New paper explores measure of socio-cultural origins
A paper evaluates the development of a new ancestry item in ESS Round 7 and explains how the findings have been used to improve the item for future rounds of the survey.
The paper - Developing a Measure of Socio-cultural Origins for the European Social Survey - has been published by GESIS - Leibniz Institute for the Social Sciences - based in Mannheim, Germany.
It explains how an ancestry item was included in the ESS for the first time in Round 7 (2014/15) as a person’s ethnic background can help predict a range of social attitudes and behaviours.
To discover self-reported family origins or descent, respondents in each country were asked about their ancestry using a showcard displaying country-specific national, ethnic or other cultural groupings.
Answers were then harmonised for comparative analysis by recoding into a newly developed European Standard Classification of Cultural and Ethnic Groups (ESCEG).
The paper also makes some suggestions on how to code derived variables from ESCEG for statistical analysis.
The paper includes a thorough evaluation of the ancestry item’s performance in Round 7 and the reasons behind its inclusion, with some modifications, as a permanent addition to the ESS core questionnaire from Round 8 (2016/17) onwards.
The evaluation concluded that the item worked well across ESS countries and generated meaningful and innovative data on respondents’ socio-cultural origins, especially by taking sub-national groups into account, in contrast to existing measures such as ‘country of birth’.
The paper also suggests further improvements to translation guidelines, revisions to the harmonised code-frame, and more consistent treatment of sub-national socio-cultural groups, which were already implemented in ESS round 8.
The evaluation report will be of interest to researchers carrying out substantive analyses using the new ESS ancestry item and survey methodologists interested in lessons learned for the development of cross-national questionnaires and classifications.
The paper was written by Anthony Heath (University of Oxford), Silke Schneider (GESIS) and Sarah Butt (City, University of London).
GESIS is a member of the ESS Core Scientific Team and fulfils major tasks in sampling, questionnaire translation, fieldwork planning and monitoring. Dr. Angelika Scheuer of GESIS is one of four ESS Deputy Directors.