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Record W3132832311 · doi:10.1177/0020702020987858

The European Union’s two-fold multilateralism in crisis mode: Towards a global response to COVID-19

2021· article· en· W3132832311 on OpenAlexaffabout
Chantal Lavallée

Bibliographic record

VenueInternational Journal Canada s Journal of Global Policy Analysis · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsRoyal Military College Saint-Jean
Fundersnot available
KeywordsMultilateralismEuropean unionCoronavirus disease 2019 (COVID-19)Political scienceCrisis responseMember statesPandemicPolitical economyCrisis management2019-20 coronavirus outbreakTransatlantic relationsEuropean integrationInternational tradeSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Development economicsSociologyEconomicsForeign policyLawVirologyOutbreakPoliticsPublic relationsMedicine

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.717
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.067
GPT teacher head0.518
Teacher spread0.451 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2021
Admission routes2
Has abstractyes

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