There’s a widespread idea that “People who make things are simply different [read: better] than those who don’t.”
Debbie Chachra, “Why I Am Not a Maker,” The Atlantic, January 23, 2015.
In this quote, Chachra points out the cultural tendency to associate people who make things for public output as more superior than those who do not.
Until I read this article, I had not put that much weight into the word “maker.” But, after reading it, I agree with Chachra. There is a deeply-rooted idea in our culture that people who make products for the world are more important, or at least more respectable, than the people who work behind-the-scenes, enabling the “makers” to even make stuff in the first place. If it were not for the person at home making them dinner so that they can work until late, or the community management workers on whom their companies’ success is based on, these makers would not be nearly as successful. Yet, somehow the invisible infrastructure of labor that stands behind the makers receive little to no credit.
This quote stood out to me because I could think of immediate real-life examples where I have seen this bias play out. The most common one is people (who Chachra would consider as makers) shaming their Starbucks barista or McDonalds employee for doing “useless” work. Ironically, though, the ones doing the shaming are often the people who would be the most upset if their local Starbucks shut down because they would no longer be able to get their morning coffee.
To tie this into the topic of digital humanities, I think that there is a makers bias in the world of academia as well. There seems to be a divide that keeps computer scientists and other technology-savvy departments from intersecting with the humanities because the scientists think that they are superior. My hope is that this divide one-day diminishes and the digital humanities can grow as a bridge between the two fields.
Personally, I find data visualization to be very interesting and a tool that any person in any academic field can benefit greatly from. Data visualization is also a topic that combines two things that I am interested in–digital art and statistics–so I hope to pursue more of it throughout this class.
