Though many are convinced that better social science evidence will make for better policies, we do not know how to turn that conviction into a reality. Nancy Cartwright and Julian Reiss argue that current efforts in evidence-based policy tend to focus on improving the credibility of results. But that is not enough. It is now time to invest heavily in developing methods for how to put this hard-won knowledge to use to build better societies.
Society invests a great deal of money in social science research. Surely the expectation is that some of it will be useful not only for understanding ourselves and the societies we live in but also for changing them? This is certainly the hope of the very active evidence-based policy and practice movement, which is heavily endorsed in the UK both by the last Labour Government and by the current Coalition Government. But we still do not know how to use the results of social science in order to improve society. This has to change, and soon.
Last year the UK launched an extensive – and expensive – new What Works Network that, as the Government press release describes, consists of “two existing centres of excellence – the National Institute for Health and Clinical Excellence (NICE) and the Educational Endowment Foundation – plus four new independent institutions responsible for gathering, assessing and sharing the most robust evidence to inform policy and service delivery in tackling crime, promoting active and independent ageing, effective early intervention, and fostering local economic growth”.
This is an exciting and promising initiative. But it faces a series challenge: we remain unable to build real social policies based on the results of social science or to predict reliably what the outcomes of these policies will actually be. This contrasts with our understanding of how to establish the results in the first place.There we have a handle on the problem. We have a reasonable understanding of what kinds of methods are good for establishing what kinds of results and with what (at least rough) degrees of certainty.
There are methods – well thought through – that social scientists learn in the course of their training for constructing a questionnaire, running a randomised controlled trial, conducting an ethnographic study, looking for patterns in large data sets. There is nothing comparably explicit and well thought through about how to use social science knowledge to help predict what will happen when we implement a proposed policy in real, complex situations. Nor is there anything to help us estimate and balance the effectiveness, the evidence, the chances of success, the costs, the benefits, the winners and losers, and the social, moral, political and cultural acceptability of the policy.
Image credit: CCAFS (CC BY_NC)
To see why this is so difficult think of an analogy: not building social policies but building material technologies. We do not just read off instructions for building a laser – which may ultimately be used to operate on your eyes – from knowledge of basic science. Rather, we piece together a detailed model using heterogeneous knowledge from a mix of physics theories, from various branches of engineering, from experience of how specific materials behave, from the results of trial-and-error, etc. By analogy, building a successful social policy equally requires a mix of heterogeneous kinds of knowledge from radically different sources. Sometimes we are successful at doing this and some experts are very good at it in their own specific areas of expertise. But in both cases – both for material technology and for social technology – there is no well thought through, defensible guidance on how to do it: what are better and worse ways to proceed, what tools and information might be needed, and how to go about getting these. This is true whether we look for general advice that might be helpful across subject areas or advice geared to specific areas or specific kinds of problems. Though we indulge in social technology – indeed we can hardly avoid it – and are convinced that better social science will make for better policies, we do not know how to turn that conviction into a reality.
This presents a real challenge to the hopes for evidence-based policy. But the opening of the new What Works Network provides a unique opportunity for the UK to tackle this challenge. The UK funding body for research in the social and economic sciences, the Economics and Social Research Council (ESRC), supports research on the development of new social-scientific methods.That can help us establish more – and more credible – results within the social and economic sciences. But that is not enough. It is now time to invest heavily in developing methods for how to put this hard-won knowledge to use to build better societies – to develop methods for the technology of the social sciences.
Philosopher Philip Kitcher urges that society should aim for ‘well-ordered science’ (most importantly in his 2003 Oxford University Press book Science, Truth and Democracy). A science is well-ordered to the extent that its research priorities are ones that would be endorsed in a democratic deliberation among well-informed participants committed to engagement with the needs and aspirations of others. In other words, Kitcher demands that science should ask the right questions and in the right ways. The UK is already investing heavily in answering one question: “How do we design social science studies so we can be more certain of their results?” The question we are neglecting is: “How do we put this knowledge to use to build better societies?”
This post originally appeared on the Institute of Art and Ideas (IAI) news site and is reposted with permission.
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Nancy Cartwright is former mathematician, now professor of philosophy at California and Durham universities. Author of Evidence Based Policy and How The Laws of Physics Lie.
Julian Reiss is professor of philosophy at Durham University, focusing especially on the philosophy of economics