From Data Science to Computational Ethnography: Insights from Hackers and Cabbies in New York City
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Abstract: Quantitative expertise entails systematic reasoning around formalized records to solve problems in fields as diverse as medicine, manufacturing, and media. Its recent shakeup around the rise of “data science” was an unusually visible episode in a long history of disputes among quantitative experts. Counterintuitively, this technical shift grew out of qualitative reflections among its protagonists. In this talk, I discuss the abductive logic of inference that drove this collective process and propose an extension to quantitative research itself. I turn to New York City’s Yellow Cab industry for an illustration that reveals the relational foundations of a seemingly formal labor market. This abductive logic of inquiry offers computational social scientists a way to move beyond measuring known sources of inequality to detecting new ones as they emerge.