How data work in contexts
‘How data work in contexts’ collects together some of the research by Susan Oman (and others) that considers how different kinds of data work for and against people in various contexts. This includes looking at particular policy issues, such as: well-being; loneliness; inequality; class. It also involves looking at different domains: Higher Education; the cultural sector; non-governmental departments; commercial research sector. This work has emerged from working across different knowledge cultures: everyday, expert and their intermediaries.
Background and rationale
This direction of research approaches all kinds of data, rather than focussing on ‘big data’ or ‘survey data’ or ‘inequality data’. It looks at data in context to watch how they work, and how that affects or impact on different actors, groups and cultures. Some examples outlined here include people working in small charitable arts organisations, who feel the pressure of datafication, and aspire to harness data to improve efficiency and effectiveness. It also includes civil servants feeling unequipped to grapple with larger and more complicated datasets and data laws, or indeed, people who increasingly in their everyday lives feel less in control of their data.
Three main themes emerge from a series of selected research projects: Data and measurement in and for the cultural sector; The social life of data – how data in works in, for and against people and policy domains; Well-being – how data, power and voice work to obscure or reveal experience.
Theme 1: Data and measurement in and for the cultural sector
Misuses and misplaced trust in numbers?
The growing trend of econometric analyses of well-being data and data on cultural participation has changed the way that social impact is narrated across policy domains. In the case of cultural policy-making, this has led to headline arguments about particular activities, such as ‘Dancing makes people as happy as a £1,600 pay rise’. This open access journal article written by Susan Oman and Mark Taylor addresses some of the issues with this approach. It replicates quantitative analysis of secondary data and uses media, policy and market analyses of how these econometrics are used and are influential for the cultural sector and associated policy domains.
Review of Making culture count: the politics of cultural measurement
A review of a book on cultural indicators that ‘focuses on the ever-present issues of measurement and meaning in articulating value for cultural policy practices and research’. The full review is available in the journal Cultural Trends.
Critical engagement with the reported possibilities for big data in the cultural sector
This mini-review essay considers the claim that the cultural sector is “in need” of big data. The essay reviews a report called Counting What Counts: What Big Data Can Do for the Cultural Sector, arguing that in its keenness to articulate the value of big data, the report overlooks the values and working practices of the sector. It also failed to consider the cultural sector’s contribution to big data generation, the marked differences in both organisational scale and short-term capacity to engage fruitfully with ‘big data’ technologies. Furthermore, the essay points out that ‘culturally’ the sector is resistant to big data-driven programming, as the expertise of cultural sector practitioners, and ideas of creativity itself, could be framed as in opposition to this sort of data-driven decision-making.
Susan Oman and Mark Taylor (2018) ‘The New Models of Subjective Well-being in Cultural Advocacy and the Politics of Research’, Journal of Cultural Economy. Vol 11, issue 3. DOI: 10.1080/17530350.2018.1435422
Susan Oman (2016) Making culture count: the politics of cultural measurement, Cultural Trends, 25:2, 135-137, DOI: 10.1080/09548963.2016.1170920
Susan Oman (2013) Review of ‘Counting What Counts: What Big Data Can Do for the Cultural Sector’, Cultural Value Initiative, May 2013
Theme 2: The social life of methods – how data in works in, for and against people and policy domains
The ‘social life of methods’ is a body of research proposing that methods are not neutral ways of capturing an objective reality, but have their own social effects, in fact, changing the reality they claim to capture. Data: how it is collected, shared, analysed and where the results are published are a fundamental part of this. This section highlights work that engages with some of these tensions in the role of data in real world contexts.
Re-performing data collection and analyses to reveal inequities of knowledge production
This book chapter reflects on empirical findings and methodological developments that emerged from investigating the use of data in the well-being agenda and cultural policy.
A cultural studies approach to understanding the value and values of different kinds of survey data.
Datasets that are ordinarily overlooked or marginalised in evidence-based policy-making, such as free text fields, reveal important policy solutions – and how people feel. This open access article uses a cultural studies lens to consider the values and value of different types of well-being data and evidence for policy-making, and the narratives which emerge from them. It presents secondary analyses of Office for National Statistics data from the Measuring National Well-being (MNW) debate (2010). Using Raymond Williams’ framework of ‘lived culture’ and ‘recorded culture’, the article interprets analytical discrepancies between the Findings of the Debate report and what people said in the debate. The article argues that the discrepancy demonstrates what Williams calls the culture of the ‘selective tradition’. Williams’ work is used to, firstly, address a methodological bias against free text data, and secondly, cultural sector advocacy, which prioritises profiling the activities which fall into its sector, not those that are most valuable to people. Revealing these two selective traditions in the discussion of well-being evidence, this article aims to prioritise everyday understandings of well-being over those of experts, offering an ethical and practical contribution to policy-making for well-being.
Susan Oman (2019) ‘The ‘selective tradition’ in well-being evidence for policy’ Leisure Studies, special issue on well-being policy and research. DOI: 10.1080/02614367.2019.1607536
Susan Oman (2019) ‘Re-ordering and re-performing – re-placing cultural participation and re-viewing well-being measures’, Cultures of participation – arts, digital media and cultural institutions (ed.) Birgit Eriksson, Carsten Stage & Bjarki Valtysson. Routledge.
How people feel having their personal data collected in the cultural sector?
This section of Theme 2 reflects on a project that emerged from AHRC-funded: Data, diversity and inequality in the creative industries and What constitutes ‘good data’ in the creative economy?. The project was designed to understand how data works across the cultural sector with practical aims: to help improve sector data practices; work with Arts Council England to advise on their development of a new class metric; improve equality monitoring data in the sector.
Building an accurate picture of social inequality is key to understanding how to address it. Equality monitoring of the workforce across business sectors and policy domains is a long-established practice, providing analyses such as the gender pay gap, for example. Yet, requests for people’s protected characteristics to understand diversity issues is frequently met with suspicion. Susan Oman investigated how data are collected, analysed, valued, shared and published, and the quality and ethics of these data processes.
Two formal publications contain findings and recommendations on this project to address the lack of systematic data on class in the cultural sector and wider quality monitoring data processes. The working paper, with findings, recommendations and an accessible literature review, is aimed at the cultural sector. The policy briefing, aimed at the creative and cultural industries, that can inform all sectors and domains on equality monitoring.
In A Question of Class?, a blogpost for the funders, the Arts and Humanities Research Council (AHRC), Susan argues that context is key to understanding how new measures will work in practice – and the issues they raise for people and the sector. For Arts Council England, she wrote about how we might collect and use data to tackle The Inequality Challenge in the Arts. This looked at how diversity data are collected and reflected on how people who work in arts organisations feel talking about class. It argues that to understand class inequalities across the cultural sector, people need to be asked questions in a way that does not make them feel uncomfortable or judged. More importantly, though, inequality is a discussion for everyone. Not just researchers, journalists or people seen to have the power to change things. Things can only become equal if we are all involved in the conversation.
References
Susan Oman (2019) Improving data practices to monitor inequality and introduce social mobility measures – a working paper for the cultural sector, The University of Sheffield
Susan Oman (2019) Measuring Social Mobility in the Creative and Cultural Industries – the importance of working in partnership to improve data practices and address inequality, A Policy Briefing, The University of Sheffield.
Susan Oman (2018) A Question of Class: how do social inequality metrics work in cultural organisations?, Arts and Humanities Research Council blogpost, September 2018 discusses initial findings.
Susan Oman (2018) The Inequality Challenge in the Arts, Arts Council England blogpost, 10 September 2018 reflects on how we talk about class, and how we tackle ‘the inequality challenge’ using data.
Theme 3: Well-being
Understanding well-being as a policy issue and an everyday experience
This section looks at how using marginalised data help understand power and address issues of voice. It looks across policy-making contexts, such as Higher Education and national government.
The first piece of research is a chapter on the Measuring National Well-being debate from 2015. This chapter problematises the finding that many people who used the online survey to respond to the debate questions, felt inclined to use free text, rather than relying on a tick-box to represent their thoughts on what matters. Using these data, the chapter distinguishes between the survey authors and participant authors. The survey authors wrote the survey questions with their own agenda in mind: designing indicators that are efficient and effective within the current structures and practices of national statistics. On the other hand, the participant author is trying to communicate their answer to the question ‘what matters to you’, finding themselves unable to do so appropriately in the tick-box options. The chapter explores how these different cultures of expertise meet in the survey, but only one kind of knowledge gets to reproduce itself within the existing system.
Oman, S. (2015) ‘‘Measuring National Well-being: What Matters to You?’ What Matters to Whom?’, in Cultures of Wellbeing Method, Place, Policy (ed.) Sarah C. White. Palgrave MacMillan. DOI: 10.1057/9781137536457_3
Why government issued well-being may not make us happier
Published highlights of Susan’s interview with sociologist and political economist Will Davies in The Conversation, May 2015. The interview covers how governments and big business have used various techniques to understand our well-being and use this data to explain it back at us.
Student experience metrics and student well-being
Student experience metrics, such as the Postgraduate Research Experience Survey (PRES) and National Students Survey (NSS) do not improve understanding of how students really experience university, or how marginalised students are at increased risk of ill-being.
In an article for Times Higher Education (THE), Susan argues that the increasing attention paid to the mental health and well-being of students is welcome, much needed and overdue, but that action is flawed. She reflects on her work for the University of Manchester’s Students’ Union: a year-long investigation into well-being across the PhD community, involving ethnographic analyses of policies, systems, focus groups and the reanalysis of free text from the Postgraduate Research Experience Survey (PRES).
Data and its shortfalls in understanding access, success and student experience
Getting ‘in’ and getting ‘on’ in Higher Education (HE) are two issues that are often conflated in ways that ignore what it might mean to ‘get by’ in a University. Shortfalls in access data to represent inequality of experience might be addressed by the recent fascination with monitoring and stratifying ‘success’ and ‘the student experience’. This blogpost from Oman et al. reflects on the capacity of NSS to address understanding of inequalities of experience in HE. The authors argue that ‘despite hopeful claims to the contrary, neither the experience of a homogenised student body, nor those who are marginalised from it, seem to be serviced effectively by the ‘student experience’ initiative’.
Susan Oman (2017) ‘Student Experience Survey 2017: investigating well-being at university‘, Times Higher Education, 27 March 2017
Susan Oman, Jon Rainford & Hilary Stewart (2015) Access in Higher Education: A triumph of hope over experience? Discover Society, December 2015.