Events

Harmful care, careful harm: relational entanglements in migration

Virtual , Australia

University of Sydney

This timely event will bring together experts from the diverse corners of the field of migration studies to consider the complex and dynamic relationship between care and harm in international migration. Scholars of migration have documented the multivarious forms of harm that arise from the systems, institutions and interactions surrounding the movements of people across borders. Researchers have also explored the many forms of local and transnational care that are created by, or persist despite, international migration. In this event, we explore the ways care and harm are interwoven, interdependent and mutually constitutive in diverse migration contexts. Relationships of care (for example, between migrants or between migrants and ‘allies’ in civil society) may arise in response or resistance to the harms imposed by exploitative policies and practices. Equally, policies and practices that appear to be ‘caring’ may reproduce, obscure or naturalise harm, at times perpetuating the very inequalities and injustices they purport to address. Grounded in diverse settings including immigration detention, aged care, temporary labour migration schemes, the family home, and media platforms, the speakers will present brief talks drawing on their specialist research. The speakers will then come together for a panel discussion of harmful care, careful harm, and the imperative to pursue more meaningful forms of care […]

Free

An introduction to Computational Social Science

Virtual , Australia

University of Melbourne

Computational social science (CSS) frequently uses Agent-based models (ABMs) to model social phenomena. ABMs are ‘bottom-up’ representations of individuals (computational agents) who exist within a society of other agents and who interact on a local scale based on sets of rules that govern their behaviour. When used like this, ABMs are attempts to create ‘Artificial Societies’ that we can study. The advantage of creating artificial societies is that imagined policies or interventions can then be made within these representations and the outcomes of those policies can be observed prior to implementation in the real world. The models can be anywhere between instructive or predictive, with the sophistication and detail of models often geared toward their purpose in this regard. In general, the most interesting models are those that try to replicate the generation of a large-scale social phenomenon when the mechanisms that create that phenomenon are currently unknown or contested (e.g., crowd behaviour, social behaviour, health behaviour, political behaviour, etc.). This session will introduce the audience to example agent-based models used in Computational Social Science and show how they can be used to augment existing research agendas, test theory, and trial simulated policies. We'll provide some very brief introductory 'how […]

Free