Ways with data: Understanding coding as writing
2017-05
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Ways with data: Understanding coding as writing
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2017-05
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In this dissertation, I report findings from an exploratory case-study about Ray, a web developer, who works on a data-driven news team that finds and tells compelling stories with large sets of data. I implicate this case of Ray's coding on a data team in a writing studies epistemology, which is guided by the following question: What might be learned about coding, if writing researchers explore the consequences of making language material and computational in a digital medium? I begin this study by outlining a theory of materiality of writing through 6 propositions, which serve as a lens to review literature and theories about coding that articulate the characteristics of code as written communication. From there, I describe my grounded-theory approach to this exploratory case and the battery of ethnographic methods used to collect observational data of Ray's coding over the course of approximately 6 months. Next, I present findings from my grounded analysis across 2 chapters. The first findings chapter cultivates a thick description of Ray, his coding, and how his coding is embedded within a broader objective to find stories in and through aggregate information, which I call aggregate narratives. In the second findings chapter, I conduct a more granular analysis of Ray's coding of goal-oriented slices of data from the original data set source -- a coding practice that produces what I term provisional texts. Findings indicate how Ray's coding of the provisional texts, and the texts themselves, provide active epistemic functions to create aggregate narratives. Finally, I conclude by synthesizing findings with the theoretical propositions about the materialities of writing discussed in the first chapter. Overall, Ray's coding and its materialities show how coding is a dynamic, situated cultural practice, which invites future inquiries into and across domains of coding practices.
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University of Minnesota Ph.D. dissertation. 2017. Major: Rhetoric and Scientific and Technical Communication. Advisor: Christina Haas. 1 computer file (PDF); xvii, 275 pages.
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Lindgren, Chris. (2017). Ways with data: Understanding coding as writing. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/188937.
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