The European Union’s two-fold multilateralism in crisis mode: Towards a global response to COVID-19
Bibliographic record
Abstract
The European Union (EU) has been strongly criticized from the outset for its alleged mismanagement of the COVID-19 pandemic which began early in 2020. Several observers even predicted the end of European integration. This article examines how the EU has been managing the crisis, with a focus on how this has impacted its external relations, notably with Canada. It will argue that this crisis, as is the case with most crises the EU has gone through, has brought to light existing ambiguities in European governance, but that it has not led to fundamental questions about the EU’s and its member states’ overall commitment to Europe’s “two-fold multilateralism” (i.e., internal and external collaboration). EU representatives have re-emphasized this principle when reiterating the need for both European coordinated actions as well as a global response to the COVID-19 pandemic, working closely with their partners, including Canada. Therefore, amid the evolving and serious health-related and economy-related challenges, the crisis offers an occasion for the EU to strengthen and deepen both its integration and its global role.
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 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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.022 | 0.011 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".