Responding to Mpox: Communities, Communication, and Infrastructures
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
Executive Summary<br/>The 2022 Mpox outbreak saw community organisations and sexual health services rise to the challenge of rapidly responding to a public health emergency. Nevertheless, the experience showed that successfully responding to an outbreak is often dependent on preparedness, planning, and existing infrastructure, and success in future outbreaks and scenarios may depend on this work being undertaken now.<br/>This report sets out key findings about the successes and challenges in the response to Mpox in the UK and internationally and makes research-based policy recommendations for future similar contexts. These include suggesting that:<br/>• Collaborative relationships with community organisations should be proactively<br/>fostered before an outbreak occurs, to build preparedness and resilience; and that<br/>• Governments should appreciate and appropriately resource social and medical<br/>infrastructure, including sexual health services, as these are key actors in responding to an outbreak such as Mpox.<br/>For other future scenarios including a potential rebounding of cases, the report further recommends actions including:<br/>• Deploying successful interventions such as co-producing messaging with and for affected communities; and<br/>• Targeting support to those facing additional barriers to accessing healthcare.<br/>The full list of key findings and policy recommendations is collated on the next page.<br/>The report also sets out further avenues for research illuminated by the project and its findings.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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