This week I’ve been reading Sergio Sismondo’s An Introduction to Science and Technology Studies, which has given me a lot to think about in terms of theoretical backgrounds for understanding how science creates knowledge. In fact, it’s almost given me too much to think about. There are so many different theoretical bases brought into the mix here, and I can see the relative merits of each, so I find myself wondering how to make sense of it all, but also what it means to adopt a theoretical underpinning as a social scientist. Is it like a religion, where you accept one and only one dogma, and all parts of it, to the exclusion of all others? Or is it more like a buffet, where you pick a little bit of the things that seem appealing to you and leave behind the things that don’t catch your eye? I’m hoping it’s the latter, and I’m going to go on that assumption until the theory police tell me I can’t do it. 🙂 So, on that assumption, here are some ideas I’ve put on my plate from Sismondo’s buffet.
Structural Functionalism and Mertonian Norms
My favorite theoretical framework I picked up here was structural functionalism, and in particular, Robert Merton’s four guiding norms. Structural functionalism, as I understand it, argues that society is composed of institutional structures that function based on guiding norms and customs. Merton suggests that science is one such institution, the primary goal of which is “the extension of certified knowledge” (23). Merton also outlined four norms of behavior that guide scientific practice, suggesting that those who follow them will be rewarded and those who violate them will be punished. The norms are universalism (that the same criteria should be used to evaluate scientific claims regardless of the race, gender, etc of the person making them), communism (that scientific knowledge belongs to everyone), disinterestedness (that scientists place the good of the scientific community ahead of their own personal gain), and organized skepticism (that the community should not believe new ideas until they have been convincingly proven).
Of those four norms, communism and disinterestedness speak the most to my interest in data sharing and reuse. Communism seems the most obviously related. It’s very interesting to think about what parts of science are typically thought to belong to the community and which are thought to be privately owned. For example, the Supreme Court unanimously ruled in 2015 that human genes could not be patented, a decision that seems in line with Merton’s communism norm. On the other hand, plenty of scientific ideas can be and are patented. While many scientific journals are becoming open access and making their articles freely available, many more work on a subscription model, suggesting that the ideas shared within are available for common consumption – if you are willing and able to pay the fee.
Although this example comes from an entirely different realm than science, thinking about these ideas has reminded me of the case of the artist Anish Kapoor, who purchased the exclusive rights to paint with the world’s “blackest black” so that no other artist can use it. In retaliation, another artist designed the “pinkest pink” paint and made it available for sale – to any artist except Anish Kapoor. While this episode is somewhat entertaining, it does bring up some interesting ideas about ownership in communities that are generally dedicated to the common good. Art and science are very different, but they’re also quite alike in some ways that are very relevant to the work I’m doing. They’re both activities carried out by individuals for their own reasons (artistic expression, scientific curiosity) for the common good (to share beauty with the world, to further scientific knowledge). We are outraged when we hear of a rich artist laying exclusive claim to the raw materials of art so that no one else can use them. It feels somehow petty, and it also seems like a disservice to not just the art world, but to all of is. What could others be creating for us if they had access to that black? I don’t know if we feel that same outrage when we hear of a scientist trying to lay exclusive claim to data. Of course this isn’t a perfect analogy – a big part of the work of science is gathering or creating the data, which confuses the concept of ownership. Still, I think there are some interesting ideas here to explore about how scientists think about common ownership of science – not just the ideas, but the data as well.
I started out this entry saying I was going to dip into some other theories – I have some things to say about social constructionism and actor-network theory, but now I’ve spent a long time going on and on about art and science and this is getting a bit long, so I think I’ll stop here for today. 🙂