| Project Detail |
Integrating genetics into social-sciences to better understand the origins of inequality
Funded by the Marie Sklodowska-Curie Actions programme, the ESSGN project brings together an interdisciplinary group of academic experts and non-academic partners to train the next generation of social scientists in the responsible use of genetic data. The aim is to answer a key research question: to what extent do inequalities in life chances arise from genetic variation, environmental factors, and their interplay? The project will exploit Europe’s comprehensive multigenerational databases for the separation of direct genetic effects from parental genetic and socioeconomic factors that influence the rearing environment. The trainees will employ causal inference methods used in econometrics and statistics to estimate the extent to which environments cushion or exacerbate genetic differences.
The European Social Science Genetics Network (ESSGN) brings together seven academic beneficiaries with a shared interest in social science genetics, i.e. in incorporating genetic information to improve our understanding of age-old questions in the social sciences, such as the origins of inequality, the ‘nature versus nurture’ debate, and the extent to which the interplay between environments and genes is important in shaping individuals’ lives. The consortium consists of an interdisciplinary group of academics, as well as seven non-academic partners committed to using data science to address inequalities in life chances. There is an urgent need for training in social science genetics due to recent technological advances in genetics, the intricacies of using genetic data, and the growing availability of such data in surveys traditionally studied by social scientists. Our aim is to train the next generation of social scientists in the responsible and technically correct use of genetic data and in objective communication about what can and cannot be learned from working with genetic data in the social sciences.
The project will go beyond the state-of-the-art (i) by using Europe’s most comprehensive multigenerational databases to separate direct genetic effects from parental genetic and socio-economic factors that shape the rearing environment; and (ii) by exploiting the large toolbox of causal inference methods used in econometrics and statistics to estimate the extent to which environments causally protect individuals with genetic disadvantages. We will (1) analyse to what extent genetic (‘nature’) and environmental (‘nurture’) factors contribute to equality of opportunity and intergenerational mobility, and (2) establish how nature and nurture jointly shape inequalities in life chances. As such, our programme of research provides novel and exciting opportunities to social scientists to deepen our understanding of how inequalities in life chances are shaped. |
