‘Networking for Global Justice’, which was organised by Leeds Social Sciences Institute in conjunction with the Inequalities Research Network, Centre for Global Development and the Cities Theme, took place on Wednesday 15th November 2017.
It brought together academic researchers from University of Leeds, Leeds Beckett University and Newcastle University to focus on social and economic inequalities in the context of the Sustainable Development Goals and Global Challenges Research Fund.
The aim of the workshop was to explore the potential benefits and value of mapping and linking existing research networks aimed at reducing inequalities in order to develop critical mass, heighten the profile of research or explore ways in which we might collectively engage with global development research opportunities and build capacity.
The workshop provided an opportunity for participants to hear from academics who are conducting research on inequalities in developing countries, including insights into the challenges and benefits of establishing international collaborations with external partners.
Presentations were given by:
Professor Mike Savage, Professor of Sociology, London School of Economics
View Mike’s presentation
Dr Ghazala Mir, Associate Professor, University of Leeds
View Ghazala’s presentation
Dr Helen Elsey, Lecturer in Public Heath, University of Leeds
View Helen’s presentation
Dr Chris Paterson, Senior Lecturer in International Communication, University of Leeds
View Chris’s presentation
Professor Karen Lucas, Professor of Transport & Social Analysis, University of Leeds
View Karen’s presentation
Two ‘World Café’ sessions were held and provided the opportunity for participants to join in and contribute to discussions relating to the following topics:
- inequality themes
- mapping networks
- joining forces
The next steps emerging from the workshop were to explore the potential for a Postgraduate event as well as a collaborative event across a greater number of Universities.
The notes from the workshop can be accessed here: