chapter 7 Evidencing Culture for Policy
Data and evidence in cultural policy
‘Facts about the Arts’ sets out to bring together some of the available statistics on the arts. Anyone who has the temerity to try to do this invites the scorn of those who believe that the concept of the arts itself is elusive and indefinable and any attempt to measure it cannot begin to represent its essential quality. Others, however, believe that the considerable body of material which does already exist can be gathered together and presented in such a way as to lead to a better understanding of the extent to which the arts contribute to the quality of life of the country. Amongst those potential users are Parliament, the media, the general public, and the many who have the power to influence and make decisions about the arts.
(Nissel 1983, 1)
Muriel Nissel was a British statistician and civil servant, who collaboratively created ‘a national survey analysing trends in social welfare’ which was to become Social Trends. Social Trends1 was a significant step in the history of UK statistics, as it symbolised a move away from tracking economic-only concerns to a more general concern with welfare.((A review of the first edition of the associated publication stated that Social Trends covered ‘public expenditure, leisure, personal income and expenditure, social security, welfare services, health, education, housing, justice and law’ (Rose 1970, 241).)) Nissel was, therefore, key to the social indicators’ movement, which coincides with what we have been describing as the ‘first wave of well-being’2. Nissel’s quote from her book, ‘Facts About the Arts: A Summary of Available Statistics’ (1983), points towards this imagined clash we have encountered between the arts and data((The above review of the first edition of publications reflecting on Social Trends lists the main areas of interest in a thought-provoking order, namely leisure is further towards the front of the list than you may expect, given what we have been led to believe are the priorities for evidence.)): that they somehow do not go together, and yet must be put together.
Evidence is a contentious idea for those working in or interacting with cultural policy (both narrowly and broadly defined). The idea that the arts and culture have a role to play in improving quality of life is inherent to the identity of cultural policy. We saw this, of course, when the Arts Council of Great Britain was created, as discussed in the previous chapter. This idea of the culture–well-being relationship has then become operationalised in policy, by which we mean, it has been ‘put to use’: in order to advocate for the social purpose and even the social value of the arts; even the value added of ‘culture’ for the well-being of the wider population in various ways. So, cultural policy research will often operationalise this assumed relationship between culture and well-being in terms of value (as social impact) using quantitative evaluations, and we will look at some attempts to do that in this chapter.
Box 7.1 Operationalisation as a Process in Research Operationalisation in research has a slightly different meaning than in everyday speech. It is the process through which you decide what you are going to measure to understand a concept. Or, more formally, it involves identifying measurable dimensions of a concept.
In this book, the main concept is well-being, of course; but along the way, we have also encountered other concepts, like poverty, social value and in this chapter, of course, culture.
How do you identify measurable dimensions of a concept? This could be designing questions that you can ask survey respondents or identifying data that are already out there (administrative data like hospital admissions are a good example). Measurement is about getting from the questions to the answers.
In some cases, it’s simple: operationalisation could be, for example, deciding that in order to understand ‘hospital capacity’ you will use average A&E waiting times as the measure.
But sometimes it’s intermediate: you might be interested in A&E waiting times overall; or average A&E waiting times for people under 18; or the percentage of people who wait more than four hours; or the longest anyone ever waited in a four-week period.
And sometimes it’s complicated: for example, you may be calculating a scale based on responses to loads of survey questions—where the operationalisation is ‘we’re interested in all of these questions to get at this concept’. Think of something that looks like the PANAS Questionnaire (Fig. 4.3). Instead of lots of different feelings and emotions (as in the PANAS), imagine lots of questions that are more specific, yet similar, about your mood. This could be an operationalisation of ‘anxiety’ or of ‘depression’.
If we want to understand the culture–well-being relationship— as policy, or in social impact—there are a number of ways we might operationalise culture and a number of ways we might operationalise well-being.
In statistics, operationalise, more specifically, would mean we need to find a concept from well-being data that is something measurable (a variable).
The following two chapters will investigate how the idea of a ‘culture– well-being relationship’ has been operationalised in policy, also looking at how it has been operationalised in research that is used to advocate policy decisions. This chapter problematises a number of aspects of the assumed relationship, by reconsidering how these concepts are operationalised in data. It also poses questions about why some data are utilised to reinforce long-held beliefs and values, when other data are readily available, yet are not used. Could it be that they do not allow for such a positive narrative?
Given that the value of culture is promoted for its positive relationship to well-being, and that this is partly to assure policy investment, we begin by looking at the relationship between data that capture changes in government investment in culture, and data that capture change in an aspect of subjective well-being. This exercise has two aims: to review the relationship from a different angle and to demonstrate how data can be found and used on websites that are accessible by everyone. We then look at ideas of being an artist and cultural work and compare two reports that use a similar methodology to analyse data from different countries. Again, this not only reveals something about the relationship between ‘culture’ and ‘well-being’, but also demonstrates how we can interact with research and evidence. Finally, we examine one piece of academic research that looks at ‘cultural access’ (participating in cultural activities) and well-being, to observe how this rendering of the culture–well-being relationship is evidenced in an academic journal article. While far from exhaustive, this chapter takes the key concerns of cultural policy: what gets funded, and to do what; who makes culture; who consumes culture; to look at them all in their own terms.
