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Record W2504920912 · doi:10.1057/9780230251007_6

US Under Stress: Free Trade and Fracture in the National Regime?

2009· book-chapter· en· W2504920912 on OpenAlexaboutno aff
Ben Richardson

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2009
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsInternational tradePosition (finance)AgricultureEconomicsInternational economicsEconomyPolitical scienceBusinessGeographyFinance

Abstract

fetched live from OpenAlex

The previous chapter outlined how the EU regime inherited from the national era was made consonant with the imperatives of the contemporary trade environment but with significant concessions that left its key protective measures intact if not inviolate. This chapter turns our attention across the Atlantic and moves to examine the evolution of the national regime in the US. Out of the three economies in North America, focus on the US is apposite here both because of its market importance (in 2006/07 the USA consumed 9.23mt of sugar, Mexico 4.98mt and Canada 1.43mt) and its political influence (ISO 2008: 15). As outlined in Chapter 4, the type of agricultural support adopted in the US was of crucial significance to the rules adopted within the trading system at large. This remains the case today. Through its position as the biggest agricultural exporter and its material and institutional power in the global trade architecture, the policy vision emanating from the US has had direct consequences for global agricultural trade. Within this vision, sugar has been a notable exception to the general thrust of aggressive market opening. During the Uruguay Round for instance, since the US had lowered its average trade distorting support under the 1990 Farm Bill and because tariffication and minimum market access provisions in sugar had already been set in place, there was no need for adjustment, and certainly no effort made to make this otherwise. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.003
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 score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.017
Scholarly communication0.0100.008
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0120.001

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 head0.024
GPT teacher head0.220
Teacher spread0.196 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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