Pandemic Preparedness in the Live Performing Arts: Lessons to Learn from COVID-19
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This report summarises research and presents key findings and recommendations from the British Academy-funded Pandemic Preparedness in the Live Performing Arts project. Between April 2023 to January 2024, a UK-led research team with co-investigators in the USA, Canada and Germany and Research Associates in France, Italy and Japan examined the lessons learned from the responses of the live performing arts sector and governments to COVID-19 in the G7 countries. We focused our attention on policy interventions by governments and funders as well as the individual responses by workers in the live performing arts as well as organisations and their audiences. We further considered the impact of the pandemic on digital modes of working and disseminating creative content; how the pandemic affected communities, places and how ‘cultural value’ is understood; and what the pandemic revealed about systems and structures in the sector. The aim was to support sector preparedness for future crises, whether caused by new pandemics, climate-related disasters, demographic changes, economic pressures or the impacts on the live performing arts of national and international politics. This summary is written for readers in the UK and stresses points of convergence and lessons that can be learned from best practice elsewhere.<br/><br/>The detailed literature reviews covering all G7 nations which underpin this summary report are available.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it