The European association on national Research Facilities (ERF) brings together open-access national research facilities – institutes carrying out big-budget research including particle physics, astronomy, nanotechnology, nuclear research, medicine, and natural history. I’m sure I will have missed something off that list. The key is being open: ERF stipulates that facilities wanting to join must carry out their work openly. When communication features so high on the list of priorities, the positive social impacts should be self-evident. But the methodologies to evaluate socioeconomic impact of big science are not agreed – they’re still the subject of vigorous debate.
Convened at DESY – the German Electron Synchotron – in Hamburg are representatives of research facilities, research funders, and various European bodies. We’re here to discuss the socioeconomic impacts of research infrastructures. Across two days of talks and discussions, those attending debated exactly how such impacts should be measured. The Experimental Facilities Manager of the Canadian Light Source (CLS), Emil Hallin, preceded his talk with a response to a previous question – a point that would turn out to be a recurring theme, at least for the first day of talks. “The problem with reaching out to industry,” he said, “is that those in industry – the economists – don’t often value work that is done for free.” The collaborations that facilities and research infrastructures engage in, when they’re for academic purposes – or non-commercial – are often done for free. Or at least they’re done gratis; perhaps not libre – because sometimes contracts stipulate that intellectual property (inventions) resulting from such collaborations remain the property of the facility or infrastructure provider, as Carlo Rizzuto from the Italian infrastructure Elettra, would discuss later.
Stefan Michalowski from OECD returned to the disconnect between looking at economic and other impacts of a project: “funders wanting to measure socioeconomic impact ask how many jobs the research infrastructure creates; how much it increases GDP... Researchers themselves look at how many PhDs are produced per year, how many papers are written…” but also, “Qualitative, rather than quantitative methods, are how we should measure impact.” That, of course, is difficult. Especially for economists wanting to evaluate whether big money is being spent well in the throes of a global financial crisis. But perhaps it highlights an unfortunate result of the concatenation ’socioeconomic’ itself: if a word comprises two spheres – two different ways of looking at the world – and one naturally lends itself to (easy) quantitative analysis and the other calls for qualitative analysis, then the easy quantitative analysis, the bit that concerns itself with the money, will win out. Especially when big money is what it takes to put the infrastructure in place. This dichotomy between cold finance and the wooly human aspects of research impacts even permeated the scheduling of the talks: ‘Economic aspects’ ran parallel to ‘Social, Educational and Environmental Aspects’ – perhaps all four concerns should have been addressed together. But then, that’s why there are networking sessions, and after dinner discussions. It’s worth reminding funders though: you can’t – or at least it’s not easy to – put a number on everything.