Past research has included a study of women in science with Professor Judith Glover of Roehampton University and a study of stress among the police with Professor Jennifer Brown of Surrey University. More recently, she has been involved with several Defra/ Environment Agency projects (with Dr Kate Burningham) including ‘Flood warning for vulnerable groups’(Defra / Environment Agency, Flood and Coastal Erosion Risk Management R&D Programme, R&D Report W5C-018 (2005)) and another entitled, ‘Public Response to flood Warning’, (Defra / Environment Agency, Flood and Coastal Erosion Risk Management R&D Programme, ID number W5E, Final Report pending).
In addition, during December 2004-March 2005, she was involved with a consortium of researchers led by Professor Gordon Walker of Lancaster University on another Agency project, “Addressing Environmental Inequalities”. Jane was also co-holder on an ESRC Methods Programme project (2002-2005) exploring the integration of quantitative and qualitative methods in an investigation of the concept of vulnerability.
During 2007-8 Jane acted as a consultant on an DEFRA/EA contract awarded to Collingwood Environmental Planning (CEP) entitled “Supporting the Development of a Social Science Strategy for the Flood and Coastal Erosion Risk Management (FCERM) R&D Programme (DEFRA/EA)”.
Jane is co-Director of the ESRC-funded QUIC (Qualitative Innovations in CAQDAS) Node of the National Centre for Research Methods (NCRM). This programme of research commenced in September 2008 and will run for three years. The QUIC Node will explore qualitative software support for integrating qualitative and quantitative data in mixed methods research, for the analysis of Access Grid multi-stream visual data and for the integration of geo-referenced data within qualitative analysis.
Her research primarily uses secondary analysis of large government data sets including the 1991 and 2001 Census area statistics, the British Social Attitude Survey (BSA), the Labour Force Survey (LFS), the Universities Statistical Records (USR), and the National Child Development Study (NCDS). Her particular interest is in the use of GIS software in mapping environmental risk and the social distribution of environmental inequality.
Jane teaches modules in computing and quantitative methods on both the undergraduate and postgraduate degree programmes and holds an advanced methods workshop in GIS techniques.
This article considers the contribution that qualitative software can make to ‘opening up’ Open-Ended Question (‘OEQ’) data from surveys. While integrating OEQ data with the analysis of fixed response items is a challenge, it is also an endeavour for which qualitative software offers considerable support. For survey researchers who wish to derive more analytic value from OEQ data, qualitative software can be a useful resource. We profile the systematic use of qualitative software for such purposes, and the procedures and practical considerations involved. The discussion is illustrated by examples derived from a survey dataset relating to environmental risk in the UK.
This paper explores the environmental inequalities of living in the floodplains of England and Wales and the differences in flood awareness of those 'at risk'. An area comparison is made between an etic, objective flood risk exposure, and an emic, subjective perception of that risk by social class. In all areas except the Midlands, the working classes were more likely to reside in the floodplains; the greatest exposure inequality is seen in the North East and Anglian regions. Flood awareness in the Anglian regions was much lower than average, but there were no significant class differences. In the Thames region, despite equal flood risk exposure between classes, the most deprived displayed the least awareness of flood risk. In the North East, inequalities in the distribution of flood risk exposure accompanied inequalities in perception, resulting in the least aware and most deprived experiencing the greatest flood risk.
Access Grid (AG) is a state-of-the-art video conferencing system that operates over computer networks such as the Internet. In the research sphere it has principally been used to conduct meetings of natural scientists in large international collaborations, such as physicists collaborating over the Large Hadron Collider. Social scientists have recently begun exploring the use of AG to conduct ‘virtual fieldwork’ where researchers carry out interviews or moderate group discussions involving participants at remote sites. There have also been experiments in using AG to deliver social research methods training and to facilitate meetings between social researchers and government researchers who are collaborating on research projects. This article provides a quantitative analysis of the experiences of a sample of participants in such AG sessions. It finds a high degree of satisfaction with the technical affordances of the medium, and identifies differences in perspective according to whether a session is research-oriented or has a ‘real world’ purpose.
This paper explores the environmental inequalities of living in the flood plains of England and Wales and the differences in flood awareness of those ‘at risk’. Large area differences are seen in both flood risk likelihood and also in flood awareness. Furthermore these differences are often class dependent. In all areas except the Midlands, the working classes are more likely to be resident in the flood plains and the greatest inequality is seen in the NE and in the Anglian region. It was found that flood awareness in some areas, especially the NE, was much lower than average and furthermore, these low perceptions of risk were disproportionately displayed by the most deprived. Wales was another region which shows low awareness but is high flood risk. But in Wales, it is the middle classes who exhibit the least awareness.
This chapter considers mixed methods, defined as using two or more research methods within a project, and explores the reasons why a researcher may choose two or more methods to address their chosen area of study. Starting with a discussion of the aims researchers may have in using multiple methods, the chapter then briefly describes key debates about what constitutes mixed methods. It presents the advantages of using a mixed methods approach and discusses a variety of ways that researchers have used mixed methods in social research. It considers how different methods may be linked to different paradigms of social research and how different types of data offer researchers different perspectives on the social world. The existence of different paradigms and perspectives are crucial to understanding mixed methods, because being able to see from different points of view is one of the key reasons for undertaking mixed methods research. These differences, however, are the source of some difficult aspects of mixed methods projects. Mixed methods also entail a number of practical difficulties, and these are also discussed in the chapter.
In recent times there has been a considerable growth in research projects using more than one method. This has led to renewed debate about the issues involved in using multiple methods in a single study, including questions concerning the different ways in which methods and data could or should be brought together. However, within these debates there is a tendency to focus attention on designs which bring together qualitative and quantitative methods, leaving aside research designs which utilise multiple qualitative methods, perhaps on the assumption that ‘qualitative data’ is an homogeneous category. In this chapter we examine the issues involved in integrating different types of qualitative data generated through three qualitative methods: ‘conventional’ in-depth interviews, photo-elicitation interviews, and narrative interviews. Drawing on data from the PPIMs projecti (Practice and Process in Integrating Methodologies project) - which explored the methodological issues that arise in multi-method and multi-level approaches to investigating the management of vulnerability in everyday life - we specifically focus on the process of achieving integration across these sets of data at the point of analysis and document an approach we call ‘following a thread’ (Moran-Ellis et al, 2004).
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