Miriam Posner, “What’s Next: The Radical, Unrealized Potential of Digital Humanities.”
I have to admit, I have been a long doubter of digital humanities before I was involved in DH projects–and maybe long after that. I come from another culture and the general “feels” about digital humanities in East Asia, or the critical institution that I was apart of, is very negative. It is not even “not positive” stage. In a country hosting Samsung and LG, benefiting with world’s one of the most developed technological practices, people in subway all looking down at their cellphones, it is maybe ironic. And this may be the reason more so for the humanities professionals to be against anything that combines digital with the humanities.
And before I say every doubt you have is legitimate as well as beginning to be answered, here are some of the questions I had: What do humanities have to do with anything digital? Aren’t we supposed to be persons who endorse reading? Will it need the professionals in humanities who were trained to read, analyze, think critically, etc. to work in realms fueled by corporate-driven funding and computer coding? As I learned to realize, most of the doubts I had was due to lack of information or understanding of what DH is. And now it seems even embarrassing to write down the questions I had.
By chance and will, I’m in an institution where the university as well as faculty members are open and even eager (wow) to the promotion of DH. In my first semester as a doctorate student, I did a mapping project using ArcGIS program, visualizing how “monsters” and ghosts of 18th and 19th Century differ in terms of gender of the creature and authors. I pinpointed the locale of creature’s existence, sightings, the amount they traveled, the course they took, the monstrosity of their appearance as well as actions, etc. I used excel to make a data collection, did tons of calculations that I already forgot how to, used technology to visualize the intensity of atrocity of monsters. It was a frustrating experience largely because I had to learn how to master a program that I have not even heard existed but mainly because I had “doubts.”
As a person who were used to “close-reading” analysis, and who believed that was the “legitimate” way to “do” literature, counting word frequency, making a monstrosity level spectrum (i.e. murder being the highest, haunting being the lowest, for example) as well as empathy level spectrum, and above all, presenting literature as a spectacle one could understand at first glance was disturbing for me. (And perhaps the fact that I would show this to non-humanities-professionals and they say “it’s cool!” was discouraging.) Still, my data proved (and “showed”) that female monsters have less travel-distance (i.e. home-bound) and were more empathy-evoking. I concluded the project linking female monsters/ghosts demonstrating their fears and angers as well as limitations about domestic spheres they were confined to. Though my findings were wonderful and received great reviews, I still was hesitant. How can I judge the Creature from Frankenstein’s murder of a little boy is less monstrous than Count Dracula’s possession which will later lead to another killing? How can I assess a female ghost’s vindictive haunting to her failed lover is less monstrous than a male monster’s random killing?
Miriam Posner says, this is exactly what humanities in DH should be doing. Digital humanities is not just about using software, transferring data to an online collection, archiving, producing visual data that layperson can look and convinces themselves of granting you the funding. Our job is to ask questions, to tease out the assumptions, especially ideologically-driven ones, and to ask for change.
In the chapter above mentioned, she focuses her attention to gender and race. As a person who does Age Studies, I wonder the same argument could be made for age-category. Just like the distinction or the opting of black/white, male/female, we take the distinction of age granted. Does “senior years” start with 65? Why? Mostly because it is the time when pension begins not because of some inherent quality associated with the number. Oftentimes when I’m doing DH projects, I have the need to categorize humans, cultures, events, not only identifying them but also making inclusive-exhaustive definitions. Sometimes I am frustrated with this process because it is necessary to get the “result.” It is not so satisfying (not for me though) to have many unclassified/double/triple/or more overlaying elements in your data. And sometimes you have to make sacrifices. When I was using z-axis map, it incorrectly assumed words that carry negative connotation to be used to describe negative event/emotion. But without making some sacrifices, it seems meta-data is not possible. But is it? Posner suggests that we will get results and data, only that it might not conform to already existing social norms. If we add–or figure out a way to represent/categorize gender, we will not have how many women vs men have jobs but something radically different. It could be women vs men vs many other categorizes but also could be of different ramification. It might even further the idea of the futility of gender categorization–or the opposite.
I am not familiar with technology. I use my phone until it breaks, rarely install anything that doesn’t come with the laptop, doesn’t have a twitter account, just started trusting Starbucks phone app. And the talk of digital presence scares me still. But I don’t believe DH is about one’s preference. It’s about the responsibility as well as the ability of people in humanities to ask meaningful questions about a cultural phenomena and contributing to it with valuable doubts.
