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Data Diffraction: Challenging Data Integration in Mixed Methods Research.

Emma UprichardLeila Dawney
Published in: Journal of mixed methods research (2016)
This article extends the debates relating to integration in mixed methods research. We challenge the a priori assumptions on which integration is assumed to be possible in the first place. More specifically, following Haraway and Barad, we argue that methods produce "cuts" which may or may not cohere and that "diffraction," as an expanded approach to integration, has much to offer mixed methods research. Diffraction pays attention to the ways in which data produced through different methods can both splinter and interrupt the object of study. As such, it provides an explicit way of empirically capturing the mess and complexity intrinsic to the ontology of the social entity being studied.
Keyphrases
  • electronic health record
  • study protocol
  • big data
  • working memory
  • healthcare
  • crystal structure
  • randomized controlled trial
  • clinical trial
  • solid state