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 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 | 0.002 | 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) | 0.002 | 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".