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STSS in my blog

Several of my blog posts were directly inspired by my participation in the STSS certificate program, both inside and outside the classroom.

I was inspired to write this post while reading the edited volume “Raw Data” is an Oxymoron for Gina Neff’s COM 539 class. The book examines how from an STSS perspective, data are never “raw” but instead are always conceived of and imagined to be data, before they can be collected or generated or even used as such. I focus my post on a chapter of the book that gives a linguistic history of “data” and explores the tensions between data as single and plural noun. I then apply these concepts and insights in the context of genetic data.

I wrote this post following a meeting of the Data Science Studies Working Group about engineering and design. The speakers promoted the idea of “seamful design” as opposed to seamless design, the former being a way to give users a more transparent and honest experience of a product or design.  I was intrigued by the idea of celebrating “seamfulness” and consider what it might look like to make the process of scientific manuscript publication more seamful. Looking back on this post, I think one could see much STSS work as trying to show the “seams” (i.e. human elements, assumptions, disruptions, messiness, interconnectedness) of science as a whole.

This post was a reaction to Geoff Bowker’s Simpson Center sponsored lecture in which he made the provocative suggestion that people don’t really exist outside of their digital data flows. In the post, I react to that claim and the extent which, if true, people can try and fight back by exerting (at least some degree of) control over their own data. These ideas are central to my dissertation project in that some argue (or at least intuitively feel) that being able to download their genetic data and move it about in third-party interpretation systems gives them control.

I wrote this post while taking INFO 450 and processing my thoughts for my class paper. Recent lectures had covered deontological versus utilitarian moral theories. The former are based on the idea of intrinsically valuable acts, regardless of outcome. Utilitarianism, on the other hand, considers the outcome of acts when considering their worth. Here I apply both approaches in turn to thinking about the value or worth of having personal genetic data, a topic central to my dissertation research.

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