Bibliographic record
Abstract
The article aims to analyze the basic directions and preliminary results of President Trump’s policy in a sphere of foreign economic relations. It is shown mayor goals and reasons of ongoing radical reforms in the U.S. foreign economic relations. Among declared principles of new foreign economic strategy – ensuring of national security, strengthening of American economy, achievement of more beneficial agreements for the USA, promotion of American law into international trade practice, reforms of multilateral international trade system. To promote these principles President Trump’s administration undertook several steps to reform country’s foreign economic policy, including growth of import tariffs on solar batteries and on steel and aluminum. The U.S. Administration raised national security concern about unfair trade practices in a sphere of technology policies, mandated technology transfer and intellectual property. Among other steps – impose of increased tariffs on automobiles and parts, threat to impose sanctions against Mexico in conjunction with illegal immigrants from this country. A special attention in President Tramp’s strategy in paid to China. The author analyses the U.S. complaints about Chinese policy. Among them – to stop an intellectual property theft and forced technology requirements, to reduce trade deficit and to stop currency rate manipulations. The article also reviews the economic relations between USA and China, which brought many benefits to both countries, as well as some losses. On one side, the U.S. exports to China contributed to creation of new jobs in the USA, on the other – the transfer of companies from the USA to China led to job destruction in the USA, especially in manufacturing. U.S. consumers have also gained from trade with China. The lower-priced imports from China reduced an inflation and led to variety of goods on consumer market. The author analyses the problem of trade deficit of the U.S. with China and other countries, arguing that other factors should be accounted. The overall size of the U.S. trade disbalance is largely a function of low U.S. domestic savings relative to its investment needs, rather than the result of foreign trade barriers. The author makes a conclusion that the current U.S. foreign economic strategy has serious contradictions. Many decisions made by U.S. Administrations turned to financial losses for U.S. companies and consumers. It is noted that following current strategy the President Trump’s administration is trying to reach not only short-term goals (to reduce trade deficit, for example), but is seeking the long-term goals – to strengthen economic and technological security of the USA in a situation of exacerbation of international competition.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".