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Record W4232584708 · doi:10.1108/oxan-db244672

Unstable politics may make trade deals uncertain

2019· other· en· W4232584708 on OpenAlexaboutno aff

Bibliographic record

VenueEmerald expert briefings · 2019
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic, financial, and policy analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBrexitNegotiationInternational tradePoliticsGovernment (linguistics)Trade barrierInternational economicsIdeologyPolitical scienceFace (sociological concept)Investment (military)Foreign direct investmentDivergence (linguistics)EconomicsBusinessEuropean unionLawSociology

Abstract

fetched live from OpenAlex

Subject Politics and trade talks. Significance Understanding the factors that determine how long trade negotiations take will help businesses navigate the uncertainty, as the UK government prepares to negotiate trade agreements once it leaves the EU. The Comprehensive Economic and Trade Agreement (CETA) between Canada and the EU took seven years to finalise. Less comprehensive renegotiations of international agreements can be shorter, including the US-Mexico-Canada agreement, which took less than two years. Impacts UK sectors highly exposed to the EU or United States, including automotive and financial services, face prolonged investment uncertainty. Timing of national elections, lobbying and the ideological divergence between trade partners will determine post-Brexit trade deal talks. Continued polarisation of major economies' electorates will delay or stop other global deals, including on foreign aid and climate change.

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)0.008
metaresearch head score (Gemma)0.023
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: Commentary · Consensus signal: none
Teacher disagreement score0.071
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.006
Scholarly communication0.0190.009
Open science0.0010.006
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0710.011

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 head0.035
GPT teacher head0.253
Teacher spread0.218 · 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
GenreCommentary

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

Citations0
Published2019
Admission routes1
Has abstractyes

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