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Record W2104879077 · doi:10.5539/ass.v6n7p29

On British-American Special Relations through 9.11 Event

2010· article· en· W2104879077 on OpenAlexvenueno aff
Renfeng Zhang

Bibliographic record

VenueAsian Social Science · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Political and Economic Relations
Canadian institutionsnot available
Fundersnot available
KeywordsTerrorismSpecial Interest GroupPolitical scienceInternational relationsConsistency (knowledge bases)Special RelationshipEvent (particle physics)History of the United StatesPolitical economyLawSociologyPolitics

Abstract

fetched live from OpenAlex

For a long time, America and Britain have been keeping a kind of special relations. Britain has always been the follower of America in many international issues, and paced with America accordingly. When 9.11 Event broke out, Britain still was the first one who wanted to cooperate with America to fight against terrorism. In the process of European integration, Britain was relatively isolated, known as “Europe’s orphan”. Strengthening the special relations with the United States, can not only enhance the status of the United Kingdom in Europe, but also can enhance Britain's standing in international affairs. Therefore, Britain seized the very opportunity to maintain consistency with the United States.However, there were some serious conflicts of interest between Britain and the United States in other parts of the world. It seemed that there are no so-called special relations between them. From time to time, the United States was dragged on the British interest edge, mainly because Britain wanted the United States to bear some responsibilities for it, while Britain did not want itself to be the most powerful country as to bear the responsibility of maintaining the present situation.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.234
Threshold uncertainty score0.466

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 studies0.0210.004
Scholarly communication0.0080.003
Open science0.0010.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0270.003

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 head0.013
GPT teacher head0.312
Teacher spread0.298 · 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 designQualitative
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

Citations0
Published2010
Admission routes1
Has abstractyes

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