This week’s readings about data journalism further complicated my understanding of data and how we use it. In the podcast interview with Mimi Onuoha and Lam Thuy Vo, they discussed the ways in which documentation can be a form of violence to already-marginalized communities. Documentation, in itself, is a way of reducing people or stories into something more easily understandable or measurable. It strips data of crucial context that is necessary to understanding the complexity of human systems, and it works to actively disempower people and knowledge. They also note that many of the questions we have as data journalists ultimately center on power; who holds power in this data? Who loses power? Who holds power over this data? These questions are incredibly important to keep at the forefront when collecting and analyzing data, because data does not exist in isolation from human beings and their communities. 

Building upon this argument, Nikki Stevens talks about the ways in which the concepts of “dirty” and “clean” data can further reinforce harmful stereotypes. She states that “a focus on a data’s cleanliness is a way of controlling which knowledge is ‘valid’ and is directly counter to intersectional aims” (p. 12). This quote struck me, as did our conversation about raw data as an oxymoron last week, because I’ve been so primed to accept the clean/messy data binary as an academic. Consequently, I never understood the ways in which this standardization can be used to eliminate some of the nuance that exists within and between human relationships. Taking an intersectional approach to data collection and analysis is a substantial goal, however the author notes that the positivist assumptions made in quantification are somewhat incompatible to the broader intersectionality framework. The question I was left with from this article was, how can reimagine data journalism in completely new, black feminist structure that seeks to flip conventional power dynamics on its head? 

During his talk, Alex Howard explained that data + journalism + activism + responsive institutions = social change. The articles previously discussed tackle the first three components of this equation by discussing how data journalism can be used as a form of activism that empowers vulnerable communities. However, I believe responsive institutions is one of the most important ingredients to social change. How do we make institutions responsive to us as the public? Understanding this accountability mechanism disrupts the status quo and requires the people to take power in a way that they previously were unable to. This, I believe, is the core role of data journalism—to shift the narratives that focus on outdated social and power structures to center voices that have previously been silenced. Data journalism has the capacity to reinvent how we think about numbers representing people while also highlighting the limitations to this logic.