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My name is Ji MA (马季; first name pronounces “G”), Assistant Professor in Philanthropic and Nonprofit Studies at the Lyndon B. Johnson School of Public Affairs at the University of Texas at Austin. I’m also an affiliated faculty member of the Center for East Asian Studies and the School of Information at UT Austin.

  • Office hour: Friday 2-4pm (2023 spring semester)
  • Office: SRH3.324, +1-512-232-4240
  • Email:
  • Elsewhere: @Google Scholar | @GitHub

I study philanthropy, civil society, and the nonprofit sector from the following perspectives (CV | recent papers):

Civil society sectors in authoritarian countries. Before entering academia, I co-founded a grassroots nongovernmental organization (NGO) focused on improving the quality of education in rural China. While serving as its inaugural executive director, I was puzzled and curious about the appropriate roles of NGOs in an authoritarian country and how the state and NGOs should interact. This curiosity motivated my doctoral training and dissertation: why do civil society sectors exist in authoritarian countries, and how do they interact with states? This line of research has appeared in Scientific Data, Social Networks, Nonprofit Management & Leadership, Journal of Chinese Political Science, Voluntas, and Chinese Public Administration Review.

Intellectual growth in nonprofit and philanthropic studies. Developing a cohesive and substantial body of knowledge is at the core of all academic disciplines. My second research area focuses on my research field’s intellectual growth and knowledge production. I became interested in this research line while I was in my doctoral program, where we would often ask questions such as “Is there an emerging research field of nonprofit and philanthropy?” and “Will we form a new discipline or stay as a research field?” These types of questions are typical and critical to all emerging and interdisciplinary research areas. This line of research has appeared in Voluntas and Nonprofit and Voluntary Sector Quarterly.

Computational social science methods. Social scientists are well trained in conventional qualitative and quantitative methods, but an emerging set of methods commonly known as “computational social science” is novel and exciting to researchers in all social science disciplines. Although computational social science has been coined for a while, many scholars still treat it as a buzzword instead of a new methodological paradigm. Given its growing importance in evidence-based policymaking, my most recent research line advances computational social science methods and has appeared in Nonprofit and Voluntary Sector Quarterly and Voluntas.