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Record W4323315157 · doi:10.1177/00438200231160775

THE STILLBORN UNITED KINGDOM‒UNITED STATES TRADE AGREEMENT

2023· article· en· W4323315157 on OpenAlexaff
Sangeeta Khorana, William A. Kerr

Bibliographic record

VenueWorld Affairs · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsKingdomPrime ministerBrexitPoliticsAdministration (probate law)Political scienceOptimismWork (physics)LawPublic administrationPolitical economyEconomicsInternational tradeEngineering

Abstract

fetched live from OpenAlex

With Brexit done and the desire to alter U.S. trade policy in the wake of the election of President Donald Trump, both British Prime Minister Boris Johnson and President Trump were optimistic that a trade agreement between the United Kingdom and the United States could be swiftly negotiated. This proved not to be the case despite the efforts of both leaders. We use an Open Economy Politics lens to examine the political and economic forces at work in both the United Kingdom and the United States during the tenure of the Trump administration that led to the initiative being stillborn and why the original optimism was misplaced.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.051
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0100.003
Open science0.0000.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.002

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 head0.041
GPT teacher head0.247
Teacher spread0.206 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2023
Admission routes1
Has abstractyes

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