerial duties?”

1. Manager

   Go to question 6

2. Foreman/supervisor

   Go to question 6

3. Not manager/supervisor

   Go to question 6

Question 6: Number of employees

“How many people worked for your employer at the place where you worked? Were there...

1. “1 to 24*”
2. “25 or more”

Note: Be clear that you are asking about the total number of employees at the respondent’s workplace, not just the number employed within their particular section or department. You are also asking about the local unit of the establishment at which the respondent works (that is, the geographical location where the job is mainly carried out). Normally, this will consist of a single building, part of a building or, at the largest, a self-contained group of buildings. You are not asking about the entire enterprise. Although it is preferable to gather data at the enterprise level, questions about local units produce more reliable results. (See also 9.2.2.)

Question 7: Self-employed working on own or with employees

“Were you working on your own or did you have employees?”

1. On own/with partner(s) but no employees

2. With employees

   Go to question 8

Question 8: Number of employees (self-employed)

“How many people did you employ at the place where you worked? Were there…

1. “1 to 24*”
2. “25 or more”

*You will need to include an additional break (1 to 9, 10 to 24) if you are intending to map the SOC 2020 codes to the International Standard Classification of Occupations 2008 (ISCO 08).

11.1 Standard Occupational Classification 2020 (SOC 2020) was published in February 2020. Volume 1 includes the structure of the classification and descriptions of the unit groups. Volume 2 contains the coding index and notes on coding. The revision process and main changes are detailed in Volume 1.

11.2 SOC 2020 has a hierarchical structure with four nested tiers. It is important to understand how this structure works before deriving the National Statistics Socio-economic Classification (NS-SEC).

11.3 The four tiers of SOC 2020 are represented in the way the occupational classification codes are numbered. They are:

• major groups – top-level, broad definitions of occupation, providing the first digit of the SOC 2020 code number
• sub-major groups – second-level definition of occupation, providing second digit
• minor groups – third-level definition, providing third digit
• unit groups – lowest, most detailed definition of occupation, providing the complete four-figure SOC 2020 code

11.4 Using the example of unit group 1211 Managers and proprietors in agriculture and horticulture, Table 7 shows how the unit groups are nested within SOC 2020’s hierarchical structure.

12.1 Using the full method

There are four steps to derive the National Statistics Socio-economic Classification (NS-SEC) using the full method.

Step one: Code occupation to the SOC 2020 four-digit unit group

Use the answers to the questions on occupation and industry (questions one to three in 10.3) to assign the four-digit unit group code of Standard Occupational Classification 2020 (SOC 2020).

Step two: Follow procedures when the answers to questions on employment status and size of organisation are missing (questions 4 to 8)

Combine the answers to the questions 4, 5 and 6, or 4, 7 and 8 to produce the employment status or size of organisation variable (see Figure 2).

Where the questions have not been answered, take the following actions:

Step three: Derive the employment status or size of organisation variable

The employment status or size of organisation variable has seven codes:

Use the answers or assumed answers to questions on employment status or size of organisation and the SOC 2020 unit group code to derive one of the seven codes. Figure 2 illustrates the process.

Figure 2: Deriving the employment status or size of organisation variable, full method

Notes:

A. Codes 2131, 2132, 2161, 2321, 2322, 2324, 2440, 2455, 2482, 2491, 2494, 3534, 3556, 4141, 4143, 5436, 6250

B. Codes: 4142, 5111, 5250, 5330, 6136, 7132, 7220, 8160, 9251, 9261

C. Codes: 3319, 3582, 6240, and 7131 are special cases. See 9.2.3

Download this image Figure 2: Deriving the employment status or size of organisation variable, full method

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Step four: Derive the NS-SEC category

With both SOC 2020 unit group code and employment status or size of organisation code, use the full derivation tables to assign an operational category (Table 9) or an analytic class (Table 10) of the NS-SEC.

The full method derivation tables contain a row for each SOC 2020 unit group, a column for simplified NS-SEC, and columns for the seven employment status or size of organisation codes.

Use the SOC 2020 unit group code to find the appropriate row, and work across the row to reach the column for the employment status or size of organisation code. Take the NS-SEC operational category or analytic class from the cell where the row and column intersect.

The following examples show how the NS-SEC operational category is derived using the full method:

Example one:

Resulting codes:

SOC 2020 unit group code 1140
Employment status or size of organisation 5
NS-SEC operational category 5

Example two:

Resulting codes:

SOC 2020 unit group code 5312
Employment status or size of organisation 2
NS-SEC operational category 8

Example three:

Resulting codes:

SOC 2020 unit group code 6240
Employment status or size of organisation (Not derived)
NS-SEC operational category 10 (from simplified NS-SEC)

Example four:

Resulting codes:

SOC 2020 unit group code 8113
Employment status or size of organisation 7
NS-SEC operational category 11

12.2 Using the reduced method

There are four steps to derive the NS-SEC by the reduced method.

Step one: Code occupation to the SOC 2020 four-digit unit group

Use the answers to the questions on occupation (questions one to three in 10.3) to assign the four-digit unit group code of SOC 2020.

Step two: Follow procedures when the answers to questions on employment status are missing

Combine the answers to questions 4, 5 and 7 to produce the employment status variable. Where the questions have not been answered, take the following actions:

Step three: Derive the employment status variable

Use the answers or assumed answers to questions on employment status and the SOC 2020 unit group code to derive one of the five codes. Figure 3 illustrates the process.

The employment status variable has five codes:

Figure 3: Deriving the employment status or size of organisation variable, reduced method

Download this image Figure 3: Deriving the employment status or size of organisation variable, reduced method

.png (39.9 kB)

Step four: Derive the NS-SEC category

With both SOC 2020 unit group code and employment status code, use the reduced derivation tables to assign an operational category (Table 11) or an analytic class (Table 12) of the NS-SEC.

The reduced method NS-SEC derivation tables contain a row for each SOC 2020 unit group, a column for simplified NS-SEC and columns for the five employment status codes.

Use the SOC 2020 unit group code to find the appropriate row and work across the row to reach the column for the employment status code. Take the NS-SEC operational category or analytic class from the cell where the row and column intersect.

The following examples show how the NS-SEC operation category is derived using the reduced method:

Example one:

Resulting codes:

SOC 2020 unit group code 1140
Employment status 3
NS-SEC operational category 5

Example two:

Resulting codes:

SOC 2020 unit group code 5312
Employment status 1
NS-SEC operational category 8

Example three:

Resulting codes:

SOC 2020 unit group code 6240
Employment status (Not derived)
NS-SEC operational category 10 (from simplified NS-SEC)

Example four:

Resulting codes:

SOC 2020 unit group code 8113
Employment status 5
NS-SEC operational category 11

12.3 Using the simplified method

There are two steps to derive the NS-SEC by the simplified method.

Step one: Code occupation to the SOC 2020 four-digit unit group

Use the answers to the questions on occupation (questions one to three in 10.3) to assign the four-digit unit group code of SOC 2020.

Step two: Derive the NS-SEC category

With the SOC unit group code, use the full or reduced derivation table to assign an operational category of the NS-SEC (see Tables 9 and 11). Use the SOC 2020 unit group code and the “ssec” column to find the NS-SEC operational category.

13.1 National Statistics Socio-economic Classification (NS-SEC) is derived from occupation and employment status information, occupation being ideally coded to the most detailed level of Standard Occupational Classification 2020 (SOC 2020). As there are 412 unit groups, this can be time-consuming and costly. The five-class self-coded version is simpler and less expensive.

13.2 The self-coded version is not as accurate as its interviewer-coded counterpart: the agreement level for NS-SEC based on SOC 2000 is 87% based on omnibus data against the self-coded version (although some disagreement between the two classifications may arise from coder error).

13.3 The five-class version of the self-coded NS-SEC has the following classes:

13.4 You derive the self-coded version from a combination of information on occupation (self-classified into eight categories) and an employment status variable that captures information on employment status and size of organisation.

13.5 The employment status variable means that you will need to know whether an individual is an employer, self-employed or an employee; the size of the organisation; and the individual’s supervisory status (see 9.2).

13.6 The four questions to include in self-coded questionnaires refer to the respondent’s current or last main job and occupation.

Ask respondents to tick one box only per question.

Question one: Employee or self-employed

“Do (did) you work as an employee or are (were) you self-employed?”

1. Employee
2. Self-employed with employees
3. Self-employed or freelance without employees (go to question 4)

Question two: Number of employees

For employees: “How many people work (worked) for your employer at the place where you work (worked)?”

For self-employed: “How many people do (did) you employ?” (Go to question 4 when you have completed this question.)

1. 1 to 24
2. 25 or more

Question three: Supervisory status

“Do (did) you supervise any other employees?” (A supervisor or foreman is responsible for overseeing the work of other employees on a day-to-day basis.)

1. Yes
2. No

Question four: Occupation

Ask respondents to tick one box to show which best describes the sort of work they do. If they are not working now, ask them to tick a box to show what they did in their last job.

1. Modern professional occupations such as: teacher, nurse, physiotherapist, social worker, welfare officer, artist, musician, police officer (sergeant or above) or software designer

2. Clerical and intermediate occupations such as: secretary, personal assistant, clerical worker, office clerk, call centre agent, nursing auxiliary or nursery nurse

3. Senior managers or administrators (usually responsible for planning, organising and co-ordinating work and for finance) such as: finance manager or chief executive

4. Technical and craft occupations such as: motor mechanic, fitter, inspector, plumber, printer, tool maker, electrician, gardener or train driver

5. Semi-routine manual and service occupations such as: postal worker, machine operative, security guard, caretaker, farm worker, catering assistant, receptionist or sales assistant

6. Routine manual and service occupations such as: HGV driver, van driver, cleaner, porter, packer, sewing machinist, messenger, labourer, waiter or waitress, or bar staff

7. Middle or junior managers such as: office manager, retail manager, bank manager, restaurant manager, warehouse manager or publican

8. Traditional professional occupations such as: accountant, solicitor, medical practitioner, scientist, or civil or mechanical engineer

13.7 There are three steps to derive the five-class self-coded NS-SEC from the answers to questions one to four:

Step one: Create the employment status variable

The employment status variable has seven codes.

Figure 4 illustrates the procedure to follow to derive an employment status variable from the answers to questions one to three.

Figure 4: Deriving the employment status/size of organisation variable, self-coded method

Download this image Figure 4: Deriving the employment status/size of organisation variable, self-coded method

.png (45.4 kB)

Step two: Create the self-coded occupation variable

On the basis of respondents’ tick-box responses to question four, create a variable with the following occupational codes:

Step three: Derive the NS-SEC

Once you have derived the employment status and occupational variables, combine them and assign one of the five NS-SEC class codes to each combination of the two variables using the matrix table (see Table 8).

If there is information missing on employment status or occupation, you can either impute missing values or treat these cases as missing data.

14.1 Many users will derive the National Statistics Socio-economic Classification (NS-SEC) by employing software to match the appropriate derivation matrix to their data by Standard Occupational Classification 2020 (SOC 2020) occupation coded to the unit groups (OUG) and then use information on the respondent’s employment status to obtain the appropriate NS-SEC operational category or analytic class.

14.2 The tables for deriving NS-SEC from the SOC 2020 are:

• full method – NS-SEC operational categories (Table 9)
• full method – NS-SEC analytic classes (Table 10)
• reduced method – NS-SEC operational categories (Table 11)
• reduced method – NS-SEC analytic classes (Table 12)
• simplified method – NS-SEC operational categories (Tables 9 and 11, look in column “ssec”)
• simplified method – NS-SEC analytic classes (Tables 10 and 12, look in column “ssec”)

Tables 9 to 12 in Excel format

Acknowledgements

The project to rebase the National Statistics Socio-economic Classification (NS-SEC) on the Standard Occupational Classification 2020 (SOC 2020) was conducted by Professor David Pevalin, Department of Sociology, University of Essex and funded by the Office for National Statistics (ONS). The project team included expert advisors: David Rose, Emeritus Professor, Institute for Social and Economic Research, University of Essex; John Goldthorpe, Emeritus Fellow, Nuffield College, Oxford; and Colin Mills, Professorial Fellow, Nuffield College, Oxford. The project team would like to thank members of the steering group and workshop participants for their valuable contributions.

Note

This work was produced using statistical data from the ONS. The use of the ONS statistical data in this work does not imply the endorsement of the ONS in relation to the interpretation or analysis of the statistical data. This work uses research datasets that may not exactly reproduce National Statistics aggregates.

A note on the derivation tables

Responses will sometimes produce combinations of codes for occupation and employment status or size of organisation that are incompatible or unallowable (for example, self-employed police officers).

In the original derivation tables, the cells for these incompatible or unallowable combinations were left empty (see Table 13). For example, for Standard Occupational Classification 2000 (SOC 2000), all managerial jobs are in major group one, which includes all the unit group codes that start with “1”. In the original derivation tables, the cells in the employees’ and supervisors’ columns for unit groups in major group one were empty.

The tables in this user manual contain no empty cells because we have used priority order rules (shown in Table 14) to fill them. Filling empty cells in this way does not make the combinations of codes allowable; it provides the best choice of National Statistics Socio-economic Classification (NS-SEC) value to use when these combinations of codes occur in data. The filled cells are shaded grey in the derivation tables (Tables 9 to 12).

Applying priority order rules to fill the derivation tables

There are two ways of dealing with incompatible or unallowable responses in data processing systems: rejecting records and setting them aside for scrutiny by clerical staff or automatically assigning a value to the records, avoiding the need for clerical intervention.

The process of filling a derivation table is done one row at a time and working from left to right across the table. Where a cell is empty, we take the employment status or size of organisation given at the top of the column and use this code to identify which row of the priority order table we should use.

Looking from left to right across the table, we take the number given in the first priority column.

Using this number as an alternative employment status or size of organisation code, we return to our original row on the derivation table to locate the cell that sits in this column.

If there is a value in this cell, this is the best alternative NS-SEC value to use for our original combination of codes, and we write it into the original empty cell.

But if the “first priority” cell is empty, we return to the priority order table. Using our original employment status or size of organisation code to identify the correct row, we locate the number in the second priority column. Again, we use this number as an alternative employment status or size of organisation code and return to our original row on the derivation table to locate the cell that sits in this column. We repeat the process until we locate a cell that contains an NS-SEC value.

For example, to fill the empty cell on row 2255 (Paramedics), under column three, of the original NS-SEC derivation table, we would use row three of the priority order table (Table 14).

The number in the first priority column is two. Using two as an alternative employment status or size of organisation code, we return to the derivation table to look in row 2255, column two. This cell is also empty. We return to row three of the priority order table to find our second priority code, which is one. Column one of row 2255 of the derivation table also gives us a blank cell. Returning to row three of the priority order table, we find that the third priority code to use is seven. This returns us to the cell on row 2255, column seven, of the derivation table, which contains the value seven. We enter seven into the original empty cell on row 2255, column three. The results are shown in Table 15.

Re-basing the NS-SEC on SOC 2020

Project Summary

1. The Office for National Statistics (ONS) commissioned the University of Essex to undertake a rebasing of the National Statistics Socio-economic Classification (NS-SEC) to the Standard Occupational Classification 2020 (SOC 2020). The development of SOC 2020 was undertaken by a team from NatCen and the University of Warwick. The NS-SEC rebasing project had two phases: the first from April to September 2017 and the second from January 2018 to April 2020.

2. The main deliverable from Phase 1 was a paper exploring options for the collection of, or otherwise acquiring, the data required to enable a revision of the NS-SEC, with recommendations about designs and methods for how best to proceed. This phase involved consultation with leading academics and practitioners in the area and a review of the relevant contemporary literature as it relates to the NS-SEC. This was mainly done through a one-day workshop convened in Oxford on 8 June 2017. The main conclusions from Phase 1 were:

   • there were no existing data that fully met the requirements for the rebasing exercise
   • there were sufficient existing employment relations (ER) questions to draw on if new data were collected
   • we strongly recommended that new specialised data are collected by way of either a dedicated survey or through a suite of ER variables added to an existing large-scale survey
   • Workplace Employment Relations Study 2011 (WERS 2011), combined with a dual SOC-coded Labour Force Survey (LFS) quarter, could be used if no other alternative was possible and if the WERS data could be adequately recoded to SOC 2020
   • a Census 2021-specific derivation matrix is recommended and necessary for the best possible NS-SEC allocation given the changes to the census content (discussions of possible changes to the census questions and the impact on deriving the NS-SEC through a specially constructed census matrix were superseded by retaining a supervisory question on the census)

3. Following consideration of the Phase 1 report, the ONS decided to proceed with Phase 2 of the project with the aim of collecting new data through adding employment relations questions to an existing large-scale survey. An Expert Group meeting was held in Oxford on 9 April 2018 to consider specific ER questions and make recommendations to the ONS. The Expert Group recommended adding four additional questions to question one of the 2019 LFS that would also contain the Eurostat Ad Hoc Module on “Work organisation and working time arrangements” that had a number of questions relevant to the rebasing exercise. This LFS quarter would then be dual coded to the draft SOC 2020. This proposal was accepted by the ONS and approved by the LFS Steering Group. The questions were tested by the LFS team and revised in consultation with the NS-SEC rebasing team before going into the field.

4. The data were collected using the standard LFS methods. These data were used by the Classifications Unit of the ONS to add SOC 2020 occupations coded to the unit groups (OUGs). An extract of the whole LFS data was then made available for analysis in the ONS secure setting in London. These data have approximately 52,000 individuals coded to a SOC 2020 and SOC 2010 OUG, and approximately 51,000 have an employment status for use in the full NS-SEC derivation matrix. The Eurostat Ad Hoc Module and the additional ER questions was only asked of certain employees, so there were data on approximately 27,000 individuals. Of these, approximately 17,000 were “other employees” in the NS-SEC derivation matrix column seven (that is, not managers or supervisors).

5. The initial data analysis followed the methods used in the original construction of the NS-SEC based on SOC 2000. This approach and initial results were discussed at a NS-SEC Steering Group meeting convened on 17 September 2019 in Oxford. The Steering Group recommended that the ONS consider removing the operational sub-categories of the NS-SEC that were originally designed for continuity to the former classifications: Social Class based on Occupation (SC) and Socio-economic Groups (SEGs). The Steering Group also suggested exploring alternative methods of analysis to inform final allocation decisions.

6. As in the original construction of the NS-SEC, we note the limitations of using a limited set of ER variables and how allocation to classes was not wholly driven by statistical analysis of the LFS data. Therefore, other sources of information and considerations (such as face validity and continuity) were used. An important document was the SOC 2010 to SOC 2020 revisions produced by the SOC revision team. This traces the SOC 2010 OUGs (whole or in part) that form the SOC 2020 OUGs.

7. In terms of NS-SEC allocation and matrix construction, the main (non-exhaustive) groups of OUGs considered were unchanged, split and merged OUGs.

   Unchanged OUGs have remained unchanged from SOC 2010 to SOC 2020. Some may have changed their OUG number and/or their minor or major group but are substantively the same. Also included in this group were those OUGs that had only had minor changes to titles and descriptions. Unchanged OUGs that were moved into a new major group were given especial consideration.

   Split OUGs are when a single OUG was split into two or more new OUGs without parts of other OUGs being included. In this case, it was not assumed that all of the new OUGs would have the same NS-SEC allocation as the single OUG of origin.

   Merged OUGs are when two or more whole OUGs are merged into a new OUG without parts of other OUGs being included. This could be either (i) the original OUGs all having the same NS-SEC allocation, or (ii) the original OUGs having different NS-SEC allocations. The most common type of merging was part of an OUG with other parts of or whole SOC 2010 OUGs.

8. Analyses of the LFS data included descriptive statistics, scale construction based on factor analysis and replication of original methodology (see Annex 3 in full report), and comparison with statistical profiles drawn from NS-SEC based on SOC 2010. Under secure data protocol, small cell counts had to be redacted, so for a small number of OUGs there were no new data.

9. Many of the main tables on the distributions of the NS-SEC and levels of agreement between different derivation methods (that is, full compared with reduced) are included in SOC 2020 Volume 3 (Tables 2 to 5). Additional important tables only in the final report are included here:

   • Table S1: NS-SEC from full derivation method (SOC 2010 and SOC 2020) by sex.
   • Table S2: NS-SEC 7 classes full derivation method from SOC 2010 by from SOC 2020.

10. The levels of continuity between NS-SEC from SOC 2010 and from SOC 2020 by number of categories or classes are given here, with the seven analytic class version having 90.3% compared with 94% continuity from SOC 2000 to SOC 2010. It is worth noting that no new ER data on SOC 2010 OUGs were available for the 2010 rebasing.

    13 operational categories (L1 to L13) 89.31%
    7 classes (C1 to C7) 90.28%
    5 classes 96.69%
    3 classes 97.92%

11. From Tables S1 and S2, a number of changes can be seen in the distribution of NS-SEC analytic classes. The main off-diagonal cells in Table S2 (greater than 1% total sample) are: (i) increase in the size of analytic class 1 (C1) mainly because of movement from analytic class 2 (C2); (ii) notable movement from C1 to C2; and (iii) an increase in the size of analytic class 7 (C7) mainly because of movement from analytic class 6 (C6).

12. It is estimated that 62% of the movement from C2 to C1 is because of changes made in the derivation matrix based on the new ER data. This is mainly because of:

    • OUGs in major group 1 changed from a L5 or L5 profile for managers to L2 or L5 (that is, OUGs 1122, 1150, 1221, 1258 and 1259) or OUGs with different NS-SEC profiles under SOC 2010 being merged and now have a L2 or L5 profile (that is, OUG 1131); both of these result in managers in large organisations who were previously in L5 (C2) now being in L2 (C1)
    • OUGs in major group 2 changed from L4 (C2) to L3 (C1) (that is, OUGs 2422, 2453 and 2493)

13. It is estimated that 45% of the movement from C1 to C2 is because of changes in the derivation matrix based on new ER data and the remainder primarily because of changes in the SOC. Most of the changes are because of:

    • OUGs in major group 1 changed from a L2 or L2 profile for managers to L2 to L5 (that is, OUG 1111) or OUGs with different NS-SEC profiles under SOC 2010 being merged and now have a L2 or L5 profile (that is, OUG 1131). These both result in managers in small organisations who were previously in L2 (C1) now being in L5 (C2).
    • OUGs changed from L3 (C1) to L4 (C2) (that is, OUGs 2251, 2463 and 3532)
    • merging OUGs with different NS-SEC profiles under SOC 2010 (that is, L3 with L4, L3 with L7) with the final SOC 2020 allocation being in L4 (C2) (that is, OUGs 2126, 2141, 2329 and 3511)

14. It is estimated that 85% of the movement from C6 to C7 is because of changes in derivation matrix based on new ER data with OUGs changed from L12 (C6) to L13 (C7) (that is, OUGs 8111, 8131, 8145, 8222, 9211 and 9263).

15. Project timeline, main events, and documents:

    Phase	Year	Quarter	Event	Documents
    1	2017	Quarter 2	Academic and practitioner workshop	Workshop discussion paper
    		Quarter 3		Phase 1 Report*
    2	2018	Quarter 1
    		Quarter 2	Expert Group questions meeting
    			LFS Steering Group approval	Questions meeting discussion paper
    		Quarter 3
    		Quarter 4
    	2019	Quarter 1	LFS data collection
    		Quarter 2	LFS dual coded and data available for analysis
    		Quarter 3	Steering Group meeting	Steering Group discussion paper
    		Quarter 4
    	2020	Quarter 1		SOC 2020 Volume 3
    				Project Final Report

    Download this table

    .xls .csv

16. A full report of the rebasing project is available in PDF format upon request.

Standard Occupational Classification 2020 (SOC 2020)

Volume 1: Structure and description of unit groups
Volume 2: The coding index

Standard Occupational Classification 2010 (SOC 2010)

Volume 1: Structure and description of unit groups
Volume 2: The coding index
Volume 3: The National Statistics Socio-economic Classification rebased on SOC 2010

Standard Occupational Classification 2000 (SOC 2000)

Volume 1: Structure and description of unit groups
Volume 2: The coding index

The ESRC Review of Government Social Classifications

Published in 1998 jointly by the Office for National Statistics (ONS) and Economic and Social Research Council (ESRC), this report describes the development of the new socio-economic classification, which was the interim version of the National Statistics Socio-economic Classification (NS-SEC).

The National Statistics Socio-economic Classification (NS-SEC): Origins, Development and Use

A complete description of the development of the NS-SEC, including its rebasing on SOC 2000. Published in 2005.

The National Statistics Socio-economic Classification (NS-SEC): User manual

A user manual for the NS-SEC, including derivation tables from SOC 90 and SOC 2000. Published in 2005.

Economic and Social Research Council (ESRC)

The ESRC is part of UK Research and Innovation (UKRI), a new organisation that brings together the UK’s seven research councils, Innovate UK and Research England.

Household Reference Person(HRP)

The HRP is the person within the household who is chosen to characterise the household’s social position. The official definition was introduced in 2001.

International Standard Classification of Occupations 2008 (ISCO 08)

ISCO 08 is the classification of occupations developed by the International Labour Office and revised in 2008.

National Statistics Socio-economic Classification (NS-SC)

The NS-SEC is a classification, with a defined conceptual basis, that has been developed to replace the versions based on Standard Occupational Classification 2000 (SOC 2000) and SOC 2010.

Occupation coded to the unit groups (OUG)

An OUG is a group within the most detailed tier of the occupational classification, more specifically one of the 412 unit groups of the SOC 2020.

Social Class based on Occupation (formerly Registrar General’s Social Class) (SC)

The SC is a scale for classifying people into five groups (represented by Roman numerals), one subdivided. The composition of the classes brought together, as far as possible, people with similar levels of occupational skill. The allocation of occupations varied when Social Class was rebased on the revised occupational classification with the intention of preserving the gradient rather than literal continuity. It was derived from OUG and employment status. The final version was based on SOC 90.

Socio-economic Group (SEG)

SEGs are a classification aimed to bring together people with similar social and economic status into 17 groups, three subdivided. It was derived from OUG, employment status and size of establishment. The final version was based on SOC 90.

Standard Occupational Classification 2000 (SOC 2000)

SOC 2000 was the UK’s official occupational classification, which was revised, updated and published in June 2000.

Standard Occupational Classification 2010 (SOC 2010)

SOC 2010 was the UK’s official occupational classification, which was revised, updated and published in June 2010.

Standard Occupational Classification 2020 (SOC 2020)

SOC 2020 was the latest edition of the UK’s official occupational classification, which was revised, updated and published in February 2020.