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Record W3124824115 · doi:10.1177/0020702020985325

COVID-19: Is this the end of globalization?

2021· article· en· W3124824115 on OpenAlexaboutno aff
Shahar Hameiri

Bibliographic record

VenueInternational Journal Canada s Journal of Global Policy Analysis · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsGlobalizationFinancial crisisRivalryEconomicsInternational tradeChinaDevelopment economicsEconomyPolitical sciencePolitical economyMarket economy

Abstract

fetched live from OpenAlex

Lockdowns and border closures to manage the ongoing COVID-19 pandemic have caused the greatest global economic shock since the Great Depression. Does this also signal the end of economic globalization, the most significant trend of the past forty years? And if so, what kind of global political economy is emerging from the wreckage? In this article, I argue that COVID-19 is mainly intensifying pre-existing trends, set in motion by the global financial crisis of 2008 and the People’s Republic of China (PRC)’s economic rise. The disruptions to global supply chains wrought by COVID-19 have combined with rising United States–PRC rivalry, growing disaffection with the distributional impacts of global value chains, and automation to catalyze the turn away from globalized production. Meanwhile, amid the economic doom and gloom, financial markets are booming, high on the central banks’ liquidity injections to which they have been addicted since the 2008 crisis. As in the decade since the 2008 crisis, booming markets will likely deepen inequality and resentment, fuelling economic nationalism and eroding support for globalization even more. The governments of relatively small and open economies, such as Australia and Canada, will need to guide their economies more purposefully or find themselves at the mercy of the increasingly confrontational, yet domestically fragile, United States and the PRC.

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)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.871
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.027
GPT teacher head0.318
Teacher spread0.291 · 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

Citations20
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal Canada s Journal of Global Policy AnalysisSame topicCOVID-19 Pandemic ImpactsFrench-language works237,207