The Trump Administration's Strategy for the Arab States of the Persian Gulf
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".