BigMig: Digital and non-digital traces of migrants in Big and Small Data approaches to human capacities
Funding Institution: National Science Center Poland, Program OPUS 19, duration 4 years (2021-2024).
Our whole lives we have been raised with the notion that “international journeys educate” and through undertaking these opportunities we are able to open up our minds to the world. The whole idea of the 19th Century Grand Tour was to take tours to the principal cities and places of interests in Europe, formerly said to be an essential stages of education of youth with ‘good birth’ and ‘fortune’. In the 20th and beginning of the 21st Century a gap year has been popular among middle class students who from Europe and USA started mainly travelling to Asia; while previously they were mostly travelling to Europe and USA respectively. It is different however for Central and Eastern Europeans. They just go for work and additionally they can develop their human capacities and eventually transfer them home. Can we say that international migration is a school of life? What distinguishes migration from other „school of life” experience? During changing cultural contexts we learn things which were never taught at school about: self, others, relationships, work. Migrants can be seen as onlookers who can through their experience bring perspective which muted in familiar context. It is different to watch the world through a keyhole, and differently through an open door. This BigMig project develops an interdisciplinary approach, drawing on migration studies, sociology, psychology and social informatics. It makes use of Big and Small Data analysis. BigMig integrates these disciplines and methodologies with a common focus on migrant selectivity, the impact of migration on human capacities, and their relations with social remittances and carriers. The main aims of this project are to understand: (1) the selectivity of international migrants by comparing the personality traits, as well as the human and social capital of movers and stayers (Big Data); (2) the impact of migratory experience on formation and enhancement of human capacities (international comparative survey); and (3) social remittances as individual and collective outcomes of migration-patterned human capacities (multi-sited ethnography with asynchronous interviews).
The BigMig project develops an interdisciplinary approach, drawing on migration studies, sociology, psychology and social informatics. It makes use of Big Data and Small Data analysis. BigMig integrates these perspectives and methodologies into a common focus on migrant selectivity, the impact of migration on human capacities, and their relationship with non-financial transfers (social remittances).
The project addresses three fundamental issues of international mobility:
(1) Who migrates and who stays in terms of personality traits in the reference to socio-demographic characteristics?
(2) What is the impact of international migration on human capacities?
(3) How do migration-patterned human capacities produce social remittances?
The project consists of five sub-projects: (1) Developing a new approach to human capacities and international migration; (2) Understanding migrant selectivity by combining sociological and psychological approaches (Big Data); (3) Understanding the interconnection between human capacities and international migration (international comparative survey); (4) Understanding social remittances, their carriers and geographies (multi-sited ethnography with asynchronous interviews); (5) Synthesis – connecting theoretical and empirical outcomes.
This project is innovative in at least four ways. First, it is the first multidimensional study of migrant selectivity in Big Data. It considers both human and social capital parameters but also personality traits in the digital footprints of both movers and stayers. Second, it will create a taxonomy of human capacities, including capacities patterned by international migration. Third, it integrates concepts of migrant selectivity, human capacities and social remittances into a single ontological guideline. Fourth, it links various strands of literature and combines Big Data and Small Data analyses.