Educational attainment, field of education and training, employment status, occupation and industry are core variables in many surveys, as are the size and intensity of social networks. However, their measurement – especially in cross-national and cross-cultural surveys – is cumbersome, not sufficiently standardized and often expensive.
Already in national surveys, the coding of occupations is very resource-intensive. In migrant surveys, the question arises of how to account for migrants’ foreign educational qualifications. In cross-national surveys, the social context of many different societies needs to be taken into account, and substantial economies of scale can be achieved by using common questions and classifications whenever possible.
We will offer a cross-country harmonised, fast, high-quality and cost-effective questionnaire and coding module for these variables. The questions adapt to the country where a survey is held, i.e. the language(s) used in this country. Respondents may also choose to respond in a different language though. The education questions also adapt to the country a respondent was educated in.
The module uses a large multi-lingual dictionary with tens of thousands of entries about job titles and industry names. Additionally, the module includes country-specific, structured lists of educational qualifications and employment status categories, as well as general lists of fields of education and training. For all these variables, we provide up-to-date codes according to standard international classifications.
It thereby facilitates cross-national surveys, and serves as an infrastructure reaching out to a global audience. We will offer the questionnaire module in many languages, including the most spoken language groups outside the EU28 area (including Russian, Mandarin, Arabic, Hindi and Bahasa, a total of 47 languages servicing 99 countries) .
Interested? Go to survey implementation.
Schneider, S. L., Joye, D., Wolf, C., & Surveys, C. (2016). When Translation is not Enough: Background Variables in Comparative Surveys. In C. Wolf, D. Joye, T. W. Smith, & Y.-C. Fu (Eds.), The SAGE Handbook of Survey Methodology (pp. 288–307). Los Angeles.