Posthumanist data analysis of mangling practices

Abstract

In this paper, I argue against traditional coding in interpretive data analysis and offer a posthumanist alternative that offers qualitative researchers a new way to create ontological becomings in their reading of data. I begin with an overview of how humanism enables us to think qualitative data analysis as coding, and then counter human-centered inquiry with a description of Pickering’s mangle and its potential as a both a figuration and a different tool for analysis. I then give an example of a reading of data as/in/of the mangle. I show the agentic features of both human and non-human elements of the mangle to move away from epistemological representations of the “real” to practices of decentering the human in social science inquiry. I conclude that using Pickering’s posthumanist ontological theory of agency is one gesture toward the becoming of what the editors of this issue call post-qualitative research.

Keywords:

• post
• qualitative
• research

Notes

1. I want to acknowledge that the analysis here, for the purposes of this paper, is limited; that is, it is indeed possible (and desirable) to complicate a mangled analysis to include more critical discussions of race, class, gender, embodiment, power, and so forth. Because I want to focus on particular aspects of Pickering’s mangle (i.e. agency) to make an argument for a different way of conducting post-humanist analysis, I refrain from pulling in other analytic threads. This analysis of mangled practices, therefore, is admittedly selective and narrow, but nonetheless detailed. I hope to give readers an introduction to the possibilities of analyzing the mangle, rather than even a partial representation of meaning.

2. This work comes from my and Lisa Mazzei’s recent book, Thinking with Theory in Qualitative Research: Viewing Data Across Multiple Perspectives (Jackson & Mazzei, 2012). Our purpose in the book is to challenge qualitative researchers to use theory to think with their data (or use data to think with theory) in order to accomplish a reading of data that is both within and against humanistic practices of analysis and interpretation.