Regímenes internacionales sobre servicios e inversiones: el estándar estadounidense inferido del USMCA
Bibliographic record
Abstract
Procura-se neste artigo examinar o desenvolvimento dos regimes internacionais sobre o comércio de serviços – especificamente serviços financeiros, telecomunicações e serviços digitais – e sobre investimentos, colocando em perspectiva comparada o Tratado Norte-Americano de Livre Comércio (North American Free Trade Agreement – NAFTA) e o Acordo Estados Unidos-México-Canadá (United States-Mexico-Canada Agreement – USMCA). A administração Donald Trump toma o deficit comercial como critério para precisar até que ponto outros países têm “se aproveitado” dos Estados Unidos. Sendo assim, busca obsessivamente aumentar as exportações e diminuir as importações do país. As regras sobre o comércio de serviços e sobre investimentos são estratégicas para contribuir com o sinal positivo nessa equação. Logo, elas ocupam lugar de destaque na agenda comercial atual. Não obstante, tais regras refletem muitos objetivos bipartidários de longa data. Na década de 1990, foram inseridas forçosamente pelos negociadores americanos nos fóruns comerciais internacionais a fim de servir de instrumento para o país enfrentar a concorrência econômica. Nos dias atuais, com o USMCA, que espelha muito do conteúdo do Acordo de Parceria Transpacífica (Trans-Pacific Partnership – TPP), tornam a servir de instrumento em favor das estruturas políticas e econômicas dos Estados Unidos.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".