ANALISIS ALASAN AMERIKA SERIKAT MENGINISIASI PERUBAHAN NAFTA MENJADI USMCA
Bibliographic record
Abstract
NAFTA is a North American Regional Economic Cooperation consisting of the United States, Mexico and Canada. NAFTA was renegotiated on November 30, 2018 to become USMCA at the G20 Summit in Argentina. The United States is the country that initiated NAFTA into USMCA since the beginning of President Donald Trump's administration. This research aims to determine the reasons for the United States initiating the change from NAFTA to USMCA. The data used is data from 2012-2018. This research uses Graham T. Allison's Decision Making Model Theory. Based on data from WITS WorldBank, it is stated that the United States experienced a trade balance deficit against Mexico and Canada when NAFTA was operating. Apart from that, the United States is also experiencing the problem of declining employment numbers due to the United States' efforts to increase the country's economic growth. These factors were the reason the United States initiated the change from NAFTA to USMCA.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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 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".