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Record W3209845496

The Covid-19 trade contraction: A view from global shipping, the EU and China

2020· preprint· en· W3209845496 on OpenAlexaboutno aff
Sonali Chowdhry, Gabriel Felbermayr, Vincent Stamer

Bibliographic record

VenueEconstor (Econstor) · 2020
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Zones and Regional Development
Canadian institutionsnot available
Fundersnot available
KeywordsChinaInternational tradeQuarter (Canadian coin)Coronavirus disease 2019 (COVID-19)BusinessValue (mathematics)Global value chainInternational economicsTrade volumeEconomicsGeographyComparative advantage
DOInot available

Abstract

fetched live from OpenAlex

This policy brief examines the effects of the Covid19 pandemic on international trade. Major exporting economies have posted record year-over-year monthly declines in export volume ranging from -7.9% in Germany to -24.3% in South Korea. While logistical bottlenecks are being solved, low demand puts pressure on trade activity. The shipping industry has reduced its activity around Europe, Asia and America by up to -10% pointing to a prolonged reduction in trade. Over the first quarter of 2020, China's trade contracted severely with most economies - particularly Canada, Japan, Russia, Italy and South Africa.The trade collapse affects businesses differently and especially hits those firms that participate in low-value added stages of global value chains by assembling components.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0020.002
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 head0.044
GPT teacher head0.245
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2020
Admission routes1
Has abstractyes

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