9-15 September 2024

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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

Doctors with a difference? Social science insights on widening participation in medicine: Australian, Canadian and UK perspectives

Virtual , Australia

University of Newcastle

Medical schools have historically been prestigious and exclusive institutions, filled with students who come from much wealthier families than average. Elaborate and competitive selection processes and the costs involved in applying to medicine are barriers to students from low-income backgrounds, as well as the perception that medicine is out of reach. For over two decades, widening participation initiatives have focused on encouraging underrepresented groups to apply to medical school, including low-income and ‘first-in-family’ students whose parents are not university-educated, based on the assumption that a more diverse medical profession will lead to better care and health outcomes for patients. The success of these initiatives has largely been measured by statistics showing increased application and admission rates of low-income/first-in-family students. Much less attention has been paid to the experience of these students once they enter medical school, and even less is known about their experiences, aspirations and trajectories as doctors. Are there residual forms of inequity that persist within medical schools, and beyond? How do low-income/first-in-family students see themselves relating to the medical profession and to patients? This webinar presents findings from three countries on the experiences of medical students and doctors who are the first in their family to attend […]

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