Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The U. S. President Trump administration has made NAFTA re-negotiation and modernization a priority of its trade policy. D. Trump has repeatedly characterized this agreement as the “worst trade deal” in history and has stated that he may seek to withdraw from the agreement. The U. S. talks with Mexico and Canada began on August 16, 2017. After more than a year of intense negotiations the three North American countries have finally reached a deal that was renamed Agreemrnt between the United States of America, the United Mexican States, and Canada (USMCA). USMCA is based on the NAFTA. Among the most prominent changes are the following: American farmers gain easier access to the tightly regulated Canadian dairy market; guidelines to have a higher proportion of automobiles and spare parts manufactured amongst the three countries rather than imported from abroad; strengthened environmental and labor regulations, increased intellectual rights protection and de minimis customs threshold for duty free treatment. New issues, such as digital trade, currency manipulation, stronger disciplines for operations of the state-owned enterprises, and relations with non-market economies, are also addressed. They may serve as a template for trade deals under the Trump administration in the future. The USMCA will take effect after ratification by all three parties, which is probable but not guaranteed. This article analyses key changes in USMCA by comparing it with NAFTA; describes peculiarities of the NAFTA re-negotiation; identifies winners and losers; assesses perspectives of USMCA ratification and its international consequences. The United States-Mexico-Canada Agreement represents a mix of free trade provisions with elements of managed trade, especially in the automotive industry. Its mere signing is not a small accomplishment in the era of backlash to free trade and economic globalization.
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.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 it