Bibliographic record
Abstract
Professor Frank Peck, of the University of Cumbria’s Centre for Regional Economic Development,says we must look beyond the current Covid-19 crisis and hope for a less pessimistic future. \n \nThe first quarter of 2020 will be remembered. Only a few weeks ago, we might have thought that the UK’s formal departure from the EU on January 31 would be the standout event. But in the short term, leaving the EU has been completely overshadowed by the threats posed by the spread of Covid-19. Officially declared a pandemic by the World Health Organisation on March 11, the situation has developed rapidly. There is still much uncertainty surrounding the details of this disease; exactly how it spreads; how contagious it is; when it might reach a peak in different countries; what impacts the mitigation measures might have on economies. Experience of previous outbreaks of disease has clearly informed responses to the current crisis. While one outbreak cannot be used to predict the precise outcome of another, previous research does provide understanding of the types of economic impacts that are likely.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.013 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".