Chao Shi

Chao Shi

Higher Degree by Research Candidate

School of Social Sciences

Faculty of Arts, Business, Law and Economics

Chao Shi is a PhD candidate at the Department of Geography, Environment and Population. His research interests include migration and development, social indicator research, and qualitative and quantitative methods. HIs thesis examines how Chinese business migrants integrate and contribute to Australian economy and society. Before starting graduate school, Chao earned a B.A. in Chemical Engineering from Dalian University of Technology and M.A. in Economics at Peking University.

Migration and development; Business migrants; Social indicator research; Quantitative and Qualitative methods. 

  • Appointments
    Date Position Institution name
    2019 - ongoing Research Assistant The University of Melbourne
    2018 - ongoing Teaching Assistant University of Adelaide
    2017 - 2017 Intern and Consultant International Labour Organization
    2016 - ongoing Research Assistant Duke University
    2016 - 2016 Research Assistant Cornell University

  • Language Competencies
    Language Competency
    Chinese (Mandarin) Can read, write, speak, understand spoken and peer review
    English Can read, write, speak, understand spoken and peer review

  • Education
    Date Institution name Country Title
    2017 University of Adelaide Australia PhD
    2014 - 2017 Peking University China Master
    2009 - 2013 Dalian University of Technology China Bechalor

  • Research Interests
    Demography Migration Sociological Methodology and Research Methods

  • Journals
    Year Citation
    2021 Shi, C., & Land, K. C. (2021). The Data Envelopment Analysis and Equal Weights/Minimax Methods of Composite Social Indicator Construction: a Methodological Study of Data Sensitivity and Robustness. Applied Research in Quality of Life, 16(4), 1689-1716.
    DOI Scopus3 WoS2
    2017 Shi, C., & Qiao, X. (2017). Age-Period-Cohort Effects on Life Satisfaction in China. Population and Development, 23(4).

Australian Government Research Training Scholarship

Charles and Frank Fenner Grant

Global Learning Grant

Walter Dorothy Duncan Trust

Funding from school of social science for fieldwork

Funding from school of social science for conference

 

Teaching Assistant in Statistical Software

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