Summary information

Study title

Derivation Matrices for the Former Official Measures of Social Class, 2000, 2010 and 2020

Creator

Pevalin, D., University of Essex, Department of Sociology
Rose, D., University of Essex, Institute for Social and Economic Research

Study number / PID

8965 (UKDA)

10.5255/UKDA-SN-8965-1 (DOI)

Data access

Open

Series

Not available

Abstract

Abstract copyright UK Data Service and data collection copyright owner.


The two former official measures of social class - Social Class by Occupation (SC), previously known as Registrar General's Social Class (RGSC), and Socio-economic Groups (SEG) - were discontinued in 2001 when the National Statistics Socio-economic Classification (NS-SEC) was adopted as the sole official measure of social class in the UK.

Derivation Matrices for the Former Official Measures of Social Class, 2000, 2010 and 2020 provides derivation matrices for SC and SEG from the Standard Occupational Classifications 2000, 2010, and 2020 after their official discontinuation to enable their use in longitudinal data and comparative analyses.

Further information is available in the publications detailing the 2010 and 2020 work.


Main Topics:

Derivation matrices for SC and SEG are available from the Standard Occupational Classifications for  2000, 2010, and 2020. These derivation matrices can be used on any data with the relevant occupational data.

Methodology

Data collection period

Not available

Country

United Kingdom

Time dimension

SOC 2000 matrices: 2001 - 2010. SOC 2010 matrices: 2011 - 2020. SOC 2020 matrices: 2021 on

Analysis unit

Occupational Unit Group

Universe

Derivation matrices can be used on data containing the relevant occupational information

Sampling procedure

No sampling (total universe)

Kind of data

Numeric

Data collection mode

Compilation/Synthesis

Funding information

Grant number

H501265031 (David Rose)

Grant number

SRG1920/100096 (David Pevalin)

Grant number

SG110232 (David Pevalin)

Access

Publisher

UK Data Service

Publication year

2022

Terms of data access

  The Data Collection is to be made available to any user without the requirement for registration for download/access under a Creative Commons Attribution 4.0 International Licence.