https://doi.org/10.1177/1077800417729847 Qualitative Inquiry 1–10 © The Author(s) 2017 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1077800417729847 journals.sagepub.com/home/qix Article It’s tempting to say that this article will illustrate the adage “There are many different ways to skin a cat”—but what an unappealing metaphor! Instead, we have been guided by the structure and ethos of Wallace Stevens’ poem “Thirteen Ways of Looking at a Blackbird” (Stevens, 1954, pp. 92-94), which employs a range of perspectives to shift readers toward a deeper, more complex understanding of what they are “really” seeing. Our aim is neither to present a single, definitive set of research findings nor to argue for the pri- macy of any one methodology. In the spirit of Stevens and his poetic precursor Emily Dickinson (“Tell all the truth but tell it slant—/Success in Circuit lies”; Dickinson, 1961, p. 506), we have experimented with a multiplicity of approaches to find out what they might teach us—not only about the data itself but also about our own positionality as researchers and writers. We began with a foot-high stack of anonymous question- naires that had been collected by Helen, the first author, over a 5-year period spanning 2011 through 2015. The questionnaires had been coded for keywords and themes by Louisa, her longtime research assistant, and subjected to some very basic qualitative and quantitative analysis. However, the findings of that analysis are mentioned only briefly in the book that Helen published as a result of the study, which focuses mainly on her interviews with one hundred “successful academic writers” (Sword, 2017). Sensing a missed opportunity, Helen invited her colleagues Marion, Alistair, and Evija to examine the questionnaires, each from a different scholarly perspective; she also asked Louisa to write a personal reflection on her experience of coding the data, and she revisited the questionnaires herself, focusing on the respondents’ use of metaphor. Whereas Louisa and Helen were already deeply familiar with the questionnaires and the information they contained, Marion, Alistair, and Evija came to the project with very little previous knowledge of Helen’s research and thus no particular preconceptions about what they might discover there. Each coauthor chose a particular critical lens through which to view the questionnaires: Louisa, a literary scholar and technical writer with a master’s degree in English, brought a postmodern perspective to her discussion of the methodologically rigorous yet ontologically slippery task of coding; Marion, a trained biologist skilled in quantitative data analysis, brought a scientist’s love of numbers; Alistair, an empiricist historian of science, brought his background as an archival scholar who treats textual sources as material culture; Evija, a former journalist with a PhD in writing studies, brought her interest in the hidden dynamics and emotional nuances of the writing process; and Helen, a lit- erary scholar and expert on academic writing and research productivity, adopted a poet’s gaze. In choosing to analyze a single data set from multiple perspectives, we join a long line of scholars who have con- tributed to the theory and practice of nontraditional or dis- ruptive research methodologies: for example, Feyerabend (1993) on method, Law (2004) on mess, Knowles and Cole 729847QIX XX X 10.1177/1077800417729847Qualitative InquirySword et al. research-article 2017 1 The University of Auckland, New Zealand Corresponding Author: Helen Sword, Professor, Centre for Learning and Research in Higher Education (CLeaR), Faculty of Education and Social Work, The University of Auckland, 18 Waterloo Quadrant, Private Bag 92019, Auckland 1142, New Zealand. Email: h.sword@auckland.ac.nz Seven Ways of Looking at a Data Set Helen Sword 1 , Marion Blumenstein 1 , Alistair Kwan 1 , Louisa Shen 1 , and Evija Trofimova 1 Abstract A literary theorist, a biologist, an historian, a writing studies scholar, and a poet walk into a wine bar. The poet says, “I’ve got a stack of 1,223 handwritten questionnaire responses here in my bag; would you like to have a look?” The others reply, “Sure. Let’s see what we can learn here.” Descending from their respective disciplinary perches, they all gather around a table and start sifting through the questionnaires, which chronicle the writing background, habits, and emotions of PhD students and faculty in 15 countries. In this single corpus of data, each researcher sees something different, and from the other researchers’ responses, each learns new ways of seeing. What counts as an appropriate data analysis? What, for that matter, counts as data? We invite you to grab a drink and join our conversation. Keywords academic writing, emotion, data coding, metaphor, alternative methodological approaches