UK Museums during the COVID-19 crisis: Assessing risk, closure, and resilience
- Funded by UK Research and Innovation (UKRI)
- Total publications:0 publications
Grant number: AH/V015028/1
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Key facts
Disease
COVID-19Start & end year
20212022Known Financial Commitments (USD)
$211,435.68Funder
UK Research and Innovation (UKRI)Principal Investigator
Fiona CandlinResearch Location
United KingdomLead Research Institution
Birkbeck, University of LondonResearch Priority Alignment
N/A
Research Category
Secondary impacts of disease, response & control measures
Research Subcategory
Economic impacts
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Adults (18 and older)
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
Museums are a vital part of the UK's cultural and economic landscape. In England alone, they attract 100 million annual visits and have a turnover of £2.64 billion per annum. Senior staff in governmental and non-governmental museum agencies are deeply concerned that many museums will not survive the impact of COVID-19 with a correlative loss to the cultural and economic landscape. Although museum agencies are urgently seeking funding and developing policy to manage the impact of COVID-19, they do not have established mechanisms for gathering comprehensive data on the UK museum sector, for tracking which museums are at risk of closure, and which actually close. Thus, they proceed with inadequate information. This project will provide museum agencies with rigorous, timely data on which museums are at risk of closure, which museums close, which remain resilient, and how the profile of the UK museum sector changes as a result of COVID-19. We will develop indicators for risk and resilience that are applicable within the current crisis and assess whether the closures that occur have a disproportionate impact on particular audiences and localities. The research draws on the expertise of an existing research team and combines quantitative and qualitative techniques including web-scraping, natural language processing, interview-based research, and primary data collection.