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There is a fruitful tension in ethnomethodological work. On the one hand, real-world data are used to rein in analytical privilege. On the other, conceptual discussions necessarily take place in a more open analytical space. Describing settings in detail and thinking about things in the abstract are both essential components of the ethnomethodological project. What ethnographies might consist in complicates this picture. Garfinkel initially deflated the concept of 'ethnography', using it to refer to how all members of society make sense of their world. Sacks, on the other hand, initially construed his sociological project as a more rigorous form of professional ethnography. Ethnographic methods rightly remain an important tool for ethnomethodological analyses. They provide an empirical grounding for analysis and facilitate 'thinking about things' in a more open manner than some other forms of data. This paper argues that ethnographic analyses more generally can be used as ethnomethodological resources, (re)introducing the idea that others' fieldwork and analyses are legitimate resources for ethnomethodological work. Some materials from Elijah Anderson's classic ethnography A Place on the Corner are used to illustrate the possibilities taking this approach might offer. [ABSTRACT FROM AUTHOR]

This paper charts the changing intersections between sociology and science and technology studies (STS) using computational textual analysis. We characterize this "quali-quantitative" approach as a Big Data method, as this calls attention to the commixture of textual and numeric data that characterizes Big Data. The term Big Data, too, calls attention to the increasing privatization of both data and data analytics tools. The data mining was done using a commercial analytics tool, IBM SPSS Modeler, that to the best of our knowledge has not yet been used for STS or sociological research. The identification of intersections occurred as part of a larger project to analyze political-economic and epistemic changes within STS, focusing on academic publishing. These epistemic changes were identified qualitatively, through 76 interviews with STS scholars, and quantitatively, through a computational analysis of three decades of STS journals (1990–2019). [ABSTRACT FROM AUTHOR]