1. Demographic indicators of cultural consumption UPTAP Workshop, University of Leeds 23 March 2007 Orian Brook, Audiences London & University of St Andrews Paul Boyle & Robin Flowerdew, University of St Andrews

2. Background

3. Why is this project important?  Mounting interest in evidence-based policy in general  Specifically in the subsidised arts sector – who benefits from the investment?  Agencies collect box office data from arts venues for marketing and other purposes  User fellowship will enable more sophisticated and robust policy-related conclusions to be drawn from these data

4. Previous Studies  Arts Council & Department for Culture, Media and Sport rely on large-scale surveys to investigate effectiveness of cultural funding  Target Group Index Survey (since 1985)  Arts Council England Arts in England (2002)  Department for Culture, Media & Sport Taking Part (2006)  Venues have also relied on audience surveys (generally not well sampled)

5. Theorising Cultural Consumption  Social inequality and patterns of cultural taste and consumption are the subject of a large and complex debate  Related to social class, education, status order (Weberian distinction)?  Three broad theoretical approaches…

6.  Homology argument  Prevailing structure of inequality within a society and cultural stratification map onto each other closely  Higher social classes prefer and consume ‘high art’  Arrogation of ‘distinction’ in cultural taste and processes of ‘aesthetic distancing’ (Bourdieu 1984)

7.  Individualisation argument  In ‘modern’ society the differences in cultural taste and consumption are diminishing  Growing ability of individuals to free themselves from social conditioning  People choose and form their own distinctive identities (Bauman 1988)

8.  Omnivore-univore argument  Challenges ‘homology’ and ‘individualisation’ arguments  Sees cultural differentiation as mapping closely to social stratification  But not necessarily on an ‘elite-to-mass’ basis  Cultural consumption among those in higher social strata is wider in its range  Distinction between cultural omnivores and univores, rather than elite and mass (Peterson & Simkus 1992)

9.  Chan & Goldthorpe consider various artforms  Latent class analysis of data from ACE Arts In England survey  Weberian distinctions of social class and social status  Suggest an omnivore / univore pattern, socially differentiated largely by status rather than class

10. But …  To an extent cultural consumption is chosen to aspire to or claim a social status  Reporting of cultural attendance in surveys is problematic – respondents may answer according to their identity rather than their visits  Can work positively and negatively  People may claim attendance at certain cultural events that accord with their self image  Deny attendance at certain artforms if they feel they do not represent who they are

11. Administrative data  Growing awareness of the value of administrative data  Avoids issue of claimed cultural attendance  Enables more detailed analysis of attendance  Different geographical contexts  Changes over time  Impact of policy change and provision  Drawbacks include  Data represent purchasers not attenders  Proportions of data capture vary enormously  Not all venues are included  However, much of this can be accounted for

12. London dataset  Box Office data collected from each venue  Events coded into artforms  Name and address records are matched at household level for 2003-2006  ~ 3 million households  ~ 8 million transactions  ~ 23 million tickets sold  ~ £400 million revenue

13. London venues who provide data Albany, Deptford Almeida Theatre artsdepot Barbican Centre Battersea Arts Centre Bush Theatre Croydon Clocktower Drill Hall English National Ballet English National Opera Greenwich Theatre Queens Theatre, Hornchurch Royal Albert Hall Royal Court Royal Festival Hall Royal Opera House Sadler's Wells Shakespeare's Globe Soho Theatre Theatre Royal, Stratford East Watermans Young Vic Hampstead Theatre London Philharmonic Orchestra London Symphony Orchestra Lyric Hammersmith National Theatre Open Air Theatre Philharmonia Orchestra The Place Polka Theatre

14. Representation of Artforms  Very Good  Classical music  Opera  Ballet & contemporary dance  Subsidised theatre and musicals  Patchy  Jazz and world music  Commercial theatre  Talks, workshops, literature and poetry events  Poor  Commercial musicals  Visual arts and museums  Cinema

15. Research to Date

16. Geographic Penetration: National Percentage of households in each postal sector attending London venues over 4 years Reached 7.4% of GB households 33.4% of London households

17. Geographic Penetration: London

18. Ticket Yield Average ticket price paid by attenders from each postal sector – those travelling further pay more

19. Venue Crossover  A common assumption is that ‘high art’ is over-supplied in London and that there is heavy competition for audiences  In fact, only 11% of the Barbican and the Royal Festival Hall’s audience for orchestral music attended both venues  Only 12% of English National Opera and the Royal Opera House’s audience attended both venues  Some evidence that following venue closure audiences just stop coming

20. Correlation of Snapshot penetration at Output Area level within London Strong positive association with education, but a weaker statistical association with Socio-Economic Group

21. Planned Analysis

22. Research Questions  What are the best geodemographic and socio- economic predictors of arts attendance?  Do these vary for different geographical regions?  Do they vary for venues focussed on “high art” compared to more populist or community-centred venues, or for venues in urban centres versus more rural locations?  Do they vary for different art forms (e.g. theatre versus dance)?  Do they vary for national venues versus those that are aiming to provide for more local audiences?

23.  Do they vary according to the number and diversity of performances available in a local region?  Has the usage of different venues by different socio- economic groups changed over time?  Do the distances that people will travel to venues vary by venue, demographic and socio-economic group and geography?  How does the opening of new venues or closure of existing venues (temporarily or permanently) affect the make-up and behaviour of local arts patrons?  Do some geodemographic classifications give better discrimination than others when analysing arts attendees?

24. Innovations  Extra data integration  Joining/comparison of attender data for venues in London and other regions  Use of Census data, including NS-SEC, qualifications, deprivation indices, age, ethnicity  Investigate the creation of a small-area Cambridge score  Exploring the geo-demographic profiles of small areas in more detail

25.  New methods of analysis  A focus on ‘small-area behaviour’ rather than households  Latent class analysis of small areas  Longitudinal modelling of flows of customers to different types of venue, by area characteristics  Explore how patterns change over time  Do we observe homologous, individualised or omnivore-univore areas?

26. Conclusion  Integration of large-scale secondary datasets to explore cultural consumption  Training in longitudinal methods and more advanced statistical modelling  Identification of intelligent clusters of arts attendance areas (AAAs)  Which theoretical approach best describes the AAA’s cultural consumption?

28. Socio-economic penetration