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Record W3126172375 · doi:10.1016/s2542-5196(20)30291-6

COVID-19 and the collapse of global trade: building an effective public health response

2021· review· en· W3126172375 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Lancet Planetary Health · 2021
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsUniversity of Ottawa
FundersNational Institute for Health and Care Research
KeywordsPandemicRecessionGlobalizationCoronavirus disease 2019 (COVID-19)BusinessPublic healthEconomicsInternational tradeDevelopment economicsMedicine

Abstract

fetched live from OpenAlex

The scale of the COVID-19 pandemic is a consequence of international trade and globalisation, with the virus spreading along established trade and travel routes. However, the pandemic also affects international trade through reductions in both supply and demand. In this Viewpoint we describe the many implications for health and propose ways to mitigate them. Problems include reduced access to medical supplies (in particular, personal protective equipment and tests), budgetary shortfalls as a result of reduced tariffs and taxes, and a general decline in economic activity-leading, in many cases, to recessions, threats to social safety nets, and to increased precariousness of income, employment, and food security. However, in exceptional cases, the pandemic has also brought some transient benefits, including to the environment. Looking ahead, there will be great pressure to further liberalise rules on trade to encourage economic recovery, but it is essential that trade policy be informed by its many consequences for health to ensure that the benefits are maximised and threats are minimised through active identification and mitigation.

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.

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)0.024
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.520
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.141
GPT teacher head0.418
Teacher spread0.276 · 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