Bibliographic record
Abstract
As of the beginning of February 2025, Donald Trump has been president for just a few weeks, and already he has dramatically altered and impacted US foreign policy and the international system. In a matter of a few days, as part of his “America First” policy, Trump’s administration has reassessed and ended a number of the United States’ prior international commitments, including withdrawing from the World Health Organization (WHO) and the Paris Agreement on climate change. He has urged NATO allies to increase financial burden sharing, announced tariffs on imports against China, Canada, and Mexico, and sanctioned the International Criminal Court (ICC), arguing that it is improperly targeting US and Israeli individuals. He has also expressed an interest in buying Greenland and retaking possession of the Panama Canal, and suggested taking over Gaza and removing the Palestinian population. More generally, Trump is abandoning both the tenets of US foreign policy held for decades and the benchmarks of international legitimacy as outlined by international law. International competition tamed by cooperation is no longer the name of the game. Raw competition and leverage for one’s own benefit regardless of the impact on others appear to be the modus operandi of the new Trump administration.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.445 | 0.400 |
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".