Bibliographic record
Abstract
During 2021, the International Security Studies Forum (issf) posted a series of articles on H-Diplo, the Diplomatic and International History discussion network, in which leading scholars of U.S. foreign relations assess the legacy of President Donald J. Trump's policies in world affairs.As the editors explain, these essays examine and evaluate "the effects of the Trump presidency, from a range of different perspectives, and in light of the events of the Trump years, . . . on the United States' standing in the world."1Many articles address the impact of Trump's policies on specific regions and nations, including India, France, Britain, Germany, Russia, Canada, Palestine, the Middle East, and Latin America.There also are essays covering major issues, such as, to name a few, Brexit, economic sanctions, racism, the arms trade, human rights, the environment, intelligence, and international law.As for East Asia, only one article deals with a specific country-the People's Republic of China (prc).However, Dayna Barnes of City, University of London has contributed an appraisal of the effects of Trump's policies on the region overall.She writes disapprovingly about how Trump weakened U.S. alliances with Japan and South Korea with threats to withdraw American protection unless the two nations paid more for U.S. defense.He also did nothing to reverse a steady deterioration in relations with the Philippines.Barnes sharply criticizes Trump's withdrawal from the Trans-Pacific Partnership that has squandered "a chance to write the rules that shape trade decisions in accordance with American interests and values . ..." While crediting Trump for opening a new channel to control North Korea's nuclear ambitions, she finds unwise his heightening of public support for Taiwan.Worst of all, Trump "gave ammunition to regimes which are sceptical 1
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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 teacher head, 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".