Theory, Practice, and STS

Working on Chapter 3 of Normalizing Health Technologies, I've been musing on the problem of agreement about fundamental problems of practice in Sociology. For example, we can find representatives of very different perspectives – for example, John Goldthorpe [1], representing rational choice theory applied to large population data-sets; and John Law [2], representing actor-network theory in ethnographic case studies – arguing that the integration of theory and empirical research is a core problem.

Traditionally, STS practitioners have usually been cautious about theory in the form of grand narrative. (…) They tend to speak somewhat austerely, to want to know both what large scale generalisations or theories mean in practice, and about where they apply. Indeed, they are prone to ask whether such generalisations mean anything at all. They also, and in a related way, tend to avoid buying into a theory/data distinction. This is because in STS theory is not first created and then applied empirically. Theory and data are created together. However empirical it may be, everything is already theorised (2008: 629)

This implicit theorisation is both inscribed in the meanings and assumptions that are designed into technologies like telemedicine – in this case that clinical encounters can be lifted out of the clinic, and be made more efficiently and equitably available that are by the people who are implicated in those practices, and in the cognitive and behavioural ‘toolkit’ that those people draw on in their everyday lives. So, one task for sociological analysis is to engage with those implicit cognitive resources and to find ways to make them explicit. But for Law and others, the business of STS is also about breaking down distinctions between data and theory, and saying that STS analysis is about the co-production of theory and data in relation to some empirical topic.

Law wants to avoid social science in which the empirical world is divided off from the world of theoretical development – like many sociologists (me included). He’s also anxious that the methods of sociological research come to constitute the realities that sociologists seem to engage with. Foucault’s dictum, that ‘discourse constitutes its own objects’ [3] applies here. So, to read theory in STS is to read the literature of cases studies. It is in this context that theory is developed as the empirical world is described and understood. An approach in which ‘theory’ and ‘data’ are co-produced and interwoven, then, is at the heart of Law’s analysis of the strengths of STS.

I think this is true of the work of a very small number of theoretical innovators including Law, but also – and especially the astonishing Sociological imagination of Michel Callon [4, 5]and Donald Mackenzie [6-8], both of whom have become interested in the sociology of maths, markets, and machines. However, it is much less clear that this is, in practice, what happens more generally. It's certainly not what I see as a reviewer for journals like Social Science and Medicine. In fact, just as in other areas of theoretically informed social science investigation, we see multiple instances of the transportation of basic constructs of a theoretical perspective from empirical setting to empirical setting. They don’t change much as they move between them, and slowly the socio-technical world becomes framed in relation to such constructs. It's hard to have a sociological conversation now about a new technology without addressing the problem of how the network is stabilized or not.

1. Goldthorpe, J.H., The integration of sociological research and theory - Grounds for optimism at the end of the twentieth century. Rationality and Society, 1997. 9(4): p. 405-426.

2. Law, J., On sociology and STS. Sociological Review, 2008. 56(4): p. 623-649.

3. Foucault, M., Afterword: the subject and power, in Michel Foucalt: beyond structuralism and hermeneutics, H.L. Dreyfus and P. Rabinow, Editors. 1986, Brighton. p. 208-226.

4. Callon, M., C. Meadel, and V. Rabeharisoa, The economy of qualities. Economy and Society, 2002. 31(2): p. 194-217.

5. Callon, M. and F. Muniesa, Economic markets as calculative and calculated collective devices, C.U. New York Conference on Social Studies of Finance, Editor. 2002.

6. MacKenzie, D., Mechanizing Proof: Computing, Risk and Trust. 2001, London: MIT Press.

7. MacKenzie, D., Knowing Machines: essays on technical change. 1998, London: The Massachusetts Institute of Technology Press.

8. MacKenzie, D., Inventing Accuracy: A Historical Sociology of Nuclear Missile Guidance. 1993, Cambridge, Mass: MIT Press.