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PHOENIX: Human Mobility, Global Challenges and Resilience in an Age of Social Stress - Social tipping points and climate mobilities

Grant number: 23/13182-1
Support Opportunities:Scholarships in Brazil - Post-Doctoral
Effective date (Start): December 01, 2023
Effective date (End): November 30, 2025
Field of knowledge:Interdisciplinary Subjects
Acordo de Cooperação: Belmont Forum
Principal Investigator:Rafael de Brito Dias
Grantee:Tiago Balieiro Cetrulo
Host Institution: Faculdade de Ciências Aplicadas (FCA). Universidade Estadual de Campinas (UNICAMP). Limeira , SP, Brazil
Associated research grant:22/09743-5 - PHOENIX: human mobility, global challenges and resilience in an age of social stress, AP.R


This postdoctoral research is linked to the PHOENIX project, which is a study of how Global Changes - including environmental and climate changes, demographic changes, changing consumption patterns, energy and land-use, developments in the politics of food and mental health, and socio-cultural transformations - impact mobility. Specifically, PHOENIX undertakes data modeling of social tipping points by utilizing GIS techniques and synthesizing existing geographical, earth science and longitudinal datasets. PHOENIX also apply a Governance of crisis approach to macro, meso and micro-levels to understand how diverse policy areas ranging from sustainable development and disaster risk reduction to health, food, and climate change might be bridged with larger policy frameworks to understand and predict mobility patterns. The project conducts two human-centric case studies of social tipping points: (1) food security and belonging and (2) cultural survival and resilience. These case studies provide new ways of looking at how climate (im-)mobilities and their social tipping points are shaped by socio-cultural contexts and the psycho-social health of populations. Drawing on natural sciences like climate and sustainability studies and on the social sciences of political science, sociology, psychology, economics and anthropology, the project adds to the interdisciplinary diagnostic and prognostic toolbox of Global Change and mobility as well as vulnerability and resilience assessments.The Project is organized in five integrated clusters. The postdoc will assist in the interaction of the UNICAMP team with the different clusters but will mainly develop activities related to Cluster 1 (Data collection and analysis for modeling of Social Tipping Points). Cluster 1 is to provide a coherent information basis, to create a common analytical framework, and to facilitate integration of all works of the project, a common database and modeling tool will be developed based on GIS technologies. Related information and data for factors influencing migration will be identified and compiled. These include but are not limited to the following factors: 1) Environmental change directly influencing livelihoods; 2) indicators for governance in terms of designed development policies targeted by race, ethnicity and gender, institutions and rule of law, and inadequate service delivery; 3) Economic drivers; 4) Social or cultural drivers; 5) Use of new ICT that enables potential migrants to build networks and facilitate the migration process; 6) Political conflicts caused by historical discords, social injustices or economic inequalities. Since most of these factors operate on different levels and scales, it is important to have a nested approach: from the local to the international and vice-versa. The collected data will enable team members of the Project to jointly, objectively, and systematically characterize the situations at hand, model the relationships among the influencing factors, formulate and test hypotheses, and eventually draw conclusions. The main tasks of postdoc will include: a) developing a database construction plan; b) Collection of data and database building, involving the compilation of relevant data from different disciplinary perspectives and using advanced multivariate analysis tools, especially those related to climate change research, to address the complex relationships between heterogeneous factors and quantify their effects on climate-driven migration; and, c) Identify relevant climate variables for understanding migratory phenomena, allowing the identification of patterns and connections between different variables.

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