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Research

Research

Research

Summary

This project seeks to understand the migration dynamics of highly educated migrants. Using the "intellectual migration" framework and empirically connecting China and the United States, the research aims to understand the who, why, and where, of intellectual migration and examine how country-specific policies impact intellectual migration. This project will contribute to ideas about the movement of people between countries and what motivates them, and adds a geographical dimension to the understanding of the migration of the highly educated. This project is significant as China has been a main source of international students and foreign-born professionals in the U.S. in recent decades. A better understanding of the dynamics of these highly educated migrants can inform policies that facilitate mutually beneficial intellectual migration. Findings will help US national, local and institutional leaders to retain/build a diverse US-trained workforce of different backgrounds and in different fields which enhances local, regional, and national economic development.

This project will be conducted by an interdisciplinary and international team of researchers and employs a multi-level and multi-methods approach, integrating surveys and in-depth interviews with secondary data analysis and GIS mapping to study a cross-sectional sample of three groups of migrants: pre-international-migration students in China, China-born international students and faculty in the U.S., and China-born and US-trained faculty and professional returnees in China. Results from this study are expected to advance theory on mobility and transnationalism, and will add a geographical dimension to the understanding of the migration of the highly educated. Findings will facilitate further research to conduct comparative analysis with other major highly-educated migrant sending and receiving locations in the future.

Funding

National Science Foundation, Division of Behavioral and Cognitive Sciences

Timeline

June 2017 — November 2020