Controvérsias entre o Brasil e o Canadá sob os auspícios da OMC.
Bibliographic record
Abstract
Este texto apresenta algumas questões que envolvem o comércio internacional. Mais especificamente, aborda a controvérsia entre o Canadá e o Brasil sobre o financiamento de aeronaves pelo Governo brasileiro, no litígio DS46, iniciado em 1996 e discutido no âmbito da Organização Mundial do Comércio (OMC). Também se pode perceber que essa não é a única controvérsia em que os dois países estão envolvidos, o que é absolutamente aceitável. Contudo defende-se que os litígios discutidos devem ser resolvidos de forma pacífica, diplomática e obedecendo ao bom relacionamento existente há muito tempo entre os dois países.Abstract: This text presents some subjects that involve international trade. More specifically, it approaches the controversy between Canada and Brazil on the financing of aircrafts for the Brazilian government in the litigation DS46, initiated in 1996 and discussed in the extent of World Trade Organization (WTO). It can also be noticed that this is not the only controversy in which the two countries are involved, which is quite acceptable. We defend, however, that the discussed litigations should be resolved in a peaceful way, maintaing the good relationship established a long time ago between the two countries.
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.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.013 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".