Data diffraction: challenging data integration in mixed methods research

Emma Uprichard, Leila Dawney

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Pages (from-to)19-32
JournalJournal of Mixed Methods Research
Issue number1
Publication statusPublished - 1 Oct 2016

Bibliographical note

This article is distributed under the terms of the Creative Commons Attribution 4.0 License ( which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (


  • cut
  • mess
  • mixed methods
  • diffraction
  • integration


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