By Craig Hamilton
My living room is where I do most of my work. It has a window that looks out on a point halfway between a school and a park.
My kids go to the school, and like all the other kids they play in the park when the school finishes. The park has a play area. Swings, slides, climbing frames. After the kids have been cooped up all day, sat still and paying attention, learning to read and write – the stuff of formal education – the park affords immediate freedom. They can let off steam and test out new skills and boundaries, both social and physical. Sharing this, climbing that, seeing how high someone can go. School is theory. The park is practice.
There are some monkey bars in the play area. I see a man in the park sometimes, early in the morning, dressed in the type of fitness gear that suggests he means business. He does fifty chin-ups on the monkey bars before disappearing to complete the rest of his doubtlessly arduous workout. I look on in sullen admiration, smoking. I’ve always been terrible at chin-ups. He’s an expert. I’m not.
Molly, aged 7, lives four doors away. She also goes to the school and the playground. She’s a natural gymnast, fearless and strong; effortless on the monkey bars. I asked her recently if she could do chin-ups. She’d never tried, she said. Neither had my son, Mac. I told them I was terrible at chin-ups, and also about the man who does fifty. They were impressed. Now, every time we’re in the park, we try to do chin-ups. Mac struggles to make two. Molly can do three. I’m winning, though. I can do five!
Here’s why I’m telling you this:
I started my PhD thinking I was operating in the field of Popular Music Studies. Popular Music is something I thought I knew more about than most, but I’ve since realised there are people who can do more chin-ups than me. To achieve the requisite new contribution to knowledge demanded of a PhD, I wanted to look at how the experiences of listeners were evolving alongside digital technologies, something very few people know about. I soon realised that what I was really trying to do was understand how digital technologies are impacting on society, and that popular music listeners were the means by which I might do that; a subtle but important shift. I decided that in order to understand the impact of industrial data collection and analysis, something increasingly seen in the delivery of the popular music experience, I would process my data in similar ways.
This is where the man on the monkey bars is important. As is the school and the playground.
How did he get to the stage where he could do fifty chin-ups? How does anyone learn to read or write? The answer is: they start at the beginning.
I can now do five chin-ups because a few days ago I just about managed four, and had huffed and puffed my way towards three before that. Kids learn sounds, then speech, the alphabet, phonics, then words, punctuation and grammar. Before you know it, they are carving their names into tree trunks in the park and winning the Booker Prize. That’s the theory, anyway. That’s how school works, and that’s how fitness instructors make their money. They provide the framework and the roadmap, but it is practice that puts flesh on the bones of arms and legs, and of Booker Prize-winning novels.
So, in order to attempt to do what I’m attempting to do, I’ve gone back to school and learned a new language, one chin-up at a time. To understand how data and code affects us, I’m learning not only what data and code are, and what they may mean, but I’m also learning how to code. Code as a language with it’s own rules, affordances and limitations: I code, Molly codes, Mac has coded.
The Cultural Analytics scholar, Andrew Piper, asks, “At what point did it become necessary, in the sense of unavoidable, to use computation to study culture?”. It’s a fair question: what does code have to do with culture? Well, just about everything these days, and certainly when it comes to popular music. In my thesis, one of the things I’m going to argue is that unless you understand code, data, and their consequences and affordances, at least on some level, then an understanding of the world of popular music is going to be beyond your grasp. Everyone is going to need to start doing chin-ups.
But more than that, there has been an interesting intersection between theory and practice in the laborious detail of my own learning. I’m a one-finger coder, I can only do five chin-ups, and that is proving to be –paradoxically – enormously helpful.
A computer script is as a logical argument in the same way that a theory is, and when you build one very slowly, as I am being forced to do by my limitations, that the myriad of assumptions inherent in your argument are constantly foregrounded. There is a fascinating tension between the empiricism of numbers, data and scientific process, and the reflexive realisation that the methods used in pursuit of them are ultimately creative acts. Collins, Evans and Gorman call this a ‘trading zone’ between disciplines. Much is still up for grabs they say since, ‘no one is sure exactly what it is, what it is called or should be called, who should do it, or how exactly it ought to be done’.
The use of code in cultural studies has been criticised. The work of Lev Manovich, for example, has been described as being ‘endless visualisations with no foreseeable end’. A reductive battle line of sorts has been drawn between Hack vs Yack; upstart coders against traditional theorists. But the reality is not so stark. Piper argues that not only can computation help us to develop a better understanding of culture, but that cultural scholars can have a beneficial impact on the nature of code. This suggests interesting times ahead for both.
Sandvig and Hargattai argue that – apart from in Ethnographic work – there is very little notion of ‘Bench Science’ in the humanities and social sciences, but that there should be. They call for the ‘workaday’ practice of our research processes to be highlighted, particularly in areas of work that look at digital media and the Internet, because these are producing the ‘new methods, new opportunities, and new challenges for understanding human behavior and society.’ The desired outcome is a space where ‘researchers can reveal the messy details of what they are actually doing, aiming towards mutual reflection, creativity, and learning that advances the state of the art’. As I develop my own analysis, one chin-up at a time, learning from one grammatical error after another, the limitations and affordances of theory and practice are slowly revealed in the process of writing my notes, in the detail of the painfully slow, step-by-step Benchwork.
My living room window looks out on the point halfway between the school and the playground. This is the room where I do my work.
Craig Hamilton is a PhD student in the School of Media at Birmingham City University. He tweets at @craigfots.
Originally posted 22nd May 2017.