A estratégia de Trump para o investimento estrangeiro: do NAFTA ao USMCA
Bibliographic record
Abstract
Donald Trump fulfilled a campaign promise by opening the North American Free Trade Agreement (NAFTA) to renegotiation. Although the country is the largest exporter of capital in the world, the level of protection offered to investors has been reduced in the new agreement called the USMCA (United States-Mexico-Canada Agreement). This contradicts the United States' record of defending an agenda of investment protection and liberalization. The objective of this thesis will be to trace the negotiation process and the strategic logic behind this change of position conducted by the new administration. The case study will be carried out by means of a bibliographic and documentary review that will allow mapping both the previous historical path and the most recent negotiation process. The working hypothesis is that the renegotiation has as objective to reverse the alleged redirection of jobs of which the president, curiously agreeing with sectors of the American left, accuses NAFTA. Through a very sophisticated adjustment to the wording of chapter 14 of the USMCA, the United States seeks to restrict the application of investment clauses to sectors that for reasons intrinsic to their economic nature could not return to operate from the United States, such as the petrochemical, utilities and infrastructure sectors. On the other hand, some adjustments seek to respond to criticisms that have been made to the investment treaty regime, in general, and to NAFTA itself, in particular, since the 1990s. These reforms seek to reinforce the State's right to regulate for the benefit of its population and prevent it from being held responsible for mere breaches of profit expectations in investor-State dispute settlement (ISDS) procedures. Despite accusations of having put several economic sectors at risk with no prospect of benefits for the country, it was possible to identify a clear strategic orientation in the process of negotiating the investment chapter of the new agreement.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| 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 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".