Chapter 1 Introducing well-being data
Who is this book for?
For people who work in social and cultural policy and charities, this book offers lots of context to the data they use every day and aims to help everyday usage of data in practice. It hopes to speak to people who think they can’t do numbers at all. This includes those who think they do not understand the numerical aspects of arguments that use data. It also includes understanding the arguments themselves and potentially their limits.
Capability, capacity and confidence with data are issues for researchers and practitioners working in cultural policy and the sector . Organisations and individuals are affected differently by data-related issues, depending on various matters, including who funds them, how large and ‘professionalised’ the organisations are, for example ((Oman 2019a, b, 2020)). Despite increasing emphasis on the importance of data in social policy and cultural policy practice and research, capability, capacity and confidence have not received much attention.
Alongside some evidence of data gaps in social and cultural policy, there is anecdotal evidence that key arguments relating to the value of particular social policy areas remain obscure to some working within them, because of the way data are expressed. For social and cultural policy researchers and students, who are not comfortable with numeric data and the way they are presented, this book aims to open the black box and shed light on what is happening. Looking under the bonnet of data means peering under the cover of the workings, the arguments made, the evidence used and the connection between them and data. Looking at all these components together helps us better understand well-being and data at the same time.
For readers who are happy with analysing data and reading statistics, the book reveals some of the social or political ramifications of data and their uses. How governments ‘follow the data’ as a way of justifying policy decisions has been foregrounded in COVID-19 times. Revealing the implications of using the idea of data to justify bad, even dangerous decisions, does not mean all is fixed, however. The enduring presence of the pandemic should be the motivation to ask more questions about policy decisions that claim to be fair and equitable based on evidence using specific data, but which are often just the opposite. Understanding well-being data in these broader contexts is therefore critical.