Bibliographic record
Abstract
Formulation of the problem: In the article management problems are examined Geographic proximity has ensured strong linkages between the United States and Latin America and the Caribbean, based on diverse U.S. interests, including economic, political, and securityт concerns. The United States is a major trading partner and the largest source of foreign investment for many countries in the region, with free-trade agreements enhancing economic linkages with 11 countries. Purpose of the research: The region is a large source of U.S. immigration, both legal and illegal; proximity and economic and security conditions are major factors driving migration. Curbing the flow of illicit drugs has been a key component of U.S. relations with the region for more than three decades and currently involves close security cooperation with Mexico, Central America, and the Caribbean. U.S. support for democracy and human rights in the region has been long-standing, with particular current focus on Cuba, Nicaragua, and Venezuela. The article analyzes the priorities of Administration of President Trump ordered U.S. withdrawal from the proposed Trans-Pacific Partnership trade agreement, which would have increased U.S. economic linkages with Mexico, Chile, and Peru. President Trump criticized the North American Free Trade Agreement (NAFTA) with Mexico and Canada as unfair, warned that the United States might withdraw, and initiated renegotiations; ultimately, the three countries agreed to a United States-Mexico-Canada Agreement in late September 2018. The proposed agreement, which requires congressional approval, largely leaves NAFTA intact but includes some updates and changes, especially to the dairy and auto industries. Administration actions on immigration have caused concern in the region, including efforts to end the deportation relief program known as Deferred Action for Childhood Arrivals (DACA) and Temporary Protected Status (TPS) designations for Nicaragua, Haiti, El Salvador, and Honduras. President Trump unveiled a new policy in 2017 toward Cuba partially rolling back U.S. efforts to normalize relations and imposing new sanctions.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".