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Record W3184726861 · doi:10.31857/s268667300015580-8

The Trump Administration's Strategy for the Arab States of the Persian Gulf

2021· article· en· W3184726861 on OpenAlexaff
Nikolay Bobkin

Bibliographic record

VenueUSA & Canada Economics – Politics – Culture · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East and Rwanda Conflicts
Canadian institutionsInstitute for Christian Studies
Fundersnot available
KeywordsPersianAbandonment (legal)Administration (probate law)Middle EastGulf warPolitical scienceIntervention (counseling)Power (physics)Development economicsPolitical economyEconomyLawEconomic historyHistoryEconomicsPsychology

Abstract

fetched live from OpenAlex

Under President Trump, the Persian Gulf has become the source of a significant increase in instability in the Middle East. The policy of maximum pressure on Iran involved strengthening the US presence and strengthening cooperation with Arab allies. The purpose of this article is to analyze the internal and external aspects of Trump's Gulf strategy. The article examines its policy towards Saudi Arabia, the United Arab Emirates and Qatar. The main attention is paid to the analysis of the decisions of the President of the U.S.A that led to the growth of military tension. There are well-grounded arguments in defense of the scientific hypothesis put forward by the author that the emphasis on commercial relations and arms sales was a decisive factor in Trump's strategy. This led to the abandonment of US policy criticizing the human rights situation in Saudi Arabia, the renewal of US military intervention in the war in Yemen, and America's return to the supply of the most modern weapons to the United Arab Emirates. It is shown that the deepening of military cooperation with the Gulf states was aimed at increasing the security of Israel and changing the balance of power not in favor of Iran.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.966
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.259
Teacher spread0.237 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

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