Covid-19 Cultural Participation Monitor: Inequalities through Covid-19
Looking at Cultural Participation Monitor data to see who is more negatively impacted and how that relates to, or exacerbates, previously existing and ongoing inequalities in audiences.
This report is part of a national research programme led by the Centre for Cultural Value in collaboration with the Creative Industries Policy and Evidence Centre and The Audience Agency. The project is funded by the Arts and Humanities Research Council (AHRC) through UK Research.
COVID has been, to quote the title of the Centre for Cultural Value event in this topic, ‘The Great Unequalizer’.
In the first summary report from the Cultural Participation Monitor the report emphasises that it has impacted everyone: mostly negatively, but differently. Here, however, the report focus specifically in on inequality in its impacts.
This report lays out evidence to support the following four-part argument:
- Cultural engagement was unequal before COVID,
- The impacts of the pandemic have been experienced unequally, reinforcing this existing inequality,
- Further inequalities have developed in terms of health impacts and vaccination,
- And the result it likely to be increases in inequality in cultural engagement into the future.
Some of these findings are unsurprising; others benefit from additional nuance. It provides the latter where it can, but also recommend further exploration via the Taking Part and Active Lives Surveys, with their larger samples and different questions.
Since the impacts of COVID and inequality are only two of many topics that have been of interest in designing the survey, the report only covers what has been asked about particular aspects of them. For example, (at this stage) details of health, well-being or bereavement has not been asked . Similarly, occupational status and role types have been asked, but not potentially more sensitive questions about furlough, redundancy or class. As a result, the report looks at the impact of COVID mostly in terms of people’s amount of free time and money. It also differentiate groups by occupation type and other demographic characteristics (such as age, ethnicity, disability), as well as Audience Spectrum (a population classification based on how people tend to engage in cultural activities).
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