Thread by @math_rachel

"Data do not speak for themselves. Data must be narrated—put to work in particular contexts, sunk into narratives that give them shape and meaning, and mobilized as part of broader processes of interpretation and meaning-making." @dourish @Imagenaciones

journals.sagepub.com/doi/10.1177/20…

Two scalar moves in data science:
1. move datum➡️ data set, the claim that these data are sufficiently "alike" as to be able to be combined, compared, added, & divided
2. move large ➡️ small implicit in the drawing of conclusions or categories from data analysis 2/

The granularity of the data, both spatially and temporally, radically reconfigured the work that they had to do. The very fact of a digital trace produced the necessity of an account, leaving them with less time for their previous responsibilities to parolees and to the public 3/

The responsibility that they felt that they could still discharge, and which occupied an ever-greater amount of time, was one towards *organizational processes*, or even to the data itself. 4/

"Data makes sense only to the extent that we have frames for making sense of it, and the difference between a productive data analysis and a random-number generator is a narrative account of the meaningfulness of their outputs." 5/

journals.sagepub.com/doi/10.1177/20…