Scottish Graduate School of Social Science Summer School

Summer School June 2012

The Scottish Graduate School of Social Science (SGS) is delighted to unveil the programme for its first annual Summer School, to be held at the University of Edinburgh in June 2012. The Summer School will offer a wide range of exciting events which run either for a full or half day, and each evening affords the opportunity to attend a unique plenary event, bringing together speakers from Scotland with international speakers across the social sciences. 

Full Programme

Student Registration Form  

Summary Programme 

Day(s)	Event
13-15 June	AQMEN Training: Multilevel Modelling
Monday 18 June	Advanced Workshop in Finance & Market-based Accounting Research
	Politics & International Relations Workshop
	Public Policy Challenge Workshop: Making an Impact with Social Science
	NVivo Software Demonstration [afternoon event]
	Plenary: David Bell "The Peculiar Economics of Scottish Independence" & Patrick Jackson "Three Boundaries to Loosen in the Global Study of World Politics"
Tuesday 19 June	Business & Management with Prof Derek Pugh
	Human Geography: Contemporary Research Themes
	Information Science Doctoral Colloquium (iDocQ)
	Language-based Area Studies: Area Studies & Translating Cultures
	Social Anthropology: Creative Practices & Social Scientific Research
	NVivo Software Lab-based Training
	Plenary: Tim Ingold "Knowing from the Inside" & TBC
19-20 June	Secondary Data Analysis Lab-based Training
Wednesday 20 June	Criminology & Socio-Legal Studies Research Students Workshop
	Quantitative Methods in Psychology & Economics
	Exploring Knowledge Exchange
	Information Science: Discourse Analysis [morning event]
	Planning Your Academic Career: What makes a successful academic? [morning event]
	Social Work: The Impact of Research [afternoon event]
	NVivo Software Demonstration [afternoon event]
	Plenary: Liam Delaney "Stress & Financial Decision Making" & Mike Burton "What are we so bad at face recognition?"
21-22 June	AQMEN Training: Regression Modelling for Categorical Data