Learned Academies Special Projects - Grant ID: LA170100011
Funder
Australian Research Council
Funding Amount
$170,000.00
Summary
The use of big data for social policy: benefits and risks. This project aims to investigate the benefits and risks of using ‘big data’ and analytics for social policy. Drawing on documentary sources and interviews with experts and stakeholders, the project will use five case studies to examine the capability, underlying assumptions and possible impacts of such techniques. The project will bring together a multi-disciplinary team of social and data scientists to identify the infrastructural, tech ....The use of big data for social policy: benefits and risks. This project aims to investigate the benefits and risks of using ‘big data’ and analytics for social policy. Drawing on documentary sources and interviews with experts and stakeholders, the project will use five case studies to examine the capability, underlying assumptions and possible impacts of such techniques. The project will bring together a multi-disciplinary team of social and data scientists to identify the infrastructural, technical, and social, ethical and legal issues that need to be addressed. The project will define key issues for future research, promote collaboration between the social sciences and big data disciplines, while creating opportunities for building capability for researchers in the social sciences. Read moreRead less
Creating pathways to child wellbeing in disadvantaged communities. This project aims to test, in nine disadvantaged communities, a model for action that blends new human and digital resources to support respectful, data-driven collaborations between schools, families and community agencies.
The project expects to generate new knowledge in the area of translational prevention science about how to influence risk and protective factors for child wellbeing in a cost-efficient manner and at a scale ....Creating pathways to child wellbeing in disadvantaged communities. This project aims to test, in nine disadvantaged communities, a model for action that blends new human and digital resources to support respectful, data-driven collaborations between schools, families and community agencies.
The project expects to generate new knowledge in the area of translational prevention science about how to influence risk and protective factors for child wellbeing in a cost-efficient manner and at a scale within existing service systems. Project benefits should include a methodology for achieving lasting improvements in child wellbeing, behaviour and school success.
Read moreRead less