Bibliographic record
Abstract
Trump’s foreign policy was controversial, resulting in division into its supporters and adversaries both at national and international levels. Donald Trump managed to be flexible in relations with the Legislative, ignoring the democratic majority in the House of Representatives. However, it was possible only before the Covid-19 pandemic. Donald Trump’s foreign policy prioritized American capital that determined US relations with the EU, Canada, and Latin America. As for relations with Russia, they were defined by the Ukrainian crisis. Disarmament is still a cornerstone in Russian American relations. The US has complicated relations with countries in Latin America, the Middle East, and the Persian Gulf despite all efforts. The UN’s reform and the Security Council, where the three great powers primarily make decisions, are still questioned. The US divides Europe into three parts; Western Europe, Eastern Europe, and Russia with Belarus. These Europes have different views on US foreign policy. Republican administration aimed at the expansion of the national power and provision of global leadership. However, the implementation methods were questionable and led to some unpleasant consequences for the US allies. Some of them decided to wait, some prepared for the worst, some tried to adapt to Trump’s policy since it reflected the long-term changes of the US standing in the world regardless of the party or the president. As a result, such policy led to the defeat of the Republicans and brought Joe Biden to power.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 0.015 |
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".