Innovation in Mixed Methods

In bringing together collaborators from the UK, Germany, India and Bangladesh, this three-year project (2014-2017) acknowledges the interdisciplinary nature of labour research, as it endeavours to address a number of themes: skills, productivity, gender stereotypes, wage-bargaining, globalisation, the intensification of paid work, formal/informal and self-employment, domestic work, value chains, and the demand for labour during growth and recession.

Through this pioneering international partnership, the issue of how mixed-methods research might contribute to improved labour research is highlighted. Many labour-focused projects now use mixed methods, but studies are regularly challenged in their attempts to establish validity and generalisability. A common outcome is that qualitative material is separated from survey data and hence from statistical results.

Accordingly, the ‘Integrated Mixed Methods Network’ advocates the deep linkage of verbatim qualitative data, qualitative analysis and systematic data, such as survey and case-study data. The research element of the project involves the re-use of existing data from both qualitative and quantitative surveys. Innovations include connecting qualitative evidence with factor analysis and drawing a set of linkages connecting case-study evidence with Qualitative Comparative Analysis (QCA).

The seminars and workshops under this scheme will develop and test new and rigorous methods of creating, analysing and interrogating data. Experts in statistical and mixed methods will be in attendance, ensuring that advanced quantitative methods are explained and promoted to a wider audience, including those with qualitative specialisms.

Alongside invited seminars in the UK, Germany and India, key findings from the study will be communicated within two stakeholder events:

  • In 2015-16 a one-day workshop, held in the UK, offering a thorough review of QCA – using NVIVO software.
  • In 2016-17 a one-day workshop in Bangladesh, offering advanced training in factor analysis (again using NVIVO), linking quantitative data sets with qualitative materials such as interview transcripts.

Towards the end of the funding period – with a view to future collaborative bids – the focus on the UK, Bangladesh, Germany and India will be broadened to include additional South Asian (e.g. Myanmar, Pakistan, Sri Lanka and Nepal) and European (e.g. Belgium, Netherlands, and Ireland) partners.

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