Europe and the Covid-19 crisis: The challenges ahead CEPS Policy Insights 11 Sep 2020.
Bibliographic record
Abstract
The European economy is now recovering briskly, after an unprecedented fall in output during the second quarter of 2020. But this recovery is likely to be incomplete for some time, not least because of the substantial degree of social distancing measures still in place. The defining feature of the present situation is that the remaining demand and supply obstacles are highly sector specific. Aggregate demand management will thus be less effective. Income replacement measures, such as short-term work schemes, will be needed for some time, but should be applied flexibly to support rather than hinder structural adjustment. This also applies to the funds to be made available under the €750 bn Recovery and Resilience Facility. Money is fungible. This means that the key for success will not be the projects to be financed by the RRF, but whether member states undertake structural reforms that increase their growth potential.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.010 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.005 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".