Digging deeper into open grants data: why might we find variations between communities?

The open grants data movement is gathering pace with the recent demonstrator project from 360 Degree Giving and there are some interesting demonstrations of how to visualise this material here. Given the volume of data they’ve now released – 240 000 grants, totalling some £16Bn – we need to think how to interpret these figures. In my previous post on open grant data I pointed to one of the challenges: how should we interpret the clear socioeconomic gradients in the likelihood that registered charities received awards from a national funder. The regional distribution showed that the probability of receiving a grant was higher in areas of disadvantage like North East England. Within regions there was a broadly similar position: it was found that the more disadvantaged the area, the higher the proportion of charities receiving funds. One point to remember immediately is that these figures were proportions – so you also need to factor in the lower numbers of charities in the deprived areas. This means that while there was a degree of progressivity in the likelihood of receiving awards, this wouldn’t change the distribution of funding enormously.

Social scientists often use metaphors like peeling onions to describe the process of digging through complex layers of reality. That seems very appropriate here because of the numerous possible causes of the patterns we describe. The gradients could reflect some, or all, of the following:

The pattern of applications: it could be that the application rate varies between communities and the proportion of charities receiving awards might vary simply because more charities apply from some areas compared to others. This could be because other funding sources are available in some areas (e.g. other charitable trusts) or it could be because the funder is devoting attention to securing more applications from particular places. Or, as often argued by voluntary sector representatives, this could be a function of the availability of the local infrastructure: the support services provided to organisations by Councils for Voluntary Service (CVSs) and similar bodies.

The distribution of eligibility: before concluding that there was an absence of activity we would need to know about whether or not charities were eligible to apply for particular programmes. The needs and causes which are addressed by funding programmes are diverse – we would not expect a funder of projects to do with coastal conservation to get many applicants from the West Midlands, for example.

The size of the awards: the presence or absence of awards is only one indicator – another might be the amount of funding awarded: a large award spread over several years could be of more value than a succession of small annual awards, and organisations might decide to put more effort into a smaller number of bids.

Complementary providers of services: what is the balance between different legal forms receiving awards in different areas? Since some funders are open to applications from public sector agencies, schools, etc., the absence of awards to charities doesn’t mean that other agencies don’t receive funding. This ties into the question of eligibility, above.

It could also be that strong public sector agencies (community centres which are run directly by local authorities, for instance) fill the gap. And there could be other sources of social action in communities both in the third sector and elsewhere, as Diane Coyle points out: one of the reasons the “charity deserts” rhetoric of the Commission on Social Justice is an oversimplification.

Other funders: a low proportion of charities receiving awards in one area could be because there is another strong funder in the area, which is well-connected with local charities, and may well have an informal working relationship with other funders. Without information on who else is funding what in which community, we can’t say with certainty what the pattern really tells us. We need therefore not just data on individual funders, but data on all funders, if we are to make progress. And we also need better information on other sources of income received by third sector organisations.

Differences between applicants and recipients of awards: this would be really interesting and relevant if you wanted to try and look at the effect that receipt of an award has on an organisation. Sarah Smith has done some work on this. She was provided with application data as well as award data, and then compared organisations that had passed a scoring threshold but not been funded, with those who were funded. She found that the particular grants programme had indeed made a difference to the fortunes of recipients, at least over the six years covered by the data she had available.

There are no doubt other reasons for the patterns we observe. Understanding the pattern of awards and its relationship to social conditions would be a good starting point; understanding the overlap between funders would begin to take us further. Ultimately it would be useful to know much more about how various funding streams interact, how organisations change their behaviour in response to funding opportunities, and how systems might be developed in which resources reach those most in need of them.

 

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