The Applied Quantitative Methods Network (AQMeN) was a research centre funded by ESRC from 2013-2017 to develop a dynamic and pioneering set of projects to improve our understanding of current social issues in the UK and provide policy makers and practitioners with robust, independent, research-based evidence to build a better future.
AQMeN had three primary strands of research involving a multidisciplinary team of researchers from the UK and abroad :
• Crime and Victimisation – led by Professor Susan McVie (University of Edinburgh) and involving Professor Brian Francis, Dr Les Humphries, Professor Jon Bannister, Dr Paul Norris, Professor Paul Nieuwbeerta, Dr Ellie Bates and Dr Rebecca Pillinger together with doctoral students Sara Skott and Ben Matthews
• Education and Social Stratification – led by Professor Cristina Iannelli (University of Edinburgh) and involving Professor Lindsay Paterson, Professor Adam Gamoran, Professor Marita Jacob, Professor Emer Smyth, Dr Selina McCoy, Dr Markus Klein and Dr Adriana Duta together with doctoral students Dafni Dima and Carla Cebula
• Urban Segregation and Inequality – led by Professor Gwilym Pryce (University of Sheffield) and involving Professor Nick Bailey, Dr Nema Dean, Dr Duncan Lee, Dr Stephan Heblich, Professor Chris Timmins and Dr Jonathan Minton together with doctoral students Johanna Jokio and Cathy Zhu.
AQMeN also developed five additional, one-year projects that were supported by ESRC investment. Three of these projects were part of the ESRC’s Future of the UK and Scotland programme of work that aimed to address issues around the future of Scotland and aimed both to inform the debate in the run-up to the referendum and to assist in planning across a wide range of areas which were likely to be affected by the outcome of the vote, whether for independence or the Union.
As of October 2017, AQMeN training in quantitative methods will be delivered through the School of Social and Political Science at the University of Edinburgh. Visit www.aqmen.ac.uk to find out more.