Discovery Early Career Researcher Award - Grant ID: DE240100232
Funder
Australian Research Council
Funding Amount
$431,704.00
Summary
Demographic and life course drivers of social cohesion. The project aims to understand the individual and community-level drivers and pressures on social cohesion in Australia. It is expected to generate new knowledge on how and why individuals become more or less engaged in their communities and society over time by combining information from multiple existing data sources. Expected outcomes of the project include the creation of analytical tools for measuring the dynamics of social cohesion, h ....Demographic and life course drivers of social cohesion. The project aims to understand the individual and community-level drivers and pressures on social cohesion in Australia. It is expected to generate new knowledge on how and why individuals become more or less engaged in their communities and society over time by combining information from multiple existing data sources. Expected outcomes of the project include the creation of analytical tools for measuring the dynamics of social cohesion, helping to bridge the gap between current theories and data. This should provide significant benefits in identifying threats and opportunities, and informing community and government initiatives, to strengthen and maintain social cohesion and the collective well-being of communities and Australia.Read moreRead less
The demographic consequences of extreme weather events in Australia. This project aims to understand how extreme weather events are likely to affect Australians’ residential mobility choices, using machine learning techniques to provide the first overview of the impact of natural hazards on where Australians are likely to live in the future. Expected outcomes include an understanding of the influence of extreme weather events on changes in population numbers and composition. Expected benefits in ....The demographic consequences of extreme weather events in Australia. This project aims to understand how extreme weather events are likely to affect Australians’ residential mobility choices, using machine learning techniques to provide the first overview of the impact of natural hazards on where Australians are likely to live in the future. Expected outcomes include an understanding of the influence of extreme weather events on changes in population numbers and composition. Expected benefits include an understanding of how environmental drivers are influencing internal migration in Australia, enabling better planning for service provision and economic growth.Read moreRead less
China’s changing internal migration: patterns, causes, policy implications. China’s massive internal migration is no longer simply rural–urban and circular but highly diversified. The project aims to unravel that transition: its patterns, causes, and effects. Using 2020 census data and major longitudinal datasets, a China variant of Zelinsky’s classic mobility transition theory will be developed and deployed to identify underlying mechanisms. Among expected outcomes are powerful methods for asse ....China’s changing internal migration: patterns, causes, policy implications. China’s massive internal migration is no longer simply rural–urban and circular but highly diversified. The project aims to unravel that transition: its patterns, causes, and effects. Using 2020 census data and major longitudinal datasets, a China variant of Zelinsky’s classic mobility transition theory will be developed and deployed to identify underlying mechanisms. Among expected outcomes are powerful methods for assessing spatio-temporal migration patterns and causes, applicable to many economies especially in the Asia–Pacific. Benefits should include a new evidence base for migration and related urban–rural policy in China; and for Australia, policy inputs to improve prosperity through better relations with our biggest trading partner.Read moreRead less