As Unlimited transitions into an independent organisation, it’s more important than ever to find out who applies, who gets funded, and crucially, who might be missing out. To find out more we analyse data at three points within our open commissions round – when people first apply at Expression of Interest (EoI) stage, once we have a shortlist, and once we have awarded commissions. We measure across all areas within our equal opportunities form, plus in relation to artform and geography.
The gaps are as important as the achievements. They can show if there is a group or sub-set of disabled people we are just not reaching at all, from whom we might never receive Expression of Interest applications in the first place. This might highlight areas for future outreach, development, or partnership. Or gaps can be found within the process – where applications are made, but people within those groups or sub-sets do not make it through to the shortlist and/or receive awards. This might suggest unconscious bias within the decision-making process and/or panels, or highlight training needs for those applying.
You can download and read the full report, but here’s a summary…
We have to compare our data against something to see if there is a gap. Although our data comes from England, Scotland, and Wales – we’ve used Arts Council England data and the Office of National Statistics figures for the percentage of the working age population in England to give us a start.
New to Unlimited
One of the most striking things is the high proportion of artists and companies that we support who have never been previously funded by Unlimited. The percentage in the shortlist was 68%, rising to 70% for those awarded grants.
What does the data show?
There are many positives:
- We have a broad range of ages applying and being awarded,– from 18 to over 65. ACE don’t report this so we can’t compare data.
- The numbers of those applying who define as straight/heterosexual are just over 50% leaving the remainder defining somewhere along the LGBTQIA+ spectrum. ACE figures show between 32 and 56% of the value of their recent awards going to artists who are LGBT, so this is fairly similar.
- Between 53 and 61% of our applicants and awardees identify barriers in their life as a result of self-defining as working class. Data on numbers of working-class artists is hard to find – but the Panic! 2018 – It’s an Arts Emergency! Report estimates them to be one third of the sector.
There are some areas where we may choose to explore more in the future:
- Few applicants have ever been a refugee or asylum seeker at any point
- 13-19% of our applicants and awardees have experienced barriers because of their country of origin
- Under 15% of our applicants and awardees have experienced the criminal justice system
- We receive and support almost twice as many female-identifying artists compared to male-identifying. ACE figures show a different picture with around 38-39% of the value of their awards going to artists who are female identifying. For Unlimited, we have between 7 – 9.4% of applicants as non-binary. ACE do not currently report non-binary statistics.
Whilst we use the term ‘disabled people,’ in line with the social model approach we take, we asked people to define using terms they prefer. The majority of people prefer to use the term ‘disabled person.’
There were some responses that are perhaps not surprising but that show the increasing difficulties faced by many disabled artists: over half our disabled artists describe themselves as precariously employed and/or on a zero hours contract and a large number of applicants (26.2%) have experienced homelessness.
We currently collect data on ethnicity and have formally reported in summary on the ‘four white categories’ and then those defining within ‘minority ethnic’ categories. This is no longer appropriate and we need to give urgent consideration to better ways of future reporting.
The majority of our applicants and awardees are White British (59-67%) and 21% of our applicants and 30% of those awarded define as People of Colour. This compares to Office of National Statistics: 17% ethnic minorities.
The terminology around ethnicity is rapidly evolving. Other organisations are using terms such as People of Colour, BIPOC (Black, Indigenous and People of Colour), person who is racialized with experience of racism, global majority, and more. Further investigation and discussion are needed before we determine the way in which we monitor this area.
Geography and artform
We had most applications from London based artists but awarded most to those from the Midlands. The lowest number of applications came from the south west and the lowest volume of funds went to the south east.
Most applications and awardees defined their artform as combined arts. Literature had the lowest number of applications and dance the lowest number of awards, although it is hard to fully understand any gaps relating to artform, due to the high number of combined arts applications.
The key reason for asking additional questions on our equal opportunities form wasn’t to specifically look at those dedicated areas, but to help us look from an intersectional perspective – are people who face intersectional barriers being additionally penalised through our processes?
Conversely, the opposite appears true. In most categories there is a small percentage increase between those applying and gaining awards.
Given that Unlimited is known for its intersectional approach, and that its selection panels are 50% disabled people and include those with lived experience of diverse backgrounds, this perhaps is unsurprising. According to the data we’ve collected, no commissioned artist in this round faces only one barrier.
What will Unlimited do now?
As Unlimited transitions into independence, it needs to determine what it measures, how, and why, and give further thought to the terms it uses. There is a real balance to be struck between the freedoms we can offer to enable people to use the terminology they prefer and not the terminology we prescribe, and the reporting that may be most useful – which is often against data sets using different terminology and definitions.