Alex Hulkes is Strategic Lead for Insights at the ESRC, and is responsible for developing our ability to evaluate and carry out data-informed analysis of ESRC investments, policy and operation.
Here he outlines the latest analysis from ESRC on funding distribution, funding concentration and the size of the ESRC applicant population.
No, it’s not ESRC Scrabble day (243 points to us though). The quincunx, or ‘bean machine’, demonstrates the way in which the cumulative results of many small effects can create striking patterns in distributions of outcomes. Along these lines there are three new analyses which seek to explain how the resources we provide come to be shared the way that they are shared.
The first starts with ESRC applicants (PDF). How many are there? That’s easy – it’s the same as the number of UK academics working in social science. Well, actually no. To be an ESRC applicant you have to be eligible to apply, to want to apply, and to have something that you want to apply to do. These conditions mean that there is no fixed size for the applicant pool and that it changes every minute of every day.
A reasonable estimate is somewhere between 16,000 and 20,000 applicants, meaning that less than 10% of the pool of potential ESRC applicants will actually decide to apply in any one year. That goes some way to explaining why the average time between applications is probably about six or seven years. And that in turn explains why demand management based on individuals won’t work for ESRC.
The second analysis on the distribution of funding (PDF) looks at the same sort of issue, but for research organisations (ROs). If you held an ESRC proposal in your hand and were asked to guess how many other proposals that particular RO submitted in the same year, you’d be best off saying ‘no more than two’, as the average RO applies perhaps three times a year. Different ROs make different choices about how often to apply and how much to ask for.
Some apply much more than that of course, and there is a fair degree of concentration of funding in the larger ROs as a result. But there is a surprising degree of variability in any conceptual list of the ‘top 10’ applicants. ROs rise into and drop out of this list all the time, with only a few sitting any length of time at the top of the chart.
The third analysis on funding concentration (PDF) looks at what happens once applicants have submitted a proposal. The key conclusion is that our peer review processes seem to treat organisations equally. They neither concentrate nor disperse resources among ROs to an extent any greater than that reflected in the proposals themselves.
Much of the decision-making that leads to the concentration we see takes place before a proposal is submitted, although it also seems that organisations that submit fewer proposals experience lower success rates. The effect is subtle, but it shows through in the final pattern of funding. The outcome is a superposition of all these decisions. On occasion, it’s worth taking some time to count the beans.
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